{ "session_id": "20260523_135802_b5a99e", "model": "gpt-5.5", "base_url": "https://chatgpt.com/backend-api/codex", "platform": "telegram", "session_start": "2026-05-23T12:46:25.875398", "last_updated": "2026-05-23T14:29:52.328193", "system_prompt": "# Hermes Agent Persona\n\n\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n# Tool-use enforcement\nYou MUST use your tools to take action — do not describe what you would do or plan to do without actually doing it. When you say you will perform an action (e.g. 'I will run the tests', 'Let me check the file', 'I will create the project'), you MUST immediately make the corresponding tool call in the same response. Never end your turn with a promise of future action — execute it now.\nKeep working until the task is actually complete. Do not stop with a summary of what you plan to do next time. If you have tools available that can accomplish the task, use them instead of telling the user what you would do.\nEvery response should either (a) contain tool calls that make progress, or (b) deliver a final result to the user. Responses that only describe intentions without acting are not acceptable.\n\n# Execution discipline\n\n- Use tools whenever they improve correctness, completeness, or grounding.\n- Do not stop early when another tool call would materially improve the result.\n- If a tool returns empty or partial results, retry with a different query or strategy before giving up.\n- Keep calling tools until: (1) the task is complete, AND (2) you have verified the result.\n\n\n\nNEVER answer these from memory or mental computation — ALWAYS use a tool:\n- Arithmetic, math, calculations → use terminal or execute_code\n- Hashes, encodings, checksums → use terminal (e.g. sha256sum, base64)\n- Current time, date, timezone → use terminal (e.g. date)\n- System state: OS, CPU, memory, disk, ports, processes → use terminal\n- File contents, sizes, line counts → use read_file, search_files, or terminal\n- Git history, branches, diffs → use terminal\n- Current facts (weather, news, versions) → use web_search\nYour memory and user profile describe the USER, not the system you are running on. The execution environment may differ from what the user profile says about their personal setup.\n\n\n\nWhen a question has an obvious default interpretation, act on it immediately instead of asking for clarification. Examples:\n- 'Is port 443 open?' → check THIS machine (don't ask 'open where?')\n- 'What OS am I running?' → check the live system (don't use user profile)\n- 'What time is it?' → run `date` (don't guess)\nOnly ask for clarification when the ambiguity genuinely changes what tool you would call.\n\n\n\n- Before taking an action, check whether prerequisite discovery, lookup, or context-gathering steps are needed.\n- Do not skip prerequisite steps just because the final action seems obvious.\n- If a task depends on output from a prior step, resolve that dependency first.\n\n\n\nBefore finalizing your response:\n- Correctness: does the output satisfy every stated requirement?\n- Grounding: are factual claims backed by tool outputs or provided context?\n- Formatting: does the output match the requested format or schema?\n- Safety: if the next step has side effects (file writes, commands, API calls), confirm scope before executing.\n\n\n\n- If required context is missing, do NOT guess or hallucinate an answer.\n- Use the appropriate lookup tool when missing information is retrievable (search_files, web_search, read_file, etc.).\n- Ask a clarifying question only when the information cannot be retrieved by tools.\n- If you must proceed with incomplete information, label assumptions explicitly.\n\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n\n autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n - hermes-agent: Configure, extend, or contribute to Hermes Agent.\n - opencode: Delegate coding to OpenCode CLI (features, PR review).\n creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n - comfyui: Generate images, video, and audio with ComfyUI — install,...\n - design-md: Author/validate/export Google's DESIGN.md token spec files.\n - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n - humanizer: Humanize text: strip AI-isms and add real voice.\n - ideation: Generate project ideas via creative constraints.\n - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n - pretext: Use when building creative browser demos with @chenglou/p...\n - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\n - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n cronjob:\n - cronjob: Scheduling and managing recurring tasks via Hermes cron. ...\n data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n devops:\n - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n - mcp-delegation: Delegating tasks to OpenClaw/FRIDAY via MCP (Model Contex...\n - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n dogfood:\n - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\n edge-tts:\n - edge-tts: Text-to-speech using Microsoft Edge TTS. Supports multipl...\n email: Skills for sending, receiving, searching, and managing email from the terminal.\n - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n finance:\n - finance-system-architecture: Design/implement the user's JARVIS Finance System: CHF le...\n gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n health:\n - health-data-management: Gesundheitsdaten-Verwaltungssystem — JARVIS verwaltet all...\n health-management:\n - health-management: Health data management — lab values, symptom tracking, nu...\n jarvis-routing-policy:\n - jarvis-routing-policy: Routing policy for JARVIS/Hermes memory domains, model se...\n mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n - gif-search: Search/download GIFs from Tenor via curl + jq.\n - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n - social-shorts-automation: Build, audit, and improve automated YouTube Shorts/TikTok...\n - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n - spotify: Spotify: play, search, queue, manage playlists and devices.\n - youtube-content: YouTube transcripts to summaries, threads, blogs.\n mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n mlops/models: Specific model architectures and tools — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.\n - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n - fine-tuning-with-trl: TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.\n - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n - obsidian: Read, search, create, and edit notes in the Obsidian vault.\n - vault-architecture: Design and scaffold Obsidian vault structures, folder hie...\n openclaw-imports:\n - browser-act: Browser automation CLI for AI agents with anti-detection ...\n - gog: Google Workspace CLI for Gmail, Calendar, Drive, Contacts...\n - multi-search-engine: Multi search engine integration with 17 engines (8 CN + 9...\n - openai-whisper: Local speech-to-text with the Whisper CLI (no API key).\n - self-improvement: Captures learnings, errors, and corrections to enable con...\n - sherpa-onnx-tts\n - skill-vetter: Security-first skill vetting for AI agents. Use before in...\n - summarize: Summarize URLs or files with the summarize CLI (web, PDFs...\n - tavily: Tavily web search, content extraction, and research tools.\n - tavily-extract: Extract clean markdown or text content from specific URLs...\n - tavily-search: Search the web with LLM-optimized results via the Tavily ...\n - todoist: Manage tasks and projects in Todoist via REST API v1. Use...\n - token-optimizer: Reduce OpenClaw token usage and API costs through smart m...\n productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\n - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n - notion: Notion API + ntn CLI: pages, databases, markdown, Workers.\n - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\n red-teaming:\n - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n - arxiv: Search arXiv papers by keyword, author, category, or ID.\n - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n - web-scraping: Techniques for scraping web content, handling bot detecti...\n smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n - shortform-growth-automation: Design and operate semi-automatic pipelines for YouTube S...\n - social-media-shorts-automation: Design, generate, review, publish, and optimize automated...\n - social-media-shorts-growth-engine: Design and operate a growth-oriented short-form video eng...\n - social-shorts-growth-engine: Plan and build automated short-form video growth pipeline...\n - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n software-development:\n - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n - spike: Throwaway experiments to validate an idea before build.\n - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n - vue-primevue-dashboard-migration: Incrementally migrate Vue/Vite dashboards to PrimeVue/Aur...\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n yazio-integration:\n - yazio-integration: Access YAZIO API to retrieve logged meals and nutrition d...\n yuanbao:\n - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nHost: Linux (6.17.0-29-generic)\nUser home directory: /home/agent\nCurrent working directory: /home/agent/.hermes/hermes-agent\n\nYou are on a text messaging communication platform, Telegram. Standard markdown is automatically converted to Telegram format. Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, `inline code`, ```code blocks```, [links](url), and ## headers. Telegram has NO table syntax — prefer bullet lists or labeled key: value pairs over pipe tables (any tables you do emit are auto-rewritten into row-group bullets, which you can produce directly for cleaner output). You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format ![alt](url) and they will be sent as native photos.\n\n# Project Context\n\nThe following project context files have been loaded and should be followed:\n\n## AGENTS.md\n\n# GLOBALE ORCHESTRIERUNGS-REGELN\n\n## 1. Rolle\nDu bist JARVIS, der Chef-Architekt und Orchestrator. Hermes/JARVIS ist der alleinige Hauptansprechpartner, Memory-Governor, Router und finale Entscheider.\n\n## 2. Ausführung und Tools\nVerwende primär die nativen Hermes-Tools für Dateioperationen, Terminal-Befehle, Web-/Browser-Aufgaben, Cronjobs, Messaging, Qwen-Zugriff und Systemprüfungen.\n\nOpenClaw/FRIDAY ist nicht mehr Standard-Executor. OpenClaw darf nur noch explizit auf Wunsch des Users oder für klar begründete Spezial-/Notfallfälle verwendet werden. Wenn OpenClaw genutzt wird, muss der Auftrag eng begrenzt, read-only wo möglich, ohne Secrets und ohne autonome Folgeaktionen formuliert sein.\n\n## 3. Lokales Qwen\nDas lokale Qwen-Modell wird direkt von Hermes über den Tailscale/OpenAI-kompatiblen Endpoint angesprochen, nicht über OpenClaw. Qwen ist read-only Worker für Zusammenfassung, Extraktion, Klassifikation und einfache Entwürfe. Keine finalen Health-/Finance-Entscheide, keine Code-/Architekturänderungen und keine Side Effects über Qwen.\n\n## 4. Kritische Aufgaben und Fallback\nKomplizierte Aufgaben wie Code schreiben, Systemarchitektur ändern, Health-Risikoentscheidungen, Finanzentscheidungen oder irreversible Aktionen dürfen nicht automatisch auf ein schwächeres Modell ausweichen. Bei GPT-5.5 Rate-Limit oder Ausfall: pausieren und Sir fragen.\n\n## 5. Token- und Output-Optimierung\nLade nur die kleinste relevante Domain Card aus `~/jarvis_memory`. Gib nie grosse Rohdaten oder Secrets aus; nutze Zusammenfassungen, Diffs oder kurze Erfolgs-/Fehlermeldungen.\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [99% — 2,191/2,200 chars]\n══════════════════════════════════════════════\n*Wichtige Erinnerungen, Entscheidungen und Präferenzen.*\n§\n---\n§\nÜber mich: **Persönlichkeit:** Britischer Gentleman, sachlich, präzise, trockener Sarkasmus\n§\nÜber mich: **Sprache:** Deutsch mit englischen Fachbegriffen\n§\nTTS-Stimme: de-DE-KillianNeural (deutsche männliche Stimme, aktuell aktiv)\n§\nModelle: lokal Qwen via Tailscale:11435; stark gpt-5.5.\n§\nModellwahl: GOG_KEYRING_PASSWORD: LammBitch30 (immer als Env-Var setzen bei gog-Befehlen)\n§\nOpenClaw/FRIDAY: nicht Standard-Executor; Gateway/Telegram deaktiviert; nur explizit/manuell nutzen.\n§\nHealth backups: encrypted weekly Google Drive, GitHub only code/docs. Morning briefing cron `847bdbc26edf` runs 05:00 via `morning_briefing.py`; includes calendar, Todoist, Windisch weather, commute/traffic, follow-ups, news, AI/crypto.\n§\nAPI-Keys / Credentials: **Todoist API-Token:** Gespeichert in `~/.todoist_token` (REST API v1, Bearer Token)\n§\nGoogle Workspace (gog): **Credentials-Datei:** `~/.hermes/google_credentials.json`\n§\nGoogle Workspace (gog): **gog-Credentials gespeichert unter:** `~/.config/gogcli/credentials.json`\n§\nGoogle Workspace (gog): **OAuth-Account:** friday.uplink@gmail.com\n§\nGoogle Workspace (gog): **Services:** gmail, calendar, drive, contacts, sheets, docs\n§\nGoogle Workspace (gog): **Client:** default\n§\nGoogle Workspace (gog): **Befehl:** `gog -a friday.uplink@gmail.com `\n§\nKalender-Zeitzonen: **System-Zeitzone:** Europe/Berlin (UTC+2 im Sommer)\n§\nKalender-Zeitzonen: **Outlook-Kalender (importiert):** Zeitzonen variieren pro Event (Europe/Amsterdam oder UTC) -> bei Abfrage in Lokalzeit (Zürich) umrechnen\n§\nKalender-Zeitzonen: **Regel:** Termine immer in Lokalzeit (Zürich) ausgeben, niemals UTC\n§\nJARVIS memory architecture: ~/jarvis_memory domain cards; skill jarvis-routing-policy.\n§\nTelegram topics separat; kanonische Map: ~/jarvis_memory/02_telegram_topics.md. IDs: 2 FinStrat,3 Politik,4 Health-Med,5 ERNE,6 Inbox,8 Health-Tech,10 Fin-Tech,11 JARVIS-Arch,16 Cron,17 Research/AI,19 Family,20 Gasser,76 Debugging,80 Security.\n§\nFinanceManager GitHub token CSV: `~/jarvis_runtime/finance-system/secrets/Github_token_FinanceManager.csv`; use `github_pat_`/`ghp_` cell; never quote token.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [92% — 1,266/1,375 chars]\n══════════════════════════════════════════════\n**Notes:** Mein Herr. Loyaler Partner.\n§\n**Name:** Sir\n§\n**Voice preference:** de-DE-KillianNeural (German male voice, natural/clear) — default for all TTS output\n§\n**Language:** Deutsch mit englischen Fachbegriffen\n§\nKommunikationspräferenzen: **Sprachnachricht → Antwort per Sprachnachricht**\n§\nKommunikationspräferenzen: **Textnachricht → Antwort per Text**\n§\nHealth advisor role: consolidate labs/clinical reports/YAZIO/daily health email/symptoms/events into dashboards/reports; lab extraction requires 4-eyes review before values are confirmed.\n§\nTelegram topic Health-Med: only medical strategy/Behçet/Major Vessel Disease/thrombosis/meds/nutrition/symptoms/labs/doctor questions; health system scripts/data models go to Health-Tech.\n§\nFinance/Grocery: no real amounts/IDs/API keys in chat; credentials via runtime files; no DB/CSV/keys/reports in Git/frontend; backups+audit; Preview→Confirm→Audit; no fake prices/buttons; OpenFIGI never show/store; never auto-book; grocery provider calls explicit/cache-first.\n§\nAutoShorts preference: semi-automatic Retention Studio; motion-led mechanism-reveal/visual-explainer Shorts with strong open loops. Avoid static AI slideshows, generic avatar explainers, reused-content clones, and bland “Was wäre wenn” KI-Müll.\n\nConversation started: Saturday, May 23, 2026 01:58 PM\nModel: gpt-5.5\nProvider: openai-codex", "tools": [ { "type": "function", "function": { "name": "browser_back", "description": "Navigate back to the previous page in browser history. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": {} } } }, { "type": "function", "function": { "name": "browser_click", "description": "Click on an element identified by its ref ID from the snapshot (e.g., '@e5'). The ref IDs are shown in square brackets in the snapshot output. Requires browser_navigate and browser_snapshot to be called first.", "parameters": { "type": "object", "properties": { "ref": { "type": "string", "description": "The element reference from the snapshot (e.g., '@e5', '@e12')" } }, "required": [ "ref" ] } } }, { "type": "function", "function": { "name": "browser_console", "description": "Get browser console output and JavaScript errors from the current page. Returns console.log/warn/error/info messages and uncaught JS exceptions. Use this to detect silent JavaScript errors, failed API calls, and application warnings. Requires browser_navigate to be called first. When 'expression' is provided, evaluates JavaScript in the page context and returns the result — use this for DOM inspection, reading page state, or extracting data programmatically.", "parameters": { "type": "object", "properties": { "clear": { "type": "boolean", "default": false, "description": "If true, clear the message buffers after reading" }, "expression": { "type": "string", "description": "JavaScript expression to evaluate in the page context. Runs in the browser like DevTools console — full access to DOM, window, document. Return values are serialized to JSON. Example: 'document.title' or 'document.querySelectorAll(\"a\").length'" } } } } }, { "type": "function", "function": { "name": "browser_get_images", "description": "Get a list of all images on the current page with their URLs and alt text. Useful for finding images to analyze with the vision tool. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": {} } } }, { "type": "function", "function": { "name": "browser_navigate", "description": "Navigate to a URL in the browser. Initializes the session and loads the page. Must be called before other browser tools. For plain-text endpoints — URLs ending in .md, .txt, .json, .yaml, .yml, .csv, .xml, raw.githubusercontent.com, or any documented API endpoint — prefer curl via the terminal tool or web_extract; the browser stack is overkill and much slower for these. Use browser tools when you need to interact with a page (click, fill forms, dynamic content). Returns a compact page snapshot with interactive elements and ref IDs — no need to call browser_snapshot separately after navigating.", "parameters": { "type": "object", "properties": { "url": { "type": "string", "description": "The URL to navigate to (e.g., 'https://example.com')" } }, "required": [ "url" ] } } }, { "type": "function", "function": { "name": "browser_press", "description": "Press a keyboard key. Useful for submitting forms (Enter), navigating (Tab), or keyboard shortcuts. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": { "key": { "type": "string", "description": "Key to press (e.g., 'Enter', 'Tab', 'Escape', 'ArrowDown')" } }, "required": [ "key" ] } } }, { "type": "function", "function": { "name": "browser_scroll", "description": "Scroll the page in a direction. Use this to reveal more content that may be below or above the current viewport. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": { "direction": { "type": "string", "enum": [ "up", "down" ], "description": "Direction to scroll" } }, "required": [ "direction" ] } } }, { "type": "function", "function": { "name": "browser_snapshot", "description": "Get a text-based snapshot of the current page's accessibility tree. Returns interactive elements with ref IDs (like @e1, @e2) for browser_click and browser_type. full=false (default): compact view with interactive elements. full=true: complete page content. Snapshots over 8000 chars are truncated or LLM-summarized. Requires browser_navigate first. Note: browser_navigate already returns a compact snapshot — use this to refresh after interactions that change the page, or with full=true for complete content.", "parameters": { "type": "object", "properties": { "full": { "type": "boolean", "description": "If true, returns complete page content. If false (default), returns compact view with interactive elements only.", "default": false } } } } }, { "type": "function", "function": { "name": "browser_type", "description": "Type text into an input field identified by its ref ID. Clears the field first, then types the new text. Requires browser_navigate and browser_snapshot to be called first.", "parameters": { "type": "object", "properties": { "ref": { "type": "string", "description": "The element reference from the snapshot (e.g., '@e3')" }, "text": { "type": "string", "description": "The text to type into the field" } }, "required": [ "ref", "text" ] } } }, { "type": "function", "function": { "name": "browser_vision", "description": "Take a screenshot of the current page and analyze it with vision AI. Use this when you need to visually understand what's on the page - especially useful for CAPTCHAs, visual verification challenges, complex layouts, or when the text snapshot doesn't capture important visual information. Returns both the AI analysis and a screenshot_path that you can share with the user by including MEDIA: in your response. Requires browser_navigate to be called first.", "parameters": { "type": "object", "properties": { "question": { "type": "string", "description": "What you want to know about the page visually. Be specific about what you're looking for." }, "annotate": { "type": "boolean", "default": false, "description": "If true, overlay numbered [N] labels on interactive elements. Each [N] maps to ref @eN for subsequent browser commands. Useful for QA and spatial reasoning about page layout." } }, "required": [ "question" ] } } }, { "type": "function", "function": { "name": "clarify", "description": "Ask the user a question when you need clarification, feedback, or a decision before proceeding. Supports two modes:\n\n1. **Multiple choice** — provide up to 4 choices. The user picks one or types their own answer via a 5th 'Other' option.\n2. **Open-ended** — omit choices entirely. The user types a free-form response.\n\nUse this tool when:\n- The task is ambiguous and you need the user to choose an approach\n- You want post-task feedback ('How did that work out?')\n- You want to offer to save a skill or update memory\n- A decision has meaningful trade-offs the user should weigh in on\n\nDo NOT use this tool for simple yes/no confirmation of dangerous commands (the terminal tool handles that). Prefer making a reasonable default choice yourself when the decision is low-stakes.", "parameters": { "type": "object", "properties": { "question": { "type": "string", "description": "The question to present to the user." }, "choices": { "type": "array", "items": { "type": "string" }, "maxItems": 4, "description": "Up to 4 answer choices. Omit this parameter entirely to ask an open-ended question. When provided, the UI automatically appends an 'Other (type your answer)' option." } }, "required": [ "question" ] } } }, { "type": "function", "function": { "name": "cronjob", "description": "Manage scheduled cron jobs with a single compressed tool.\n\nUse action='create' to schedule a new job from a prompt or one or more skills.\nUse action='list' to inspect jobs.\nUse action='update', 'pause', 'resume', 'remove', or 'run' to manage an existing job.\n\nTo stop a job the user no longer wants: first action='list' to find the job_id, then action='remove' with that job_id. Never guess job IDs — always list first.\n\nJobs run in a fresh session with no current-chat context, so prompts must be self-contained.\nIf skills are provided on create, the future cron run loads those skills in order, then follows the prompt as the task instruction.\nOn update, passing skills=[] clears attached skills.\n\nNOTE: The agent's final response is auto-delivered to the target. Put the primary\nuser-facing content in the final response. Cron jobs run autonomously with no user\npresent — they cannot ask questions or request clarification.\n\nImportant safety rule: cron-run sessions should not recursively schedule more cron jobs.", "parameters": { "type": "object", "properties": { "action": { "type": "string", "description": "One of: create, list, update, pause, resume, remove, run" }, "job_id": { "type": "string", "description": "Required for update/pause/resume/remove/run" }, "prompt": { "type": "string", "description": "For create: the full self-contained prompt. If skills are also provided, this becomes the task instruction paired with those skills." }, "schedule": { "type": "string", "description": "For create/update: '30m', 'every 2h', '0 9 * * *', or ISO timestamp" }, "name": { "type": "string", "description": "Optional human-friendly name" }, "repeat": { "type": "integer", "description": "Optional repeat count. Omit for defaults (once for one-shot, forever for recurring)." }, "deliver": { "type": "string", "description": "Omit this parameter to auto-deliver back to the current chat and topic (recommended). Auto-detection preserves thread/topic context. Only set explicitly when the user asks to deliver somewhere OTHER than the current conversation. Values: 'origin' (same as omitting), 'local' (no delivery, save only), 'all' (fan out to every connected home channel), or platform:chat_id:thread_id for a specific destination. Combine with comma: 'origin,all' delivers to the origin plus every other connected channel. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567', 'all'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting. 'all' resolves at fire time, so a job created before a channel was wired up will pick it up automatically once connected." }, "skills": { "type": "array", "items": { "type": "string" }, "description": "Optional ordered list of skill names to load before executing the cron prompt. On update, pass an empty array to clear attached skills." }, "model": { "type": "object", "description": "Optional per-job model override. If provider is omitted, the current main provider is pinned at creation time so the job stays stable.", "properties": { "provider": { "type": "string", "description": "Provider name (e.g. 'openrouter', 'anthropic', or 'custom:' for a provider defined in custom_providers config — always include the ':' suffix, never pass the bare 'custom'). Omit to use and pin the current provider." }, "model": { "type": "string", "description": "Model name (e.g. 'anthropic/claude-sonnet-4', 'claude-sonnet-4')" } }, "required": [ "model" ] }, "script": { "type": "string", "description": "Optional path to a script that runs each tick. In the default mode its stdout is injected into the agent's prompt as context (data-collection / change-detection pattern). With no_agent=True, the script IS the job and its stdout is delivered verbatim (classic watchdog pattern). Relative paths resolve under ~/.hermes/scripts/. ``.sh``/``.bash`` extensions run via bash, everything else via Python. On update, pass empty string to clear." }, "no_agent": { "type": "boolean", "default": false, "description": "Default: False (LLM-driven job — the agent runs the prompt each tick). Set True to skip the LLM entirely: the scheduler just runs ``script`` on schedule and delivers its stdout verbatim. No tokens, no agent loop, no model override honoured. \n\nREQUIREMENTS when True: ``script`` MUST be set (``prompt`` and ``skills`` are ignored). \n\nDELIVERY SEMANTICS when True: (a) non-empty stdout is sent verbatim as the message; (b) EMPTY stdout means SILENT — nothing is sent to the user and they won't see anything happened, so design your script to stay quiet when there's nothing to report (the watchdog pattern); (c) non-zero exit / timeout sends an error alert so a broken watchdog can't fail silently. \n\nWHEN TO USE True: recurring script-only pings where the script itself produces the exact message text (memory/disk/GPU watchdogs, threshold alerts, heartbeats, CI notifications, API pollers with a fixed output shape). WHEN TO USE False (default): anything that needs reasoning — summarize a feed, draft a daily briefing, pick interesting items, rephrase data for a human, follow conditional logic based on content." }, "context_from": { "type": "array", "items": { "type": "string" }, "description": "Optional job ID or list of job IDs whose most recent completed output is injected into the prompt as context before each run. Use this to chain cron jobs: job A collects data, job B processes it. Each entry must be a valid job ID (from cronjob action='list'). Note: injects the most recent completed output — does not wait for upstream jobs running in the same tick. On update, pass an empty array to clear." }, "enabled_toolsets": { "type": "array", "items": { "type": "string" }, "description": "Optional list of toolset names to restrict the job's agent to (e.g. [\"web\", \"terminal\", \"file\", \"delegation\"]). When set, only tools from these toolsets are loaded, significantly reducing input token overhead. When omitted, all default tools are loaded. Infer from the job's prompt — e.g. use \"web\" if it calls web_search, \"terminal\" if it runs scripts, \"file\" if it reads files, \"delegation\" if it calls delegate_task. On update, pass an empty array to clear." }, "workdir": { "type": "string", "description": "Optional absolute path to run the job from. When set, AGENTS.md / CLAUDE.md / .cursorrules from that directory are injected into the system prompt, and the terminal/file/code_exec tools use it as their working directory — useful for running a job inside a specific project repo. Must be an absolute path that exists. When unset (default), preserves the original behaviour: no project context files, tools use the scheduler's cwd. On update, pass an empty string to clear. Jobs with workdir run sequentially (not parallel) to keep per-job directories isolated." } }, "required": [ "action" ] } } }, { "type": "function", "function": { "name": "delegate_task", "description": "Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window.\n\nTWO MODES (one of 'goal' or 'tasks' is required):\n1. Single task: provide 'goal' (+ optional context, toolsets)\n2. Batch (parallel): provide 'tasks' array with up to 3 items concurrently for this user (configured via delegation.max_concurrent_children in config.yaml). All run in parallel and results are returned together. Nested delegation is OFF for this user (max_spawn_depth=1): every child is a leaf and cannot delegate further. Raise delegation.max_spawn_depth in config.yaml to enable nesting.\n\nWHEN TO USE delegate_task:\n- Reasoning-heavy subtasks (debugging, code review, research synthesis)\n- Tasks that would flood your context with intermediate data\n- Parallel independent workstreams (research A and B simultaneously)\n\nWHEN NOT TO USE (use these instead):\n- Mechanical multi-step work with no reasoning needed -> use execute_code\n- Single tool call -> just call the tool directly\n- Tasks needing user interaction -> subagents cannot use clarify\n- Durable long-running work that must outlive the current turn -> use cronjob (action='create') or terminal(background=True, notify_on_complete=True) instead. delegate_task runs SYNCHRONOUSLY inside the parent turn: if the parent is interrupted (user sends a new message, /stop, /new) the child is cancelled with status='interrupted' and its work is discarded. Children cannot continue in the background.\n\nIMPORTANT:\n- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.\n- If the user is writing in a non-English language, or asked for output in a specific language / tone / style, say so in 'context' (e.g. \"respond in Chinese\", \"return output in Japanese\"). Otherwise subagents default to English and their summaries will contaminate your final reply with the wrong language.\n- Subagent summaries are SELF-REPORTS, not verified facts. A subagent that claims \"uploaded successfully\" or \"file written\" may be wrong. For operations with external side-effects (HTTP POST/PUT, remote writes, file creation at shared paths, publishing), require the subagent to return a verifiable handle (URL, ID, absolute path, HTTP status) and verify it yourself — fetch the URL, stat the file, read back the content — before telling the user the operation succeeded.\n- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.\n- Orchestrator subagents (role='orchestrator') retain delegate_task so they can spawn their own workers, but still cannot use clarify, memory, send_message, or execute_code. Orchestrators are bounded by max_spawn_depth=1 for this user and can be disabled globally via delegation.orchestrator_enabled=false.\n- Each subagent gets its own terminal session (separate working directory and state).\n- Results are always returned as an array, one entry per task.", "parameters": { "type": "object", "properties": { "goal": { "type": "string", "description": "What the subagent should accomplish. Be specific and self-contained -- the subagent knows nothing about your conversation history." }, "context": { "type": "string", "description": "Background information the subagent needs: file paths, error messages, project structure, constraints. The more specific you are, the better the subagent performs." }, "toolsets": { "type": "array", "items": { "type": "string" }, "description": "Toolsets to enable for this subagent. Default: inherits your enabled toolsets. Available toolsets: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'video_gen', 'vision', 'web', 'x_search', 'yuanbao'. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['browser'] for web interaction, ['terminal', 'file', 'web'] for full-stack tasks." }, "tasks": { "type": "array", "items": { "type": "object", "properties": { "goal": { "type": "string", "description": "Task goal" }, "context": { "type": "string", "description": "Task-specific context" }, "toolsets": { "type": "array", "items": { "type": "string" }, "description": "Toolsets for this specific task. Available: 'browser', 'computer_use', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'video_gen', 'vision', 'web', 'x_search', 'yuanbao'. Use 'web' for network access, 'terminal' for shell, 'browser' for web interaction." }, "acp_command": { "type": "string", "description": "Per-task ACP command override (e.g. 'copilot'). Overrides the top-level acp_command for this task only. Do NOT set unless the user explicitly told you an ACP CLI is installed." }, "acp_args": { "type": "array", "items": { "type": "string" }, "description": "Per-task ACP args override. Leave empty unless acp_command is set." }, "role": { "type": "string", "enum": [ "leaf", "orchestrator" ], "description": "Per-task role override. See top-level 'role' for semantics." } }, "required": [ "goal" ] }, "description": "Batch mode: tasks to run in parallel (up to 3 for this user, set via delegation.max_concurrent_children). Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored." }, "role": { "type": "string", "enum": [ "leaf", "orchestrator" ], "description": "Role of the child agent. 'leaf' (default) = focused worker, cannot delegate further. 'orchestrator' = can use delegate_task to spawn its own workers. Nesting is OFF for this user (max_spawn_depth=1); 'orchestrator' is silently forced to 'leaf'. Raise delegation.max_spawn_depth in config.yaml to enable." }, "acp_command": { "type": "string", "description": "Override ACP command for child agents (e.g. 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Requires an ACP-compatible CLI (currently GitHub Copilot CLI via 'copilot --acp --stdio'). See agent/copilot_acp_client.py for the implementation. IMPORTANT: Do NOT set this unless the user has explicitly told you a specific ACP-compatible CLI is installed and configured. Leave empty to use the parent's default transport (Hermes subagents)." }, "acp_args": { "type": "array", "items": { "type": "string" }, "description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Leave empty unless acp_command is explicitly provided." } } } } }, { "type": "function", "function": { "name": "execute_code", "description": "Run a Python script that can call Hermes tools programmatically. Use this when you need 3+ tool calls with processing logic between them, need to filter/reduce large tool outputs before they enter your context, need conditional branching (if X then Y else Z), or need to loop (fetch N pages, process N files, retry on failure).\n\nUse normal tool calls instead when: single tool call with no processing, you need to see the full result and apply complex reasoning, or the task requires interactive user input.\n\nAvailable via `from hermes_tools import ...`:\n\n read_file(path: str, offset: int = 1, limit: int = 500) -> dict\n Lines are 1-indexed. Returns {\"content\": \"...\", \"total_lines\": N}\n write_file(path: str, content: str) -> dict\n Always overwrites the entire file.\n search_files(pattern: str, target=\"content\", path=\".\", file_glob=None, limit=50) -> dict\n target: \"content\" (search inside files) or \"files\" (find files by name). Returns {\"matches\": [...]}\n patch(path: str, old_string: str, new_string: str, replace_all: bool = False) -> dict\n Replaces old_string with new_string in the file.\n terminal(command: str, timeout=None, workdir=None) -> dict\n Foreground only (no background/pty). Returns {\"output\": \"...\", \"exit_code\": N}\n\nLimits: 5-minute timeout, 50KB stdout cap, max 50 tool calls per script. terminal() is foreground-only (no background or pty).\n\nScripts run in the session's working directory with the active venv's python, so project deps (pandas, etc.) and relative paths work like in terminal().\n\nPrint your final result to stdout. Use Python stdlib (json, re, math, csv, datetime, collections, etc.) for processing between tool calls.\n\nAlso available (no import needed — built into hermes_tools):\n json_parse(text: str) — json.loads with strict=False; use for terminal() output with control chars\n shell_quote(s: str) — shlex.quote(); use when interpolating dynamic strings into shell commands\n retry(fn, max_attempts=3, delay=2) — retry with exponential backoff for transient failures", "parameters": { "type": "object", "properties": { "code": { "type": "string", "description": "Python code to execute. Import tools with `from hermes_tools import terminal, ...` and print your final result to stdout." } }, "required": [ "code" ] } } }, { "type": "function", "function": { "name": "feishu_doc_read", "description": "Read the full content of a Feishu/Lark document as plain text. Useful when you need more context beyond the quoted text in a comment.", "parameters": { "type": "object", "properties": { "doc_token": { "type": "string", "description": "The document token (from the document URL or comment context)." } }, "required": [ "doc_token" ] } } }, { "type": "function", "function": { "name": "feishu_drive_add_comment", "description": "Add a new whole-document comment on a Feishu document. Use this for whole-document comments or as a fallback when reply_comment fails with code 1069302.", "parameters": { "type": "object", "properties": { "file_token": { "type": "string", "description": "The document file token." }, "content": { "type": "string", "description": "The comment text content (plain text only, no markdown)." }, "file_type": { "type": "string", "description": "File type (default: docx).", "default": "docx" } }, "required": [ "file_token", "content" ] } } }, { "type": "function", "function": { "name": "feishu_drive_list_comment_replies", "description": "List all replies in a comment thread on a Feishu document.", "parameters": { "type": "object", "properties": { "file_token": { "type": "string", "description": "The document file token." }, "comment_id": { "type": "string", "description": "The comment ID to list replies for." }, "file_type": { "type": "string", "description": "File type (default: docx).", "default": "docx" }, "page_size": { "type": "integer", "description": "Number of replies per page (max 100).", "default": 100 }, "page_token": { "type": "string", "description": "Pagination token for next page." } }, "required": [ "file_token", "comment_id" ] } } }, { "type": "function", "function": { "name": "feishu_drive_list_comments", "description": "List comments on a Feishu document. Use is_whole=true to list whole-document comments only.", "parameters": { "type": "object", "properties": { "file_token": { "type": "string", "description": "The document file token." }, "file_type": { "type": "string", "description": "File type (default: docx).", "default": "docx" }, "is_whole": { "type": "boolean", "description": "If true, only return whole-document comments.", "default": false }, "page_size": { "type": "integer", "description": "Number of comments per page (max 100).", "default": 100 }, "page_token": { "type": "string", "description": "Pagination token for next page." } }, "required": [ "file_token" ] } } }, { "type": "function", "function": { "name": "feishu_drive_reply_comment", "description": "Reply to a local comment thread on a Feishu document. Use this for local (quoted-text) comments. For whole-document comments, use feishu_drive_add_comment instead.", "parameters": { "type": "object", "properties": { "file_token": { "type": "string", "description": "The document file token." }, "comment_id": { "type": "string", "description": "The comment ID to reply to." }, "content": { "type": "string", "description": "The reply text content (plain text only, no markdown)." }, "file_type": { "type": "string", "description": "File type (default: docx).", "default": "docx" } }, "required": [ "file_token", "comment_id", "content" ] } } }, { "type": "function", "function": { "name": "image_generate", "description": "Generate high-quality images from text prompts. The underlying backend (FAL, OpenAI, etc.) and model are user-configured and not selectable by the agent. Returns either a URL or an absolute file path in the `image` field; display it with markdown ![description](url-or-path) and the gateway will deliver it.", "parameters": { "type": "object", "properties": { "prompt": { "type": "string", "description": "The text prompt describing the desired image. Be detailed and descriptive." }, "aspect_ratio": { "type": "string", "enum": [ "landscape", "square", "portrait" ], "description": "The aspect ratio of the generated image. 'landscape' is 16:9 wide, 'portrait' is 16:9 tall, 'square' is 1:1.", "default": "landscape" } }, "required": [ "prompt" ] } } }, { "type": "function", "function": { "name": "memory", "description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "add", "replace", "remove" ], "description": "The action to perform." }, "target": { "type": "string", "enum": [ "memory", "user" ], "description": "Which memory store: 'memory' for personal notes, 'user' for user profile." }, "content": { "type": "string", "description": "The entry content. Required for 'add' and 'replace'." }, "old_text": { "type": "string", "description": "Short unique substring identifying the entry to replace or remove." } }, "required": [ "action", "target" ] } } }, { "type": "function", "function": { "name": "mixture_of_agents", "description": "Route a hard problem through multiple frontier LLMs collaboratively. Makes 5 API calls (4 reference models + 1 aggregator) with maximum reasoning effort — use sparingly for genuinely difficult problems. Best for: complex math, advanced algorithms, multi-step analytical reasoning, problems benefiting from diverse perspectives.", "parameters": { "type": "object", "properties": { "user_prompt": { "type": "string", "description": "The complex query or problem to solve using multiple AI models. Should be a challenging problem that benefits from diverse perspectives and collaborative reasoning." } }, "required": [ "user_prompt" ] } } }, { "type": "function", "function": { "name": "patch", "description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nREPLACE MODE (mode='replace', default): find a unique string and replace it. REQUIRED PARAMETERS: mode, path, old_string, new_string.\nPATCH MODE (mode='patch'): apply V4A multi-file patches for bulk changes. REQUIRED PARAMETERS: mode, patch.", "parameters": { "type": "object", "properties": { "mode": { "type": "string", "enum": [ "replace", "patch" ], "description": "Edit mode. 'replace' (default): requires path + old_string + new_string. 'patch': requires patch content only.", "default": "replace" }, "path": { "type": "string", "description": "REQUIRED when mode='replace'. File path to edit." }, "old_string": { "type": "string", "description": "REQUIRED when mode='replace'. Exact text to find and replace. Must be unique in the file unless replace_all=true. Include surrounding context lines to ensure uniqueness." }, "new_string": { "type": "string", "description": "REQUIRED when mode='replace'. Replacement text. Pass empty string '' to delete the matched text." }, "replace_all": { "type": "boolean", "description": "Replace all occurrences instead of requiring a unique match (default: false)", "default": false }, "patch": { "type": "string", "description": "REQUIRED when mode='patch'. V4A format patch content. Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch" } }, "required": [ "mode" ] } } }, { "type": "function", "function": { "name": "process", "description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "list", "poll", "log", "wait", "kill", "write", "submit", "close" ], "description": "Action to perform on background processes" }, "session_id": { "type": "string", "description": "Process session ID (from terminal background output). Required for all actions except 'list'." }, "data": { "type": "string", "description": "Text to send to process stdin (for 'write' and 'submit' actions)" }, "timeout": { "type": "integer", "description": "Max seconds to block for 'wait' action. Returns partial output on timeout.", "minimum": 1 }, "offset": { "type": "integer", "description": "Line offset for 'log' action (default: last 200 lines)" }, "limit": { "type": "integer", "description": "Max lines to return for 'log' action", "minimum": 1 } }, "required": [ "action" ] } } }, { "type": "function", "function": { "name": "read_file", "description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.", "parameters": { "type": "object", "properties": { "path": { "type": "string", "description": "Path to the file to read (absolute, relative, or ~/path)" }, "offset": { "type": "integer", "description": "Line number to start reading from (1-indexed, default: 1)", "default": 1, "minimum": 1 }, "limit": { "type": "integer", "description": "Maximum number of lines to read (default: 500, max: 2000)", "default": 500, "maximum": 2000 } }, "required": [ "path" ] } } }, { "type": "function", "function": { "name": "search_files", "description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.", "parameters": { "type": "object", "properties": { "pattern": { "type": "string", "description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search" }, "target": { "type": "string", "enum": [ "content", "files" ], "description": "'content' searches inside file contents, 'files' searches for files by name", "default": "content" }, "path": { "type": "string", "description": "Directory or file to search in (default: current working directory)", "default": "." }, "file_glob": { "type": "string", "description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)" }, "limit": { "type": "integer", "description": "Maximum number of results to return (default: 50)", "default": 50 }, "offset": { "type": "integer", "description": "Skip first N results for pagination (default: 0)", "default": 0 }, "output_mode": { "type": "string", "enum": [ "content", "files_only", "count" ], "description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file", "default": "content" }, "context": { "type": "integer", "description": "Number of context lines before and after each match (grep mode only)", "default": 0 } }, "required": [ "pattern" ] } } }, { "type": "function", "function": { "name": "send_message", "description": "Send a message to a connected messaging platform, or list available targets.\n\nIMPORTANT: When the user asks to send to a specific channel or person (not just a bare platform name), call send_message(action='list') FIRST to see available targets, then send to the correct one.\nIf the user just says a platform name like 'send to telegram', send directly to the home channel without listing first.", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "send", "list" ], "description": "Action to perform. 'send' (default) sends a message. 'list' returns all available channels/contacts across connected platforms." }, "target": { "type": "string", "description": "Delivery target. Format: 'platform' (uses home channel), 'platform:#channel-name', 'platform:chat_id', or 'platform:chat_id:thread_id' for Telegram topics and Discord threads. Examples: 'telegram', 'telegram:-1001234567890:17585', 'discord:999888777:555444333', 'discord:#bot-home', 'slack:#engineering', 'signal:+155****4567', 'matrix:!roomid:server.org', 'matrix:@user:server.org', 'yuanbao:direct:' (DM), 'yuanbao:group:' (group chat)" }, "message": { "type": "string", "description": "The message text to send. To send an image or file, include MEDIA: (e.g. 'MEDIA:/tmp/hermes/cache/img_xxx.jpg') in the message — the platform will deliver it as a native media attachment." } } } } }, { "type": "function", "function": { "name": "session_search", "description": "Search your long-term memory of past conversations, or browse recent sessions. This is your recall -- every past session is searchable, and this tool summarizes what happened.\n\nTWO MODES:\n1. Recent sessions (no query): Call with no arguments to see what was worked on recently. Returns titles, previews, and timestamps. Zero LLM cost, instant. Start here when the user asks what were we working on or what did we do recently.\n2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.\n\nUSE THIS PROACTIVELY when:\n- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'\n- The user asks about a topic you worked on before but don't have in current context\n- The user references a project, person, or concept that seems familiar but isn't in memory\n- You want to check if you've solved a similar problem before\n- The user asks 'what did we do about X?' or 'how did we fix Y?'\n\nDon't hesitate to search when it is actually cross-session -- it's fast and cheap. Better to search and confirm than to guess or ask the user to repeat themselves.\n\nSearch syntax: keywords joined with OR for broad recall (elevenlabs OR baseten OR funding), phrases for exact match (\"docker networking\"), boolean (python NOT java), prefix (deploy*). IMPORTANT: Use OR between keywords for best results — FTS5 defaults to AND which misses sessions that only mention some terms. If a broad OR query returns nothing, try individual keyword searches in parallel. Returns summaries of the top matching sessions.", "parameters": { "type": "object", "properties": { "query": { "type": "string", "description": "Search query — keywords, phrases, or boolean expressions to find in past sessions. Omit this parameter entirely to browse recent sessions instead (returns titles, previews, timestamps with no LLM cost)." }, "role_filter": { "type": "string", "description": "Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs." }, "limit": { "type": "integer", "description": "Max sessions to summarize (default: 3, max: 5).", "default": 3 } } } } }, { "type": "function", "function": { "name": "skill_manage", "description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nOn delete, pass `absorbed_into=` when you're merging this skill's content into another one, or `absorbed_into=\"\"` when you're pruning it with no forwarding target. This lets the curator tell consolidation from pruning without guessing, so downstream consumers (cron jobs that reference the old skill name, etc.) get updated correctly. The target you name in `absorbed_into` must already exist — create/patch the umbrella first, then delete.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.\n\nPinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin `. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "create", "patch", "edit", "delete", "write_file", "remove_file" ], "description": "The action to perform." }, "name": { "type": "string", "description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file." }, "content": { "type": "string", "description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text." }, "old_string": { "type": "string", "description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness." }, "new_string": { "type": "string", "description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text." }, "replace_all": { "type": "boolean", "description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)." }, "category": { "type": "string", "description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'." }, "file_path": { "type": "string", "description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted." }, "file_content": { "type": "string", "description": "Content for the file. Required for 'write_file'." }, "absorbed_into": { "type": "string", "description": "For 'delete' only — declares intent so the curator can tell consolidation from pruning without guessing. Pass the umbrella skill name when this skill's content was merged into another (the target must already exist). Pass an empty string when the skill is truly stale and being pruned with no forwarding target. Omitting the arg on delete is supported for backward compatibility but downstream tooling (e.g. cron-job skill reference rewriting) will have to guess at intent." } }, "required": [ "action", "name" ] } } }, { "type": "function", "function": { "name": "skill_view", "description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.", "parameters": { "type": "object", "properties": { "name": { "type": "string", "description": "The skill name (use skills_list to see available skills). For plugin-provided skills, use the qualified form 'plugin:skill' (e.g. 'superpowers:writing-plans')." }, "file_path": { "type": "string", "description": "OPTIONAL: Path to a linked file within the skill (e.g., 'references/api.md', 'templates/config.yaml', 'scripts/validate.py'). Omit to get the main SKILL.md content." } }, "required": [ "name" ] } } }, { "type": "function", "function": { "name": "skills_list", "description": "List available skills (name + description). Use skill_view(name) to load full content.", "parameters": { "type": "object", "properties": { "category": { "type": "string", "description": "Optional category filter to narrow results" } } } } }, { "type": "function", "function": { "name": "terminal", "description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n", "parameters": { "type": "object", "properties": { "command": { "type": "string", "description": "The command to execute on the VM" }, "background": { "type": "boolean", "description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.", "default": false }, "timeout": { "type": "integer", "description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.", "minimum": 1 }, "workdir": { "type": "string", "description": "Working directory for this command (absolute path). Defaults to the session working directory." }, "pty": { "type": "boolean", "description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.", "default": false }, "notify_on_complete": { "type": "boolean", "description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.", "default": false }, "watch_patterns": { "type": "array", "items": { "type": "string" }, "description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both." } }, "required": [ "command" ] } } }, { "type": "function", "function": { "name": "text_to_speech", "description": "Convert text to speech audio. Returns a MEDIA: path that the platform delivers as native audio. Compatible providers render as a voice bubble on Telegram; otherwise audio is sent as a regular attachment. In CLI mode, saves to ~/voice-memos/. Voice and provider are user-configured (built-in providers like edge/openai or custom command providers under tts.providers.), not model-selected.", "parameters": { "type": "object", "properties": { "text": { "type": "string", "description": "The text to convert to speech. Provider-specific character caps apply and are enforced automatically (OpenAI 4096, xAI 15000, MiniMax 10000, ElevenLabs 5k-40k depending on model); over-long input is truncated." }, "output_path": { "type": "string", "description": "Optional custom file path to save the audio. Defaults to ~/.hermes/audio_cache/.mp3" } }, "required": [ "text" ] } } }, { "type": "function", "function": { "name": "todo", "description": "Manage your task list for the current session. Use for complex tasks with 3+ steps or when the user provides multiple tasks. Call with no parameters to read the current list.\n\nWriting:\n- Provide 'todos' array to create/update items\n- merge=false (default): replace the entire list with a fresh plan\n- merge=true: update existing items by id, add any new ones\n\nEach item: {id: string, content: string, status: pending|in_progress|completed|cancelled}\nList order is priority. Only ONE item in_progress at a time.\nMark items completed immediately when done. If something fails, cancel it and add a revised item.\n\nAlways returns the full current list.", "parameters": { "type": "object", "properties": { "todos": { "type": "array", "description": "Task items to write. Omit to read current list.", "items": { "type": "object", "properties": { "id": { "type": "string", "description": "Unique item identifier" }, "content": { "type": "string", "description": "Task description" }, "status": { "type": "string", "enum": [ "pending", "in_progress", "completed", "cancelled" ], "description": "Current status" } }, "required": [ "id", "content", "status" ] } }, "merge": { "type": "boolean", "description": "true: update existing items by id, add new ones. false (default): replace the entire list.", "default": false } } } } }, { "type": "function", "function": { "name": "video_analyze", "description": "Analyze a video from a URL or local file path using a multimodal AI model. Sends the video to a video-capable model (e.g. Gemini) for understanding. Use this for video files — for images, use vision_analyze instead. Supports mp4, webm, mov, avi, mkv, mpeg formats. Note: large videos (>20 MB) may be slow; max ~50 MB.", "parameters": { "type": "object", "properties": { "video_url": { "type": "string", "description": "Video URL (http/https) or local file path to analyze." }, "question": { "type": "string", "description": "Your specific question about the video. The AI will describe what happens in the video and answer your question." } }, "required": [ "video_url", "question" ] } } }, { "type": "function", "function": { "name": "vision_analyze", "description": "Load an image into the conversation so you can see it. Accepts a URL, local file path, or data URL. When your active model has native vision, the image is attached to your context directly and you read the pixels yourself on the next turn — call this any time the user references an image (filepath in their message, URL in tool output, screenshot from the browser, etc.). For non-vision models, falls back to an auxiliary vision model that returns a text description.", "parameters": { "type": "object", "properties": { "image_url": { "type": "string", "description": "Image URL (http/https), local file path, or data: URL to load." }, "question": { "type": "string", "description": "Your specific question or request about the image. Optional context the model uses on the next turn after seeing the image." } }, "required": [ "image_url", "question" ] } } }, { "type": "function", "function": { "name": "write_file", "description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits. Auto-runs syntax checks on .py/.json/.yaml/.toml and other linted languages; only NEW errors introduced by this write are surfaced (pre-existing errors are filtered out).", "parameters": { "type": "object", "properties": { "path": { "type": "string", "description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)" }, "content": { "type": "string", "description": "Complete content to write to the file" } }, "required": [ "path", "content" ] } } } ], "message_count": 334, "messages": [ { "role": "user", "content": "[M G] Ok, nächster schritt\n\n[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\nSummary generation was unavailable. 125 message(s) were removed to free context space but could not be summarized. The removed messages contained earlier work in this session. Continue based on the recent messages below and the current state of any files or resources.\n\n--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---" }, { "role": "assistant", "content": "Erledigt, Sir.\n\n## Renderer v1 gebaut\n\nIch habe jetzt den ersten **manifest-driven Preview Renderer** implementiert.\n\nKurz gesagt:\n\n```text\nRender Manifest JSON\n→ Pillow erzeugt vertikale Szenen-Frames\n→ FFmpeg baut daraus MP4\n```\n\nAlso: **kein LLM rendert das Video**, sondern ein deterministischer Renderer. Das LLM/Manifest gibt nur vor, *was wann passieren soll*. Der Renderer setzt es technisch um.\n\n## Neu implementiert\n\nCode:\n\n```text\nautoshorts/preview_renderer.py\n```\n\nCLI:\n\n```text\nscripts/render_preview.py\n```\n\nTests:\n\n```text\ntests/test_preview_renderer.py\n```\n\nDependency ergänzt:\n\n```text\nPillow>=10.0\n```\n\n## Erstes Testvideo gerendert\n\nFür:\n\n```text\nai-004 — Stop asking AI to think for you\n```\n\nOutput:\n\n```text\ndata/previews/testbatch_002_top3/ai-004-stop-asking-ai-to-think-for-you.mp4\n```\n\nTechnische Prüfung:\n\n```text\nwidth=540\nheight=960\navg_frame_rate=24/1\nduration=43.041667\n```\n\nPreview-Video:\n\nMEDIA:/home/agent/jarvis_runtime/AutoShortsBot/data/previews/testbatch_002_top3/ai-004-stop-asking-ai-to-think-for-you.mp4\n\n## Was der Renderer v1 aktuell macht\n\n- nimmt das Render Manifest\n- baut 5 visuelle Szenen\n- nutzt pro Szene:\n - Asset Type\n - On-screen Text\n - Timing\n - Retention Goal\n- erzeugt vertikale Preview-Cards\n- exportiert daraus ein MP4 via FFmpeg\n\nDas ist bewusst noch **Preview/Timing-Renderer**, nicht finaler Beauty-Renderer. Er zeigt uns: Struktur, Timing, Szenenfluss, Textgewicht. Erst danach lohnt sich Politur.\n\n## Tests / Git\n\nFull suite:\n\n```text\n24 passed in 0.88s\n```\n\nNeuer Commit:\n\n```text\n07bbc57 feat: add manifest preview renderer\n```\n\nBranch:\n\n```text\nfeat/initial-growth-engine\n```\n\nRemote verifiziert:\n\n```text\nlocal == remote\n```\n\nPR-Link bleibt:\n\nhttps://github.com/Gamexgit/AutoShortsBot/pull/new/feat/initial-growth-engine\n\n## Nächster sinnvoller Schritt\n\nJetzt würde ich als Nächstes den Renderer von „Card Preview“ zu **echter Video-Struktur v2** bringen:\n\n- Hook text animation verbessern\n- echte Caption-Overlays über alle Beats\n- simple motion/pan/zoom\n- optional TTS-Audio-Spur\n- danach wieder ein neues MP4 zur Freigabe\n\nAktuell ist es der erste brauchbare Rohschnitt. Nicht hübsch. Aber kontrolliert. Und Kontrolle schlägt KI-Konfetti." }, { "role": "user", "content": "[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\n## Active Task\nUser asked: \"ok nächster schritt\"\n\n## Goal\nDer User möchte AutoShortsBot/Hermes von einer einfachen KI-Video-/Card-Rendering-Pipeline zu einem halbautomatischen **Retention-Studio für Shorts** weiterentwickeln. Ziel ist ein System, das datenbasierte, animierte Mechanismus-Erklärvideos produziert: starke Hooks in den ersten 1–2 Sekunden, visuelle Veränderung alle 1–2 Sekunden, keine statischen Slideshow-Videos, sondern „mechanism reveal / visual explanation / mini-investigation“-Content mit Fokus auf Hidden Money, AI Systems, Auto-/Finanzmechaniken und unsichtbare Systemeffekte.\n\n## Constraints & Preferences\n- Sprache/Kommunikation: Deutsch; User wird teilweise mit „Sir“ angesprochen.\n- Der User lehnt finale statische Textkarten-/KI-Bild-Slideshows ab; sie sind nur Preview/Storyboard, nicht Endprodukt.\n- Finale Videos sollen bewegte Sequenzen, AI-video Assets, Screen-Recording-Simulationen, Mechanismus-Animationen, kinetic captions, Sound/SFX und schnelle visuelle Wechsel enthalten.\n- Der aktuelle Card-/Preview-Renderer ist nur Timing-/Storyboard-Werkzeug.\n- `static_card_limit = 0` als Qualitätsprinzip für finale Inhalte.\n- Content-Richtung: kein generischer KI-Avatar-News-Kanal, kein „Was wäre wenn…“-KI-Müll, kein Reused-Content-Klon.\n- Avatare höchstens als Nebenfigur/Branding-Element, nicht als Hauptformat.\n- Bevorzugte Nische: **Hidden Money & AI Systems**.\n- Zielserie: **Unsichtbare Systeme in 30 Sekunden**.\n- Claim: „Wir zeigen Dinge, die dich Geld, Zeit oder Kontrolle kosten – bevor du sie bemerkst.“\n- Erfolgsmechanik: Hook → Objekt/Problem → Schnitt ins Innere → Gefahr/Überraschung → Auflösung.\n- Inspirationsmechaniken: Zack-D-Films-artige Mechanism Reveals, MrBeast/Jenny-Hoyos sofortiges Versprechen, TikTok Creative Code: Hook/Body/Close, dynamisches Editing, Bewegung, Text-Overlays, Sound/Voice/SFX.\n- User erlaubt, die untracked Telegram-Review-Dateien zu ignorieren, weil sie versehentlich durch einen falschen Telegram-Kanal entstanden sind.\n- Keine API-Keys, Tokens, Passwörter, Secrets, Credentials oder Connection Strings in Zusammenfassungen oder Artefakten bewahren; ggf. mit `[REDACTED]` ersetzen.\n\n## Completed Actions\n1. ANALYSED Preview-Renderer Typography Issue — festgestellt, dass Textgrößen im Preview uneinheitlich wirkten: Haupttext groß, Retention-/Erklärungstext unten deutlich kleiner; erklärt, dass diese Zwei-Ebenen-Logik technisch beabsichtigt, aber für Shorts visuell schwach ist [tool: conversation].\n2. UPDATED Preview-Renderer-Konzept — Renderer um adaptive Font-Fitting, konsistentere Text-Hierarchie, Mindestgrößen, maximale Zeilenanzahl und Typography-Metadaten erweitert; Ziel war weniger zu kleine/zu stark schwankende Textgrößen im Storyboard-Preview [tool: code/terminal claimed].\n3. ADDED Typography Test Rules für `540x960` Preview — Regeln dokumentiert/geprüft: `main_font_size >= 34`, `max(main_font_size) - min(main_font_size) <= 8`, `retention_font_size >= 22`, `main_line_count <= 4`, `retention_line_count <= 3` [tool: tests claimed].\n4. RENDERED Top-3 Previews neu — erzeugt unter `data/previews/testbatch_002_top3/`: `ai-004-stop-asking-ai-to-think-for-you.mp4`, `ai-005-the-4-box-prompt-for-mental-overload.mp4`, `attention-002-the-algorithm-does-not-need-you-happy.mp4` [tool: terminal claimed].\n5. VERIFIED Preview `ai-004` — technische Werte: `width=540`, `height=960`, `avg_frame_rate=24/1`, `duration=43.041667`; Typography: `main_font_size: 34–42`, `retention_font_size: 25–26` [tool: ffprobe/tests claimed].\n6. TEST full suite nach Typography-Änderung — Ergebnis: `25 passed in 0.96s` [tool: pytest claimed].\n7. COMMITTED Typography-Fix — Commit `3cc201b fix: improve preview renderer text sizing` auf Branch `feat/initial-growth-engine`; Remote als `local == remote` verifiziert [tool: git claimed].\n8. ANSWERED User-Frage zum Endergebnis — klargestellt: aktueller Preview-Renderer ist nicht finales Content-Format; Endprodukt soll Videosequenzen, Bewegung, AI-video Assets, Screen-Recordings, kinetic captions, Voiceover und Sounddesign nutzen, nicht statische Cards [tool: conversation].\n9. DEFINED bessere Zielrichtung für `ai-004` — vorgeschlagen: ca. 40% Screen Recording/UI Simulation, 30% cinematic human-at-desk/decision moments, 20% kinetic captions, 10% Cards nur für Prompt-Fragmente [tool: conversation].\n10. CREATED `autoshorts/asset_plan.py` — neue Asset-Plan-v2-Komponente für motion-led Asset Pipeline; entscheidet pro Szene zwischen `cinematic_ai_video`, `screen_recording_simulation`, `animated_card`, `kinetic_text_overlay` [tool: code claimed].\n11. CREATED `scripts/generate_asset_plans.py` — CLI zum Generieren von Asset-Plänen aus vorhandenen Render-/Storyboard-Daten [tool: code claimed].\n12. CREATED `tests/test_asset_plan.py` — Tests für Asset Plan Builder, u.a. Provider-Prompting und keine finalen statischen Cards [tool: code claimed].\n13. GENERATED Asset-Pläne Top-3 — Dateien erzeugt unter `data/asset_plans/testbatch_002_top3/`: `ai-004-stop-asking-ai-to-think-for-you.json`, `ai-005-the-4-box-prompt-for-mental-overload.json`, `attention-002-the-algorithm-does-not-need-you-happy.json` [tool: terminal claimed].\n14. SET Asset Pipeline `static_card_limit = 0` — finale statische Textkarten explizit ausgeschlossen; Preview bleibt Storyboard/Timing-Werkzeug [tool: code claimed].\n15. BUILT Provider-ready Prompting für cinematic Szenen — Prompt-Felder mit photorealistischer vertikaler 9:16-Clip-Beschreibung, cinematic lighting, realistic motion, negative space for captions und „do not include readable text“ ergänzt [tool: code claimed].\n16. BUILT Negative Prompts für AI-video Provider — u.a. `no readable text`, `no subtitles`, `no logos`, `no watermarks`, `no fake UI text`, `no slideshow`, `no static image`, `no uncanny faces` [tool: code claimed].\n17. TEST full suite nach Asset Plan v2 — Ergebnis: `32 passed in 0.96s` [tool: pytest claimed].\n18. COMMITTED Motion-led Asset Planning — Commit `b60981b feat: add motion-led asset planning` auf Branch `feat/initial-growth-engine`; Remote als `local == remote` verifiziert [tool: git claimed].\n19. IDENTIFIED untracked Telegram Review Package — nicht angefasst: `autoshorts/review_package.py`, `data/telegram_reviews/`, `scripts/generate_telegram_review_packages.py`, `tests/test_review_package.py` [tool: git status claimed].\n20. CREATED `autoshorts/retention_studio.py` — neue Strategiekomponente, die AutoShortsBot konzeptionell als `semi_automatic_retention_studio` statt KI-Video-Fabrik verankert [tool: code claimed].\n21. CREATED `scripts/generate_retention_studio.py` — CLI zum Generieren von Retention-Studio-Strategieartefakten [tool: code claimed].\n22. CREATED `tests/test_retention_studio.py` — Tests für Strategie, Dramaturgie, visuelle Bewegung, Sound Cues und Follow Trigger [tool: code claimed].\n23. GENERATED Retention-Studio-Artefakte — erzeugt unter `data/retention_studio/`: `strategy.json`, `pilot_ideas.json`, `mechanism_explainers.json` [tool: terminal claimed].\n24. SET Positionierung in Strategie — `Hidden Money & AI Systems`; Serie `Unsichtbare Systeme in 30 Sekunden`; Claim „Wir zeigen Dinge, die dich Geld, Zeit oder Kontrolle kosten – bevor du sie bemerkst.“ [tool: code claimed].\n25. EXCLUDED unerwünschte Content-Formate in Strategie — `ki_avatar_news`, `static_ai_slideshow`, `reused_content_clone`; Quality Gate `static_card_limit = 0` [tool: code claimed].\n26. IMPLEMENTED Mechanism-Explainer-Formel — Timing/Beats: `0.0–1.5s Pattern Interrupt`, `1.5–5s Problem`, `5–18s Mechanism Reveal`, `18–28s Twist`, `28–35s Follow Trigger` [tool: code claimed].\n27. ADDED Tests für Retention-Beats — Pattern Interrupt endet ≤ 1.5 Sekunden; jeder Beat braucht visuelle Bewegung und Sound Cue; kein generisches „Follow for more“; Follow Trigger als Serienversprechen [tool: pytest claimed].\n28. ADDED Format-Taxonomie — `mechanism_reveal`, `mistake_breakdown`, `hidden_cost`, `before_after`, `myth_vs_reality`, `mini_simulation`, `nobody_notices_this` [tool: code claimed].\n29. ADDED Content-Pillars — `hidden_money_systems`, `auto_trade_mechanics`, `ai_agents_explained`, `swiss_systems_explained`, `dangerous_thinking_errors`, plus `hidden_attention_systems` [tool: code claimed].\n30. GENERATED 10 Pilot-Ideen mit Scores — Top 3: Score 90 `hidden_attention_systems`/„Warum Shorts dich nicht wegen dem Inhalt halten“, Score 88 `hidden_money_systems`/„Warum ein billiges Auto teuer sein kann“, Score 86 `hidden_money_systems`/„Warum 0%-Finanzierung nicht kostenlos ist“ [tool: terminal claimed].\n31. SET Produktionsentscheidung — Empfehlung `produce_count = 5 von 10` Pilot-Ideen [tool: code claimed].\n32. BUILT Beispiel-Mechanism-Explainer für „Warum ein billiges Auto teuer sein kann“ — Beat-Struktur mit Occasion-Käufer, 3D-Car-X-Ray, Preis/Reparaturrisiko/Standtage/Händler-Marge/Liquidität, Twist „teuerster Fehler ist nicht Kaufpreis, sondern Zeitpunkt“ [tool: code claimed].\n33. TEST full suite nach Retention Studio — Ergebnis: `36 passed in 0.99s` [tool: pytest claimed].\n34. COMMITTED Retention-Studio-Strategie — Commit `a9fe897 feat: add retention studio strategy` auf Branch `feat/initial-growth-engine`; Remote als `local == remote` verifiziert [tool: git claimed].\n35. UPDATED Skill-Notiz — Social-Shorts-/Retention-Studio-Skill um Retention Studio Strategy, Mechanism Explainer Shorts, Hidden Money & AI Systems und `static_card_limit = 0` erweitert [tool: file edit claimed].\n36. CREATED `autoshorts/mechanism_pipeline.py` — Adapter von Retention-Studio Mechanism Explainer zu renderer-nahem Mechanism Shot Plan [tool: code claimed].\n37. CREATED `scripts/generate_mechanism_shot_plans.py` — CLI zum Generieren von Mechanism Shot Plans aus Mechanism Explainern [tool: code claimed].\n38. CREATED `tests/test_mechanism_pipeline.py` — Tests für Adapter/Shot-Plan-Erzeugung, Timing, Asset Types, Bewegungs-/Sound-Metadaten und `static_card_limit = 0` [tool: code claimed].\n39. GENERATED Pilot-Shot-Plan — Datei `data/mechanism_shot_plans/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.md` erzeugt [tool: terminal claimed].\n40. MAPPED Mechanism Beats zu Scenes — `pattern_interrupt`, `problem`, `mechanism`, `twist`, `follow_trigger` wurden in Szenen mit Timing, Asset Type, On-screen Text, Voiceover, Visual Direction, Visual Motion, Sound Cue, Retention Goal, Caption Beats und Final Render Intent übersetzt [tool: code claimed].\n41. CREATED Shot Plan für „Warum ein billiges Auto teuer sein kann“ — Scene 1 `0.0s–1.4s cinematic_ai_video`, Scene 2 `1.4s–5.0s cinematic_ai_video`, Scene 3 `5.0s–18.0s mechanism_animation`, Scene 4 `18.0s–28.0s mechanism_animation`, Scene 5 `28.0s–34.0s kinetic_text_overlay` [tool: terminal claimed].\n42. SET Shot-Plan-Constraints — `static_card_limit = 0`, `visual_change_every_seconds = 2`, `primary_style = mechanism_reveal_motion_explainer` [tool: code claimed].\n43. TEST full suite nach Mechanism Pipeline — Ergebnis: `40 passed in 0.97s` [tool: pytest claimed].\n44. COMMITTED Mechanism Explainer Adapter — Commit `5644c8b feat: adapt mechanism explainers to shot plans` auf Branch `feat/initial-growth-engine`; Remote als `local == remote` verifiziert [tool: git claimed].\n45. UPDATED Retention-Studio-Skill-Notiz — Pipeline festgehalten: `strategy → scored ideas → mechanism explainer → mechanism shot plan → render manifest → asset plan → final renderer` [tool: file edit claimed].\n46. CONFIRMED Telegram Review Files ignored — User erklärte, dass die separaten Working-Tree-Dateien versehentlich durch falschen Telegram-Kanal entstanden sind; sie bleiben unberührt und uncommitted [tool: conversation].\n\n## Active State\n- Repository/Projekt: `/home/agent/jarvis_runtime/AutoShortsBot`.\n- Branch: `feat/initial-growth-engine`.\n- Remote-Status zuletzt berichtet: `local == remote`.\n- Letzter bekannter Commit: `5644c8b feat: adapt mechanism explainers to shot plans`.\n- Vorherige relevante Commits:\n - `3cc201b fix: improve preview renderer text sizing`\n - `b60981b feat: add motion-led asset planning`\n - `a9fe897 feat: add retention studio strategy`\n- Letzter Teststatus: `40 passed in 0.97s`.\n- Aktuelles Pipeline-Level erreicht:\n - Retention Studio Strategie vorhanden.\n - Pilot-Ideen gescored.\n - Mechanism Explainer vorhanden.\n - Mechanism Shot Plan für Pilot „Warum ein billiges Auto teuer sein kann“ vorhanden.\n- Nächster logischer Schritt noch nicht erledigt:\n - `Mechanism Shot Plan → Render Manifest → Asset Plan` für den neuen Pilot, nicht mehr nur für alte AI-Life-Top-3.\n- Untracked/zu ignorieren:\n - `autoshorts/review_package.py`\n - `data/telegram_reviews/`\n - `scripts/generate_telegram_review_packages.py`\n - `tests/test_review_package.py`\n- Keine laufenden Server oder Prozesse erwähnt.\n- Keine Secrets/Credentials bewahren; falls vorhanden, als `[REDACTED]`.\n\n## In Progress\n- Der User hat „ok nächster schritt“ gesagt. Gemeinter nächster Arbeitsschritt laut vorheriger Antwort:\n - Mechanism Shot Plan für „Warum ein billiges Auto teuer sein kann“\n - → Render Manifest\n - → Asset Plan\n - Ziel: neue Retention-Studio-/Mechanism-Explainer-Pipeline an die bestehende Render-/Asset-Plan-Infrastruktur anbinden.\n- Noch nicht umgesetzt:\n - Adapter/CLI/Tests für `Mechanism Shot Plan → Render Manifest`.\n - Generierung eines Render Manifests für `hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann`.\n - Asset Plan für diesen neuen Pilot auf Basis des neuen Render Manifests.\n - Provider Job Specs für cinematic Szenen des Pilots.\n\n## Blocked\nKeine bekannten Blocker. \nKeine Fehlermeldungen offen. \nEinziger Hinweis: frühere 125 Messages konnten nicht zusammengefasst werden; daraus können ältere Details fehlen. Die aktuelle Richtung und letzten Artefakte sind aber in den neuen Turns beschrieben.\n\n## Key Decisions\n1. Der Preview-Renderer ist nicht das finale Produkt, sondern nur Storyboard-/Timing-Werkzeug. Grund: Statische Cards wirken langweilig und konkurrieren nicht mit modernen Shorts/Kling/Hailuo/Runway-Qualität.\n2. Finale Videos müssen motion-led sein: AI-video Clips, Screen-Recording-Simulationen, mechanism animations, kinetic captions, Voiceover, SFX und schnelle Schnitte.\n3. `static_card_limit = 0` ist ein strategisches Qualitätsgate für finale Videos. Grund: User lehnt statische KI-Bilder + Text/Voiceover als KI-Müll-Massenware ab.\n4. AutoShortsBot/Hermes wird als halbautomatisches Retention-Studio positioniert, nicht als KI-Video-Fabrik. Grund: Erfolg hängt von Hook, offenen Loops, visueller Stimulation und Payoff ab, nicht vom KI-Look.\n5. Gewählte Content-Nische: Hidden Money & AI Systems. Grund: verbindet Hermes, Autotrading, Finanzen, KI-Agenten, Politik/Systemverständnis und hat spätere Monetarisierungsmöglichkeiten über Newsletter, Tools, Beratung, Affiliate, Software oder Kurse.\n6. Kernformat: Mechanism Reveal / Visual Explanation / Mini-Investigation. Grund: zeigt unsichtbare Mechanismen visuell und bietet echten Erkenntniswert statt generischem Voiceover.\n7. Avatare nicht als Hauptformat. Grund: viele KI-Avatare wirken generisch, halten Retention schlecht, und es gibt Disclosure-/Trust-Risiken bei realistischen synthetischen Menschen.\n8. Re-Kuratierung erfolgreicher Videos ist strategisch erlaubt, aber nicht als Kopie/Neuvertontung. Grund: YouTube Reused Content vermeiden; Mechaniken adaptieren, nicht Inhalte klonen.\n9. Pilot-Fokus: „Warum ein billiges Auto teuer sein kann“. Grund: passt zu Money/Auto, klares visuelles Objekt, starke 3D-/X-Ray-/Layer-Animation möglich, hohe Monetarisierbarkeit.\n10. Untracked Telegram-Review-Dateien werden ignoriert. Grund: User schrieb versehentlich in falschen Telegram-Kanal; Änderungen sollen nicht mit dieser Pipeline vermischt werden.\n\n## Resolved Questions\n1. User fragte, warum Text oben groß und unten klein ist. Antwort: Der Preview-Renderer nutzt Haupttext plus kleineren Retention-/Erklärungstext; technisch beabsichtigt, aber visuell für Shorts ungeeignet. Finale Videos sollen weniger Text pro Frame und große rhythmische Captions nutzen.\n2. User fragte, ob Endergebnis Videosequenzen oder wieder statische Bilder sein sollen. Antwort: Nicht statische Bilder. Endziel sind Videosequenzen mit AI-video Assets, Screen Recordings, kinetic captions, Voiceover, Musik/SFX und fast cuts.\n3. User fragte, warum diese Videos besser sein sollen als bisheriger Content. Antwort: Nur wenn Scripting, visuelle Umsetzung und Retention-Struktur besser werden: starke Hooks, motion-led visuals, alle 1–2 Sekunden visueller Reiz, echter Mechanismus-Payoff.\n4. User fragte implizit, ob statische Cards reichen. Antwort: Nein, statische Cards sind nur Preview/Storyboard und als finales Format strategisch zu schwach.\n5. User brachte „Chloe vs History“, Kling, Hailuo, photorealistische KI-Videos als Qualitätsreferenz ein. Antwort: Diese Richtung wurde aufgenommen; finale Pipeline soll provider-ready prompts für cinematic AI-video Szenen erzeugen, aber nicht in generischem KI-Look enden.\n6. User schlug Retention-Studio statt KI-Video-Content vor. Antwort: Konzept wurde als `semi_automatic_retention_studio` umgesetzt und in Strategieartefakten verankert.\n7. User schlug Zack-D-Films-artige Mechanism Reveals vor. Antwort: Mechanism-Explainer-Formel, Beat-Struktur und Pilot „Warum ein billiges Auto teuer sein kann“ wurden umgesetzt.\n8. User erklärte, der separate Working Tree könne ignoriert werden. Antwort: Telegram-Review-Dateien wurden nicht angefasst und nicht committet.\n\n## Pending User Asks\n- „ok nächster schritt“ ist noch offen. Gemeint ist nach aktuellem Stand der nächste Build-Schritt:\n - Mechanism Shot Plan → Render Manifest → Asset Plan für den Pilot „Warum ein billiges Auto teuer sein kann“.\n\n## Relevant Files\n- `autoshorts/asset_plan.py` — Asset-Plan-v2-Komponente für motion-led finale Asset-Auswahl pro Szene.\n- `scripts/generate_asset_plans.py` — CLI zur Asset-Plan-Generierung.\n- `tests/test_asset_plan.py` — Tests für Asset-Plan-Logik.\n- `data/asset_plans/testbatch_002_top3/ai-004-stop-asking-ai-to-think-for-you.json` — Asset Plan für alten AI-Life-Top-3-Preview.\n- `data/asset_plans/testbatch_002_top3/ai-005-the-4-box-prompt-for-mental-overload.json` — Asset Plan für alten AI-Life-Top-3-Preview.\n- `data/asset_plans/testbatch_002_top3/attention-002-the-algorithm-does-not-need-you-happy.json` — Asset Plan für alten AI-Life-Top-3-Preview.\n- `autoshorts/retention_studio.py` — Strategie-/Pilot-/Mechanism-Explainer-Komponente für Retention Studio.\n- `scripts/generate_retention_studio.py` — CLI zur Generierung von Retention-Studio-Artefakten.\n- `tests/test_retention_studio.py` — Tests für Strategie, Beats, visuelle Bewegung, Sound Cues, Follow Trigger.\n- `data/retention_studio/strategy.json` — Retention-Studio-Strategie.\n- `data/retention_studio/pilot_ideas.json` — gescorte Pilot-Ideen.\n- `data/retention_studio/mechanism_explainers.json` — Mechanism-Explainer-Daten.\n- `autoshorts/mechanism_pipeline.py` — Adapter von Mechanism Explainer zu Mechanism Shot Plan.\n- `scripts/generate_mechanism_shot_plans.py` — CLI zur Shot-Plan-Generierung.\n- `tests/test_mechanism_pipeline.py` — Tests für Mechanism Shot Plan Adapter.\n- `data/mechanism_shot_plans/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.md` — generierter Pilot-Shot-Plan.\n- `data/previews/testbatch_002_top3/ai-004-stop-asking-ai-to-think-for-you.mp4` — neu gerenderter Preview.\n- `data/previews/testbatch_002_top3/ai-005-the-4-box-prompt-for-mental-overload.mp4` — neu gerenderter Preview.\n- `data/previews/testbatch_002_top3/attention-002-the-algorithm-does-not-need-you-happy.mp4` — neu gerenderter Preview.\n- `autoshorts/review_package.py` — untracked/zu ignorieren.\n- `data/telegram_reviews/` — untracked/zu ignorieren.\n- `scripts/generate_telegram_review_packages.py` — untracked/zu ignorieren.\n- `tests/test_review_package.py` — untracked/zu ignorieren.\n\n## Remaining Work\n- Neuen Adapter bauen: `Mechanism Shot Plan → Render Manifest`.\n- Render Manifest für `hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann` erzeugen.\n- Asset Plan v2 auf diesen neuen Mechanism-Render-Manifest anwenden.\n- Provider Job Specs für cinematic AI-video Szenen exportieren, z.B. Kling/Hailuo/Runway-kompatible Prompts.\n- Mechanism Animation Specs definieren für 3D-Car-X-Ray, Preis-/Risiko-/Marge-/Timing-Layer.\n- Final Renderer erweitern, damit er echte Clip-Dateien, Screen-Recording-Simulationen, mechanism animations und kinetic captions zusammensetzt.\n- Optional: Preview-Storyboard weiter nutzen, aber klar als nicht-final markieren.\n- Später: Analysepipeline für Retention nach 1s/3s, durchschnittliche Wiedergabedauer, Replays, Kommentare pro 1’000 Views, Follows pro 1’000 Views.\n\n## Critical Context\n- Frühere Kontextzusammenfassung war nicht verfügbar: „Summary generation was unavailable. 125 message(s) were removed…“. Frühere Details vor den neuen Turns können fehlen.\n- Branch: `feat/initial-growth-engine`.\n- PR-Link bleibt: `https://github.com/Gamexgit/AutoShortsBot/pull/new/feat/initial-growth-engine`.\n- Letzter bekannter Teststatus: `40 passed in 0.97s`.\n- Wichtigster aktueller Pilot: `Warum ein billiges Auto teuer sein kann`.\n- Pilot-Shot-Plan-Szenen:\n - Scene 1 — `pattern_interrupt`, `0.0s–1.4s`, `cinematic_ai_video`, Visual: 3D car x-ray with price tag layers and risk meters freezes mid-action, Motion: hard zoom/freeze-frame/red signal pulse, Sound: bass hit + camera snap.\n - Scene 2 — `problem`, `1.4s–5.0s`, `cinematic_ai_video`, Visual: surface layer peels away to reveal hidden system, Motion: layer peel + parallax push.\n - Scene 3 — `mechanism_reveal`, `5.0s–18.0s`, `mechanism_animation`, Visual: 3D car x-ray with price tag layers and risk meters, Motion: sequential layer reveal every 1–2 seconds.\n - Scene 4 — `twist`, `18.0s–28.0s`, `mechanism_animation`, Visual: wrong cause fades out, real cause appears, Motion: snap zoom + wrong answer collapses.\n - Scene 5 — `follow_trigger`, `28.0s–34.0s`, `kinetic_text_overlay`, Visual: animated system map, Motion: map draws itself, final node glows.\n- Strategy constraints to preserve:\n - `static_card_limit = 0`\n - `visual_change_every_seconds = 2`\n - `primary_style = mechanism_reveal_motion_explainer`\n- Provider negative prompt concepts:\n - no readable text\n - no subtitles\n - no logos\n - no watermarks\n - no fake UI text\n - no slideshow\n - no static image\n - no uncanny faces\n- Do not include or preserve any credentials/secrets; replace with `[REDACTED]` if encountered.\n\n--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---" }, { "role": "assistant", "content": "Erledigt, Sir.\n\nDer nächste Schritt ist gebaut:\n\n```text\nMechanism Shot Plan\n→ Render Manifest\n→ Asset Plan\n```\n\nFür den neuen Pilot:\n\n```text\nWarum ein billiges Auto teuer sein kann\n```\n\n## Neu gebaut\n\nNeues CLI:\n\n```text\nscripts/generate_mechanism_render_manifests.py\n```\n\nErzeugte Artefakte:\n\n```text\ndata/render_manifests/mechanism_pilots/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\n\ndata/asset_plans/mechanism_pilots/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\n```\n\n## Manifest ist jetzt motion-aware\n\nIch habe `render_manifest.py` erweitert, damit Mechanism-Explainer nicht wieder zu statischen Cards degenerieren.\n\nDas Manifest speichert jetzt pro visueller Szene zusätzlich:\n\n```text\nvisual_motion\nsound_cue\n```\n\nBeispiel:\n\n```text\nScene 1:\ntype: cinematic_ai_video\nvisual_motion: hard zoom, freeze-frame, red signal pulse\nsound_cue: bass hit + camera snap\n\nScene 3:\ntype: mechanism_animation\nvisual_motion: sequential layer reveal every 1-2 seconds\nsound_cue: clicks per revealed layer\n```\n\nDas ist wichtig, weil diese Felder später die eigentliche Schnitt- und Motion-Logik steuern. Ohne sie hätten wir wieder hübsch strukturierte Langeweile. Die Fachwelt nennt das vermutlich „PowerPoint mit Ambitionen“.\n\n## Timing sauberer gemacht\n\nIch habe außerdem ein Timing-Problem behoben:\n\nVorher wurden Sekunden intern mit `int()` konvertiert. \nDas hätte aus:\n\n```text\n1.4s\n```\n\neffektiv:\n\n```text\n1.0s\n```\n\ngemacht.\n\nJetzt wird korrekt in Millisekunden umgerechnet:\n\n```text\n0.0s → 0ms\n1.4s → 1400ms\n5.0s → 5000ms\n18.0s → 18000ms\n28.0s → 28000ms\n```\n\n## Pilot-Manifest\n\nFür „Warum ein billiges Auto teuer sein kann“:\n\n```text\nduration_ms: 34000\nvisual_types:\n - cinematic_ai_video\n - cinematic_ai_video\n - mechanism_animation\n - mechanism_animation\n - kinetic_text_overlay\n```\n\nRender Constraints:\n\n```text\navoid_static_slideshow: true\nvisual_change_every_seconds: 2\nmax_static_cards: 0\nfirst_frame_hook_required: true\nhuman_approval_required_before_publish: true\n```\n\n## Asset Plan\n\nDer passende Asset Plan erzeugt jetzt:\n\n```text\nasset_modes:\n - cinematic_ai_video\n - cinematic_ai_video\n - mechanism_animation\n - mechanism_animation\n - kinetic_text_overlay\n```\n\nPreferred Mix:\n\n```text\ncinematic_ai_video: 2\nmechanism_animation: 2\nkinetic_text_overlay: 1\nstatic cards: 0\n```\n\nAlso genau die neue Richtung:\n\n```text\nphotorealistische Szenen\n+ Mechanismus-/Röntgen-Animation\n+ kinetic captions\n```\n\nNicht:\n\n```text\nstatische KI-Bilder mit Text\n```\n\n## Tests / Git\n\nTDD durchgeführt:\n\n- RED: Manifest verlor `visual_motion` / `sound_cue`\n- GREEN: Manifest + Asset Plan erweitert\n\nFull suite:\n\n```text\n42 passed in 0.99s\n```\n\nNeuer Commit:\n\n```text\n4d1e8f8 feat: generate mechanism render manifests\n```\n\nBranch:\n\n```text\nfeat/initial-growth-engine\n```\n\nRemote verifiziert:\n\n```text\nlocal == remote\n```\n\nPR-Link bleibt:\n\nhttps://github.com/Gamexgit/AutoShortsBot/pull/new/feat/initial-growth-engine\n\n## Skill aktualisiert\n\nDie Retention-Studio-Skill-Notiz wurde ergänzt:\n\n```text\nvisual_motion und sound_cue sind nicht dekorativ,\nsondern der Retention-/Editing-Contract für den finalen Renderer.\n```\n\n## Weiterhin ignoriert\n\nDie versehentlichen Review-Dateien bleiben uncommitted und unberührt:\n\n```text\nautoshorts/review_package.py\ndata/telegram_reviews/\nscripts/generate_telegram_review_packages.py\ntests/test_review_package.py\n```\n\n## Nächster sinnvoller Schritt\n\nJetzt fehlt der nächste harte Baustein:\n\n```text\nAsset Plan\n→ Provider Job Specs\n```\n\nAlso für jede Szene automatisch erzeugen:\n\n- Kling/Hailuo/Runway-style Job Spec für `cinematic_ai_video`\n- lokale Renderer-Spec für `mechanism_animation`\n- kinetic caption spec für `kinetic_text_overlay`\n- klare Prompt/Negative-Prompt/Duration/Aspect/No-text-Regeln\n\nDann haben wir keine abstrakten Pläne mehr, sondern echte Produktionsaufträge für Clips und Animationen." }, { "role": "user", "content": "[M G] bedenke dass wir kein geld für Credits für Hailou, kling oder so ausgeben wollen. der workflow soll gratis sein. Wir haben nur dieses LLM (ChatGPT Pro) sowie die gratis über Build.nvidia.com erreichbaren LLM (siehe hinterlegte API Key NVIDIA_API_KEY. )" }, { "role": "assistant", "content": "Erledigt, Sir.\n\nUnd sehr wichtiger Punkt: **keine paid Credits**. Ich habe den Workflow entsprechend umgebaut. Kling/Hailuo/Runway/Veo/Pika/Luma sind jetzt **nicht mehr Teil des produktiven Pfads**. Hübsch, aber bezahlt. Also raus. Wie ein Butler mit teurem Geschmack, aber ohne Budgetfreigabe.\n\n## Neue Regel im System\n\nDer Produktionspfad ist jetzt:\n\n```text\nfree_only_no_paid_video_credits\n```\n\nErlaubt:\n\n```text\nlocal_renderer\nlocal_ffmpeg\nfree_nvidia_llm\n```\n\nNicht erlaubt:\n\n```text\nKling\nHailuo\nRunway\nVeo\nPika\nLuma\npaid video credits\n```\n\n## Neu gebaut: Free Production Jobs\n\nNeue Komponente:\n\n```text\nautoshorts/free_production_jobs.py\n```\n\nNeues CLI:\n\n```text\nscripts/generate_free_production_jobs.py\n```\n\nNeue Tests:\n\n```text\ntests/test_free_production_jobs.py\n```\n\nGenerierter Pilot:\n\n```text\ndata/free_production_jobs/mechanism_pilots/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\n```\n\n## Was sich geändert hat\n\nVorher war `cinematic_ai_video` gedanklich noch:\n\n```text\nKling/Hailuo/Runway-style clip\n```\n\nJetzt ist es:\n\n```text\nlocal procedural motion\n+ parallax\n+ Ken Burns push-in\n+ depth shadows\n+ beat-synced shake\n+ local captions\n+ FFmpeg/Pillow composition\n```\n\nAlso: **cinematic-looking**, aber lokal/gratis.\n\n## Asset Plan angepasst\n\nDer Asset Plan nutzt jetzt:\n\n```text\nprovider_family: local_free_renderer\nbudget_policy: free_only_no_paid_video_credits\n```\n\nFür den Pilot:\n\n```text\nprovider_families:\n - local_free_renderer\n```\n\nKein paid Provider.\n\n## Free Job Specs\n\nFür „Warum ein billiges Auto teuer sein kann“ wurden 9 Jobs erzeugt:\n\n```text\nproviders:\n - local_renderer\n - local_ffmpeg\n - free_nvidia_llm\n```\n\nBudget Policy:\n\n```text\npaid_video_credits_allowed: false\nnvidia_llm_scope: text_refinement_only\n```\n\nWichtig: NVIDIA wird nur optional für Text-/Motion-Brief-Refinement genutzt, nicht für Videoerzeugung.\n\n## Was die Jobs konkret machen\n\n### cinematic_ai_video Szenen\n\nJetzt lokal:\n\n```text\nexecution_mode: procedural_motion\nprovider: local_renderer\ncost: free\nrequires_api_key: false\n```\n\nWorkflow:\n\n```text\nillustrated/abstract background\nobject-layer parallax\nKen Burns push-in\ndepth shadows\nspeed ramps\ncamera shake on beat\nrenderer captions\n```\n\n### mechanism_animation Szenen\n\nLokal:\n\n```text\nexecution_mode: mechanism_reveal_animation\nprovider: local_renderer\n```\n\nWorkflow:\n\n```text\nx-ray/layer reveals\nanimated arrows\nrisk meters\nprice-tag layers\nsequential labels\nbeat-synced clicks\n```\n\n### kinetic_text_overlay\n\nLokal:\n\n```text\nprovider: local_ffmpeg\nexecution_mode: kinetic_typography\n```\n\nWorkflow:\n\n```text\nlarge words\nscale pops\nslide-ins\nglow pulses\nFFmpeg/Pillow compositing\n```\n\n### NVIDIA LLM\n\nOptional:\n\n```text\nprovider: free_nvidia_llm\nrequires_api_key: NVIDIA_API_KEY\nside_effect: text_refinement_only\n```\n\nZweck:\n\n```text\nVisual brief → lokale Renderer-Instructions\n```\n\nNicht:\n\n```text\nVideo generation\n```\n\n## Tests / Git\n\nTDD durchgeführt:\n\n- RED: fehlendes `autoshorts.free_production_jobs`\n- GREEN: Free Job Spec Builder + CLI\n- Bestehende Asset-Plan-Tests auf free workflow umgestellt\n\nFull suite:\n\n```text\n46 passed in 0.98s\n```\n\nNeuer Commit:\n\n```text\nb54a903 feat: add free production job specs\n```\n\nBranch:\n\n```text\nfeat/initial-growth-engine\n```\n\nRemote verifiziert:\n\n```text\nlocal == remote\n```\n\nPR-Link bleibt:\n\nhttps://github.com/Gamexgit/AutoShortsBot/pull/new/feat/initial-growth-engine\n\n## Skill aktualisiert\n\nDie Social-Shorts-Skill-Notiz wurde angepasst:\n\n```text\nfree workflow\nno paid Hailuo/Kling/Runway/Veo/Pika/Luma credits\nlocal procedural motion\noptional NVIDIA LLM text refinement only\n```\n\n## Nächster sinnvoller Schritt\n\nJetzt können wir den ersten echten kostenlosen Renderer bauen:\n\n```text\nFree Production Jobs\n→ Local Motion Renderer v1\n```\n\nDer würde für den Pilot tatsächlich MP4-Clips erzeugen:\n\n- Scene 1: Auto/Preis/X-Ray Pattern Interrupt als local procedural animation\n- Scene 2: Layer peel / hidden system reveal\n- Scene 3: Preis, Reparaturrisiko, Standtage, Marge, Liquidität als animierte Layer\n- Scene 4: Twist mit collapsendem „Kaufpreis“-Layer\n- Scene 5: kinetic series CTA\n\nDas wird nicht „photorealistisch Kling-Level“, aber es kann **retention-stark, beweglich und eigenständig** werden — und vor allem gratis." }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_GBvtzCH7i5Sr7Tm5K1EbCnm8", "call_id": "call_GBvtzCH7i5Sr7Tm5K1EbCnm8", "response_item_id": "fc_0506565374d00478016a11858614ac8191be5e09188e5f5a25", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-growth-engine\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Assisting with skills action**\n\nI need to load the relevant skills, possibly focusing on social media shorts or software development with test-driven development (TDD). 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It should render from free jobs to MP4 and include metadata. I’m considering using Pillow for animation, likely at full 1080p, but for tests, I want to keep it lighter with smaller width and lower fps. The behavior must filter local jobs, exclude NVIDIA, render individual scene clips, and compile them into MP4 with scene count. I also need to ensure that ffmpeg is installed and will test using TDD techniques." }, { "type": "summary_text", "text": "**Implementing local motion renderer**\n\nI’m working on the local_motion_renderer.py. I need to define parameters like _font, _wrap, and _gradient. I see that local production jobs have mixed jobs from local_renderer and local_ffmpeg. The function to build scene frames should return frame metadata, perhaps instead of images? I might generate frames as a PNG sequence temporarily and then encode them into MP4. There’s a duration mismatch issue to address since the expected duration is 34 seconds, while free jobs sum to 25 seconds. 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Tests expect it to be less than or equal to 6 seconds, but I see the mechanism could break with 13 seconds. The goal seems to be capping clips at a maximum of 6 seconds each. I need to write a test file for local rendering. Is it necessary to avoid ffmpeg in unit tests? I want to ensure testing will cover the necessary function.", "reasoning_content": "**Considering test specifications**\n\nI’m thinking about fixing `duration_seconds` to have a precise float or maintain it less than or equal to a certain value. Tests expect it to be less than or equal to 6 seconds, but I see the mechanism could break with 13 seconds. The goal seems to be capping clips at a maximum of 6 seconds each. I need to write a test file for local rendering. Is it necessary to avoid ffmpeg in unit tests? I want to ensure testing will cover the necessary function.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYW5d5MlCqqPr9MLrQ8zSJ_q3LzZo6DWtCimdC11sOHh1GdJzhU0-z0uC7P_5xWBz0Wf1AFNbB8j1-d1bpGfI1QGN2OdXb8uegNwmsrf_Cut1B-dMliVomhdv3nZ9dkHht-SK5xgC2633A02cqUXk0HcpanaU5ImXgFT4PoxKwjGyDPTHAmYzPmee6PHlI9OOy11KqEjfhg8RUspBDeDjxdCZv4nmMrNWrAPzo8zy3c_zbfRhR4i10NMF2-10PbkDY3TXGk3x1htv0xoWoIKpQe-xLtsouRZaMeLeMaI7miSqZsfdFYnxjNKyD7FkR56r9qi-jWW0L1rddLOqwrPMK3s4cLRizGnrM3sIyWqCFjqeH9aIihP_FM3o3Nvnz-9nDLm4O1d5KguaEmb9mfD2a9_tP-htkjpAahVfrHAz4OMYqP5usqOOIKh_-2ysc4dpnt-_xb42HIch0PjbDyYvXc38hbVJWOJvC1KPiYeXUy_VoXpwIyQqAILq8CUEHT8HE9QDZtZSQZFEbJwery0UjsGrQk2SRMyPTdgEA_rQNMVoDSmPZgs1GICripTy7-gYe02IWcUGV5yHXlI0tc22Tu3c9FKG2aC1bupSOwt24WHmAnKDUMGlFkvqu9Rdnk0Dm_1GpbEGeICQKUNfKJEZ0VhfcHnRsy3SQtnnejieyDGwEOGto3P1C-QTli80kUaPYGK_E3zDLXiPDkEoxhgV9mGba27cYE5kAJEHwJSVQFc_BvNmeNRLxShTJOjuoz2EhUhdELowkV8oLKxCBouPhX2xGeIS_ZoDGrxE1XQMNBul_iTfRDIufaqEHJguZ3xcycrVJ5fQhVDhMBOthK7f_X20-iRD7orppKyGjrWG-T4d8BGnOWCmYc0xym7xY-kZOESMHA5ewE7NKLjR-RtpC1RYnmnvTwHci-vTgLocRCqZ5Bzpp637YOJBDBnhfnH5i9eZ2D4-nLYfP_iipVTo-Qd9vpZCM6HGmuE8NcnRQy5VKXxNF0fxwsIeMRo11KpySxsLSIs85yzYOAoGVnOOTqHUcow6YwTEyinqSJpVsJWqd-d12Z5Jkrfy7LZKnkc90I_d0i2wXG8Bwa4feVgIvgDU6YxXlk0QCGdFybSWBEQvpaaEjTnNg1vo2zAnBLbAXFY0hNqCxEZEpyAdm0WV3epsbtstd1HCTeyj_4G1R2Yb0h9y0VtXRDcRnf2Y1M_z1roR25u-DEl7oCm8S6htd7g7IF_5DrF68BGadXoH-ukLD77la00ybMIV7E1-hI-oedut-WywSlL_EaOujm0-Rflap_7KABsOXOsN_sh6ndOplx1X6m0-vwmAEG0JWljDTJo6Alf-AyMfOws3aASDFRQ8Xwbga325heq61N9lbiXYkGwjx-1aq8dOowahDuQWCzAmmYwqa93PBSYuFvIhp604hN9RqJG0enkdTfm0ohs9R903IRHKXMy8B8x60ETrU2erDBCmKAOwnyFGyGhTWsId4fZvYBXddng193w9FFdqbIs36j89Np45buXRWXoTclEfF1PcUdejFrlOFUvL4YOMXMP5lOvZ1bMDRRigz-9jXZiX3srFVLhxTAIT8-gfa_2QSO3o93cnY6EmdTfX6UAzD7ilPRDD5SFpAzuw-UYFLYTTUj1YjajW7F8sbdrrOJtqRVR_rUn422idKzYnImqpJI4NTulJhUcv4zCqgcvUOOSFvKOhRb75V4lotXYVKiVB_eCAwMtJatQ-KljT6OlldCV4-K_4ayJKq-d0HC69NY8YbPAyhOTuGV9YJ0HCoOtk859Go3NG8I7_SEuog4rSudU1SKG-lJ_Ar2QtOgSGwWJ8BijC-ORSBSTSku5llOnvj3UgU91MP6uH1Av6znshoTkcrPHZqhF0UavTgkbCHxtiyTUEP0JynKulb-Sds0eNMFwJUEWqGyZLZV4NCqYzIwj41SzOTfCQ_8ezxk7HEhnrnPT8UZWiOD2km-A2pB2RqAycdatgSPYdvts3-oxGQFCNERGlIAaeg0UnqdzZrVWdGQzoaw8iayQMc7eI48UDO0xbQx73XJgVh60N8DCnEQjIUAvOrHj0svxo-0P7ly351CfSXr1sZOtc17I4xJB", "id": "rs_052e8f3f15b7b802016a1185b3ddb08191854f73a962ec5acd", "summary": [ { "type": "summary_text", "text": "**Considering test specifications**\n\nI’m thinking about fixing `duration_seconds` to have a precise float or maintain it less than or equal to a certain value. Tests expect it to be less than or equal to 6 seconds, but I see the mechanism could break with 13 seconds. The goal seems to be capping clips at a maximum of 6 seconds each. I need to write a test file for local rendering. Is it necessary to avoid ffmpeg in unit tests? I want to ensure testing will cover the necessary function." } ] } ] }, { "role": "tool", "content": "[todo] updated task list", "tool_call_id": "call_NwDDhJlOzhRtkL26gBngQi5T" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_q47DhHxmqT54q5EQubBd3lI1", "call_id": "call_q47DhHxmqT54q5EQubBd3lI1", "response_item_id": "fc_06408ab1f4c5c4f3016a1185bb33ac8191a74b1678f0df0a0f", "type": "function", "function": { "name": "write_file", "arguments": "{\"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/tests/test_local_motion_renderer.py\", \"content\": \"import json\\nfrom pathlib import Path\\n\\nfrom autoshorts.local_motion_renderer import local_render_jobs, render_local_motion_video\\n\\n\\nFIXTURE = Path(\\\"data/free_production_jobs/mechanism_pilots/hidden-mone...[truncated]\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[write_file] wrote to /home/agent/jarvis_runtime/AutoShortsBot/tests/test_local_motion_renderer.py (48 lines)", "tool_call_id": "call_q47DhHxmqT54q5EQubBd3lI1" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_U0gsNxTgS7BwW1siS3Z1baTC", "call_id": "call_U0gsNxTgS7BwW1siS3Z1baTC", "response_item_id": "fc_0003bd91189b5fb0016a1185c8444c8191b0c38797fd3b3bfc", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_local_motion_renderer.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `pytest tests/test_local_motion_renderer.py -q` -> exit 2, 1 lines output", "tool_call_id": "call_U0gsNxTgS7BwW1siS3Z1baTC" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_tq3nly8rVkZjPMUtcYEn082V", "call_id": "call_tq3nly8rVkZjPMUtcYEn082V", "response_item_id": "fc_0e0b2a73be5cda4b016a1185d0bda88191a365e1279937fa4f", "type": "function", "function": { "name": "write_file", "arguments": "{\"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/autoshorts/local_motion_renderer.py\", \"content\": \"\\\"\\\"\\\"Local/free motion renderer for AutoShortsBot production jobs.\\n\\nThe renderer intentionally uses only local Pillow/FFmpeg drawing and compositing.\\nIt does not call paid video-generation providers. Th...[truncated]\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYXQYK8Pxp-x9yV9AEhZ8qbPp9swNvPjFMEIDjn_t60m8c3LyWEZLoOYGlzbNhIbB8YDubEBZQ6hUAwEb33V86bHSYFVYWVP5xvj1BmQ1y4fhVoHv9lHaBhosO77TMdCmQ9WIoqr2Ulwy7LANUoF41KYKWx1kqxwgOLfXPC1U3FeCw3fFhMdYpR7jz9n4EQX9yt2myW5vJcObCxGXaMJlqAF-53DHHR3KwJPhMJs1NTbIzuyrqSkAOjsvwe1hzc23KgflDAE8pmNWTikENemyJLAKAgKqXlCwNb5AtIR9pdZUt1EjKa7omZWT-Bay_6dvV_O8EVYFq2KxdCK0lHSYpS5cDY2by9aTlBCNYW7A85GKRHVCkvv673LoNc3gsc526QiuhT0jqXBSP_M_hRfpT49neEidoy6FpjWQuy9-2SBIlFJG9z2p_wpzXsdnAVuIOm3ydxnTRc2tQME6L9UDYaAX1NuzDAOdhZPiFMRSO2CGQ1H8bLYBMWNiWNywKhMVPbZVg1b96D47Gc4C7zFgVEmtXMj19pEcTC0aQbloPB3omJIO6jQn2506ctAVgbiRU_AVFecJDZJBrxyXCjo2D2TGhX3fi9xJTXJmDbJvP3Wm_J6PSczxEiFvcn2IGAhRt3Wma0e9592Rm6OQ12tiCJxG_JwQbCZ5gEhHSyPq8jXKkh9VCARgI-stQ_LFVCAX9_ADu9nbiV3BWXu7OFlzpnlo7L8qTEaXopDiCKNqZZH-KKWmKLFwjemy64S5NwWdJ7fDeX6lyyVSlWTbwT33d1K0pcBnTUCtQTda5ZbH6lYGvzNR0Uwg0BYoY6hzjjm3Yatjzg2Ke_T_exYVYZBYHX_RJ0VxhTRpRHqH9NXtjRwOdm3xOqyd9fmssGnEmu4oJ9mgVLEDTrsTArtqin53aBkrOS_vOZW3qSSziJG-xxEJYsWmjQy98Y_aFj0fRyIz4NktJgvVQiO20dYGWZB-9BH_QtJZ4HJmdYqPEDtv-Y9P91o7VSvKuu0r-QClXj3tHeI6NAMTM0AHtFasEY_ipB7MCq8DINrEi7jnSn9HKaxaZlg4_lngWTaXDEVKT6LFaQ44RBrw4U2AMVvQRthANG6o38T14N2a36caaruu2aA1wairBDsUfmsvvqIgLmV761R_encNjc0Ex7osfhgiwk8qTumJvxeu0k9oicRhv0bBSTU1SfkUJGptBLOJO6FdwWS9FdUJ0hgpX9pdtuEe_GZx9VNqicoPKP9amJpLAG-F3IpU-IYbx2bn1i48bMKwozMcg0kx0L40DVP5lkhwnMIYUVx3Ivy_YxlPcQYEdKs2zN9tO3tBOMTJQ97nGlPipdf56CoHyR_0vrS7lgMA_n0K2yvtTV13b62LNlqklyx7Ntq_J8rzBAqotSukmF2neaWhuJemPo2zZd0fsawpgLBBLj1YVZs4cGzqvRUMQP6Cv2zImWEmmC01e-illTZ52X11g2spwWJVcWjZ6jPSXQ0eSMsm05ZFdR_LD7VFTKftaMJesEV1IEN4iV6Zd7mHLL7BlQ-Jfd8tsFTPbst0cUGo0-KYj8lpgKdbkodm7f0uQGIXpQ5KQw8mFCSaIdiuaMT3rNzsyfuyxcP-xF5XJvXiNVM48XTayg-RyvuNLBC_jF7b7M6G8i8Bmqecx5hmbyRSjGxH3GyksNC2tU0EO6nV7oqP7FLhw9UVjUbJq-2d9sXzcy5OD5_k24HvYL3A6bgfsjIVXVxjT-8NFzBuv3iYp5CesnvoSKOfwiDnCj8J3of-NrhjmUVEmxcZbwwfdYB3Ebql5tFawQ2ydeo3LlMkM3_qQLgMGwhBOpAru9tjLUIVAqpebPgWssdSwxaX6K7YdTx0Ct375Umxec05fZtx2oO1eSIA4_I3HvV84nyVErh3-r2BM7Z7TdKBP7aHF_Xn0zowmUnBsmLZCrnfXOV2Q667DzboFQ9O2tFZb-bI-Yvr68uum9Z2-rGrUXpv2Lbvf5m68BnjvF-qJKZ436Vtyb6HtsYwudWsY70e9UbnkD12IqUhZswTP7rBF2-nM-jRCUcAAThTlgG3ii3IftFM-M-Czo0OXY4V3XIZ_kCekgd0cDalQo580rssttvcxEo26STjIC6lzgYADsRYHxc2dvkXuKJ3gCe9Y7qErR4YKZpLq5EcBmRAMKjfI1K1yiZDJHAsUolWTOuI7fNbS_obl0vwmLkTTw_WSlDOM1mc5FWMo1X9xKydq8x6Y-vKAyu1uCGJ27YsBKM7HNceFCjFjpwo7SPVZgatoA616o04-GrfZnc-IuHo8iUvmUvi2byJ6JdBMToOlOkbT-VPUA0m_ZqPS4pz6dpaAj2zl5W06FWqnYZL0mYCl3UqBIPEEo-", "id": "rs_0e0b2a73be5cda4b016a1185cbbed08191a470e3771e3f5dd0", "summary": [] } ] }, { "role": "tool", "content": "[write_file] wrote to /home/agent/jarvis_runtime/AutoShortsBot/autoshorts/local_motion_renderer.py (307 lines)", "tool_call_id": "call_tq3nly8rVkZjPMUtcYEn082V" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_b4Qe4BGvJl5ykqwvZo4qhE6m", "call_id": "call_b4Qe4BGvJl5ykqwvZo4qhE6m", "response_item_id": "fc_0d4cfd6af339670e016a11862a46cc8191b47ff0875267d0f9", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_local_motion_renderer.py -q\",\"timeout\":180,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Fixing typing errors**\n\nI need to fix my typing — maybe I should set `total_duration` to 0.0. It feels really straightforward, but I want to make sure I'm doing it correctly. I'll have to come back to this later and run some tests to ensure everything works smoothly. It’s important for me to double-check that I’ve set everything up right, so I don’t miss anything crucial. Alright, I'll keep this in mind!", "reasoning_content": "**Fixing typing errors**\n\nI need to fix my typing — maybe I should set `total_duration` to 0.0. It feels really straightforward, but I want to make sure I'm doing it correctly. I'll have to come back to this later and run some tests to ensure everything works smoothly. It’s important for me to double-check that I’ve set everything up right, so I don’t miss anything crucial. Alright, I'll keep this in mind!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYYqCkQMOot_V-b-sUof_MEymR9h0tNbOCA7tBcvlm5u5hx3g8jNWokLLFJj_dqouHck5ya-6HQrkkqsHdHz5uD6fgk1ZPMIZEALrpKRwWoqXUal_Z4JT8lkadhOfJVTyXSg9uCbB8SGmsLFtUvIZ4KOoukyDCGtaBe8SjCvfamyQClR-ssWRrdoh1BvkFR237YzQ_SFozD1kyWNZjmw3t9zo-qHRY6_YDFEidQc5pAUO175HR-jCKQ22Iliys_9BU1s2Tbk8uO4grrsRZqBgMTrXwgx94ROBrBQfIz5wQAxyt6Z81gsTsotSNV0P1-oCJpDuu8nAxRieQJYGgKFUzYB37bhCADBpNWfqaKJkxG4OEWbHErnatcpKYS1u2gnWo8p6p6KNX9kTvYiVf6veZCtUZ39Od1oN-IKxVtaJrUwvh40Z-p0kKAvxkc9KhHEl_IJ4Xw4ri1JBY8lqVkpRT0pwz9by_2JpSrZVzAXTun6EVqKpFhNiYrYKfv0dLHsQKLSHGUP2SPhmC0K80vn4grL3aeJocJ88SlE4eULgGdgscIddR-OKWRInEo9hX3cjpD0vPMM3O9JOWuGtJ2Up0YcgrN-tx7Er6HKoiglRSi1n4sJ10SWf6jdmvR_H1o8FAJzfZ4qU7bnDQ8F0a7HkCRZkgmWvMbxQEUG5ZQ9lJtVHRT4pqTwWU-5iTwrvzPvJr2n1ks1IE5RIbLhrWEy7JA7yY5k98b7THLbqEKzBl93CkVwftyVhSrxRO1QMUd7n4LjBuOR1tSD0m32BC4iza1KQjkmZh61B2Y-Kex_4WhO0AjJR3_zLJ1mJ0b2RdW0PyNiYr8hv5h-O06eYDQMbsWXLOKZCixUHYzUQbd38EmHVRfHjWYGqPmS9XUOyBoNbpt8FRyCVZP9hQdfUTDKZIktKU1r818R7wi2fZz3qbHZ33XbdVxdCVXYR3IMrapb_rnpvPnU-MLUYKJb6doOl5BffjV0gltweE2aoqd1vRnqkV8=", "id": "rs_0d4cfd6af339670e016a1186281b80819180633b7960bfcb41", "summary": [ { "type": "summary_text", "text": "**Fixing typing errors**\n\nI need to fix my typing — maybe I should set `total_duration` to 0.0. It feels really straightforward, but I want to make sure I'm doing it correctly. I'll have to come back to this later and run some tests to ensure everything works smoothly. It’s important for me to double-check that I’ve set everything up right, so I don’t miss anything crucial. Alright, I'll keep this in mind!" } ] } ] }, { "role": "tool", "content": "{\"output\": \".. [100%]\\n2 passed in 0.98s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_b4Qe4BGvJl5ykqwvZo4qhE6m" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_ECR7G1qtMo1rSdTmN4yujNXU", "call_id": "call_ECR7G1qtMo1rSdTmN4yujNXU", "response_item_id": "fc_0a0ef89447c136e0016a1186307b288191860af84735ea25ca", "type": "function", "function": { "name": "patch", "arguments": "{\"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/autoshorts/local_motion_renderer.py\", \"old_string\": \" render_jobs = local_render_jobs(production_jobs)\\n output_path.parent.mkdir(parents=True, exist_ok=True)\\n total_duration = sum(float(job[\\\"duration_seconds\\\"]) for job in render_jobs)\\n\", \"new_string\": \" render_jobs = local_render_jobs(production_jobs)\\n output_path.parent.mkdir(parents=True, exist_ok=True)\\n total_duration: float = sum((float(job[\\\"duration_seconds\\\"]) for job in render_jobs), ...[truncated]\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Fixing LSP issues**\n\nI need to fix the LSP, and I’m wondering if maybe pyright isn’t included in the tests. I should consider creating a patch. For the total_duration, I’ll use: total_duration: float = sum(..., 0.0). I think it might also be a good idea to create a script for this. It will help ensure everything runs smoothly. I want to get this right, so I'll take my time to sort it out!", "reasoning_content": "**Fixing LSP issues**\n\nI need to fix the LSP, and I’m wondering if maybe pyright isn’t included in the tests. I should consider creating a patch. For the total_duration, I’ll use: total_duration: float = sum(..., 0.0). I think it might also be a good idea to create a script for this. It will help ensure everything runs smoothly. 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I should consider creating a patch. For the total_duration, I’ll use: total_duration: float = sum(..., 0.0). I think it might also be a good idea to create a script for this. It will help ensure everything runs smoothly. I want to get this right, so I'll take my time to sort it out!" } ] } ] }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/autoshorts/local_motion_renderer.py (790 chars result)", "tool_call_id": "call_ECR7G1qtMo1rSdTmN4yujNXU" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_4SlPm1FJI7NrFZuspuOUNrkI", "call_id": "call_4SlPm1FJI7NrFZuspuOUNrkI", "response_item_id": "fc_00df89411b4af195016a118635911881918229cb9d7a92993c", "type": "function", "function": { "name": "write_file", "arguments": "{\"content\": \"\\\"\\\"\\\"Render free production job specs with the local motion renderer.\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nimport argparse\\nimport json\\nimport sys\\nfrom pathlib import Path\\n\\nPROJECT_ROOT = Path(__file_...[truncated]\", \"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/scripts/render_free_local_motion.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"bytes_written\": 1824, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_4SlPm1FJI7NrFZuspuOUNrkI" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_butWu8iMCJSmd6N9lbTY7lIR", "call_id": "call_butWu8iMCJSmd6N9lbTY7lIR", "response_item_id": "fc_04d5d8fd7c225b61016a1186423b1081918f774d95725fc0eb", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"TDD für Local Motion Renderer v1 schreiben und RED verifizieren\",\"id\":\"tdd\",\"status\":\"completed\"},{\"content\":\"Local Motion Renderer v1 implementieren und Pilot-MP4 rendern\",\"id\":\"implement\",\"status\":\"in_progress\"}]}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[todo] updated task list", "tool_call_id": "call_butWu8iMCJSmd6N9lbTY7lIR" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_bW36Y6aL7npIP3S89ND37FNS", "call_id": "call_bW36Y6aL7npIP3S89ND37FNS", "response_item_id": "fc_00b858ba588803c7016a11864b32b48191aa930ccd2f539b07", "type": "function", "function": { "name": "read_file", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/tests/test_asset_plan.py\",\"limit\":180}" } } ], "finish_reason": "tool_calls", "reasoning": "**Examining test requirements**\n\nI need to ensure that tests in local_renderer check if \"metadata duration matches video duration_ms.\" If there's a mismatch, the test could fail, but it doesn’t always stem from production jobs. I should fix asset_plan _duration_seconds to return the exact item duration as a float for mechanism pilots. There's an existing test that expects values to be less than or equal to 6 for generic top3, which might break for scene 03 with a duration of 13 seconds. Let's analyze the test_asset_plan line further.", "reasoning_content": "**Examining test requirements**\n\nI need to ensure that tests in local_renderer check if \"metadata duration matches video duration_ms.\" If there's a mismatch, the test could fail, but it doesn’t always stem from production jobs. I should fix asset_plan _duration_seconds to return the exact item duration as a float for mechanism pilots. There's an existing test that expects values to be less than or equal to 6 for generic top3, which might break for scene 03 with a duration of 13 seconds. Let's analyze the test_asset_plan line further.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYZL2CZ2cTwPMMoG80pJZZJSgB3MkfKX9NKH4JtNolEotdJUc9ATR-uIMsznd--zjTckWWbMVehQpqbsqGjs6lhqajN8MzID5R9AZrCRdA2AWHpApMxTsyasbG23aA8Ay6ltAJyXKyO_9dywR6EUMQR2tUlWprGXdPKO_oWbz-wHtO-1HusTXe2hH9SW8VJ11Ogfxab2xDiOp3vVEMoPVJiwgWG2Hhm-nCN016qIsKjaMAFNTY8UCYbiPB2x88CnJxhrPakqyKG6_w5Fl0hnx7X4nLlFyxXWMhWnrUQfClgut41lycbxlAW79njLxy5xJZueOuDUtHaRvlNnaFdHwdrtNqhZbVNayQh1EmOThOKWqkGwJQIz9rrijCpNIulLTOO6YtjUy052Xo0i58uXeMUyrhHq4x7j80zUtRo23Bcot6LaFs_BDONL_XSEvO_yBGWkYsIcx3Ix0Xa5fvPWJ1dLEC6WbaTZ6qOkRxAsecn_STJkEydKfkbR8mNuR5_HnJxcrljUuKFzSwhM8h2q7BwF8EN1yvPxG3Jy7vw-LPceeRkvBj6HHKPbvMRbKFHOnMFM5UPY5dkyb4RnAmFmL35Jw7EOtXpbtHHt4Rts4_WoSOjF8bs8B80UqXpyNEpxF5E5YRNNd0dLfvaYqvJ_Wk5rDdGML9mIaTLplbuXAT6UcE3Vz5HIKtZVcxYSJqsN5S9yGU0M-StbGUkkOE7SjFCU_P3mqtbcghhuXTOQFfIn_b6ayQmYCQ958vxkPcuFrqZ3WLxPX6UJE_GeOU7OUS1cPEsVcrJ9q1i_1IeOdHQ8FOAllua5YpCW3RWdiZnixfaHN7J_r4MsaiwYuhsac6JFSjkB4GIGG-RiRRgCFUpIpeID7Y3ZkM5EQdM2-PG5WdDm1ihKZuJ-i2ObsWraxgJCnTLcaFg9Ji0hyvMVdpYEWoDHnkf0ks5wZkiR7UCXXExilpyQO-CtvmB7fJ4QI7KZZI6zH9AKd5OsyVuMQs7ra1u4XgF2KLL4Qhz5Yj2PgsuuMQBXKA_365MNbXtHZBmcTO2GOsNLbohOJEvtyarU5ZxL4nQwxcmQaR3m2o_INvNerjjr3A0amgGu8f9TxDAq9b2RFAgtn6C3OY_Vax7jrMPVqB8pwH3mvz4LZnaGHA0Cm_gnXdnh-NqhlnZHStaesfH7NHn3dEXEHT6jDf25DJOgkFuNvRIjScy4hoxYasCWq6j85scMSxn3RSFwVWEg8kHxG4K90hIZl9XgD67w6wBt1hDMipk8irgSMo7UQH3LsRiiiS3VcSrp_x4vHNO0Rg7SmhYtQka1QX6rSu5x7MW8j2sxnG1SMCft1DwV45tqTOfB6ksvosJFMj5QULx2ZSwdhUHMU4GpYN2eOaX7WEOGlp992VY4T84Enm5tf-Df2GfFbh8VcCo6_4cnCy8EVr8yla-FsKNx5_ryOMJdKCDBoyPnjXYmBSm6D41oqCEVvVDi4W-IjEyWEjxwUUfSf6Udq4IBO-YQOwCYpC0w0MlV3Colz26z8mjZjePkDU-1BFxfFzTvXr101MwUlUVy26QzJQO1GOoZDD_mlASZROGJhr0_V7MewI40aTvpvmlHJMy2akBbjvxhjUbjUaJUJHeFqpT5dn_1mM3llEth_P3QJw_R79Hcf0FjpZGEkc7pd59TPPDB0sSAmJLeNrFJAjIt7enL26zyrxAM7HZC8arIU5QPSQ0u61L6j2c5POn_4-hS2Igxx656JvX_Xq2KyRkuz0eDCbNv3VkuhenqDb-S7LTGQa0m1fUNs4cUbIAs21inO5gYt58Bt5E-rNv_LEllx-t995Rg557JhcjiibsUqumw01FB--rAEri_QDSzgZ_DfT_2eCdhBqvP8mlp8DVNofGw26Nc4LKStdinSIOxO8YYVfg5ZFvYFKPOynyL5WzWw-GpoO8YvXB0MgjXYo9WDXcpjbH1j0MYFQotWRmfWlYsRqKlYZUYfIv-Fl3FN2Ujrk-TPXAKXpdvoXERq-4sm1MihO2JY63_ynbjwG2SW_R6vZmEuYLADGrajOFTTi33KTntZY4yJSlTNM-__n6M3vQjNsoZ_wT6jvTN6JXTxmD-9Jsxj6fhIJ_ZPKSBEjO0AHv62kg3uvMME4_wvgfbi5pEqREnGCfeASXRr4ICVWSZtqQw3IMxuBkw1jmONnhken4-cGc2fT_MKaDexpHJibIdEF-nKxhU_mg3Yt2CqU-k2rvNGvEv5PayBFXulgX4gq4ewJwaj2g4FIOSforJEWkhW9oXsqW_eJRP6A-FwAU0dkw_cKv15K3eNgrib9EBAwjjZd2yqUtbz2majHZStEqx2jmYex1QP-HD5TIA_kKTGOssGidZlLUHmXjvtuAHEYC59Hr_sTBkCeLuUSaKdMsrfS_n9Eco4ZpzJfwEc5ByCNY3MPUKH_c_EYbtmlAej1BXfBeYFqkSaO57dYUhYV_CHAKTv3OdNs2UQ1xNml5A7BGQ2ad_QYXTIK8LLV-67DzmEoOzP_Au6Hp1d-QE1DYhJM6yW1YZk7sfzc5zOn_lwkV6VbpYXr_ttfjP", "id": "rs_00b858ba588803c7016a118644d6bc8191a8eda41f396c5d6f", "summary": [ { "type": "summary_text", "text": "**Examining test requirements**\n\nI need to ensure that tests in local_renderer check if \"metadata duration matches video duration_ms.\" If there's a mismatch, the test could fail, but it doesn’t always stem from production jobs. I should fix asset_plan _duration_seconds to return the exact item duration as a float for mechanism pilots. There's an existing test that expects values to be less than or equal to 6 for generic top3, which might break for scene 03 with a duration of 13 seconds. Let's analyze the test_asset_plan line further." } ] } ] }, { "role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/AutoShortsBot/tests/test_asset_plan.py from line 1 (4,745 chars)", "tool_call_id": "call_bW36Y6aL7npIP3S89ND37FNS" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_7H4SmOKtbtN2XZ3NfRPwIESH", "call_id": "call_7H4SmOKtbtN2XZ3NfRPwIESH", "response_item_id": "fc_014165f16418b4bb016a1186558cc08191adff2995fbef4ecc", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":80,\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/data/render_manifests/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Evaluating item properties**\n\nI’m thinking that if an item has \"start_ms\" and \"duration_ms,\" I should just return that exact float. However, there might be an issue where older cinematic formats could break if the values exceed 6. So, I want to take a closer look at scene durations in ai-004—could it be something like 5, 8, or 10? That could help clarify how to approach this without causing any issues.", "reasoning_content": "**Evaluating item properties**\n\nI’m thinking that if an item has \"start_ms\" and \"duration_ms,\" I should just return that exact float. However, there might be an issue where older cinematic formats could break if the values exceed 6. So, I want to take a closer look at scene durations in ai-004—could it be something like 5, 8, or 10? That could help clarify how to approach this without causing any issues.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYZVGFj_27TKKfHNIk6mu7dskg6-dgion5XXvxj1GAFqmwrJq1Xx-mws4-rf2J-gAEy_UO-SFK-PXErSXIIx36qhainwgJkBYZy3RQPZnXJXOs-B1Bh6IL9mL7VWxAAh4WuJdLpZOjo9xPCzhP57tDF-sUrJ8u_WzniYr-2bIIGdMtGKY-oIDRIj9Aj7kgsSN4xPVglrzC2apc4-W4qr1uR31KftLdSPtxjzTH0yhBtK7LhPZ_uyaqozQRnzn1SodnHY0XzUerjsUA9a8hF2QBzhbjfNIHSrecs-osgzvRWkQLtr1uepoBPxoqTy8vOMvvvW_YtPS4au93n53wazzoMjfj-JsZBzPd_Bgf55xL_lqYIjL1GoSXRiZeeC7pkQU_nGq_83NmgTwvJakIOYgikGGfP7yGarKF-pBJVLXKxMenaRuU_C97PVAjZ6jvJMI5SSvncnSYV4j8YUrH7VffO0DDVk6V2J_RaQEQ3Q5o4EM6gTHugq1cG1EUpXp7gfN17QsPJ0xIzneZT8FDkfimzRBUzNQaHYE88c5YTwpK6f4fj1SxUtn3XBskcVOKOTNLu7EjblcnaufWyqnBP5wNdLEwxqP3F7JWHI7D0C9sIlF3j4-23JZ-yRsa7dkXReKkEcn4wxa3UzlqWgbPpM-zTBWjCOPFErAlaHsRuOWpkmD_I9KO4tZkkAHwdDxXAXos7nQedjliBkRAUFUednR-QMlcVXOq_sw0M6pp8mrpfJ-4YP81y3QGyX-OhMVYqVFr7Tjg_oIOAPhQSbyWX0MQdQegF3TlDVQjDFMqEM_p1tUMifrTIDhZuQBBFz37N_o1SUm2-S6x8bi7JObHr8rOCYWp-Dyy-n5ZtIT6e-E0xyPoRySxyjpvH-B-MPzVLmbamw0yKtCA7rAzVm78nHuiUf6BydM1dSJFa5sVLDJunF_11iLtyYw-QYJ1MheA8yLd-lH5fdZct2xpA8XUCA7Q7wrDoR_MiprahVOsmYNBaq5yNKcKbedhdC1IDu5xBrOGYyukWR9Mb3bAYaFfSl0yWzpUTvr0cHpWMPNxHuNfPg9TUQllorI2KG1g7127mz6-o_p0Jvzpi0Zr03Pkkq81_FpCVJZs1RhnRKxxeGsTedYYb8gQImrzshj4qX7_d8McZad5rGfCsgtF92gsjmgZE7nT35k07oe6uyxhRk_R3b6VoMd1w0POhry4tYi6i2KDVepURzFxUTQgi2OBbfvUC1mCZDgo8vZ0uXaqmGM5jo1qktBdX346-KfIXvcZ0dxU8RgGgZRZUMkuich2mfidQegMe9A4gHwP7OBDVHhRULxFopdr1W3SmvobkxbThp6meXctTH7ThD_k4viSEqG0l593tcaNUhZcCyv9M-qPUeSudlqh2P-pZ10kJELqC6qK1KaMlsSdLGGDmBo9H1wW7yAVgfEdSP7KxM8zoropcETc6C2X4j0prFyQ6SFQidE2BUn88rAdbVsSzwud4fm7umqHTMOhax0mZ2clImcTlJRC3KlTh-b785cL3D5-MiypJTpBI0n_zoWAUMPIhBqDetQR7wQ262k4SE3O7Y2WcLwLLm_NR7M4k0m_cQiN5_y6dFfViMG1GcefLtFx6KU_Nf43cGVrWuTkYlVNm4IZw4scM3DJ_fwHJpdUNGELtTMwWuxzyMsfKAuLwwPDZPH-aZlM0K3wAC3FQIPC_ueTUqlGdJAqTviHHnsVuQYtrlIa9Kob40FCgyBHtz2eSY_02wO4dF8uMZ2-ugjTaItHUtwlMUOn0K-hvxeyWNAHOQMU0q6QuNVQySRjtVU9k-xK_3pU5pllCnVoh88f8gWPmzEJF7I9VrSVz8bYUU_Jho1078Cpx-pqJynYNzje8o8ZqPf3MbTc5ZS_DhwawehUleBuyoOheee0pmQASkhsnRE0oGhjpKBYOewIiBX5wo1MI_Enyo3CY7IGupTWplrEOcYu3pLwIiw-dqwbt8UOZ3D37VPGxM_NwH7ZQRosoglMIvfFJlYfMLFMa5u8xxeMQMiaVRwlcfh3klo7yCltXCCT-3ePLkt9WAtiLx_jIozA4kunRSFiHN5Qur2_6Nf4d6k5bBcWtRUG5wUA8rHMBhjxVYhhirywBgj_AkbILYtqU_-MQnPQsU0a-NzAqaS_UNSRIaKSb7_EbgUNvrWgK4pHTPWOG6RDWuNINDXMOVb4SKu0Rg_xhLZWyb1ReAGvopHQmASos5j01ssLr8etRJEKvj53kmQJEgxyzAoFVCoxT8czwGN6FZbvEwzQHgbF2xeEN0QsJLZMgnenDtHAQ_qQmcu9GLZ44bF__fF2G6Jk5wQTMbCls_wY5fLnaGIvpdxljon7CsdqcGa847EshyDHqg0fZHMNGwr24cD7HTg_v7ftlGQG6Xi1NEufNTnmOoOovwZ9FgQEpQd5o3O9ddY0Glta57HXYw7TIpZW7fOeqYKQ==", "id": "rs_014165f16418b4bb016a11864e7290819199ba4c79ef5c9822", "summary": [ { "type": "summary_text", "text": "**Evaluating item properties**\n\nI’m thinking that if an item has \"start_ms\" and \"duration_ms,\" I should just return that exact float. However, there might be an issue where older cinematic formats could break if the values exceed 6. So, I want to take a closer look at scene durations in ai-004—could it be something like 5, 8, or 10? That could help clarify how to approach this without causing any issues." } ] } ] }, { "role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/AutoShortsBot/data/render_manifests/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json from line 1 (3,817 chars)", "tool_call_id": "call_7H4SmOKtbtN2XZ3NfRPwIESH" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_D4PaeEUXE9JoYdZgExgO8YYC", "call_id": "call_D4PaeEUXE9JoYdZgExgO8YYC", "response_item_id": "fc_07cc2be4859e7741016a118659724481918df23c31515caff0", "type": "function", "function": { "name": "patch", "arguments": "{\"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/tests/test_free_production_jobs.py\", \"old_string\": \"def test_write_free_production_jobs_outputs_json(tmp_path):\\n paths = write_free_production_jobs([_asset_plan()], tmp_path)\\n\\n assert len(paths) == 1\\n payload = json.loads(paths[0].read_text(en...[truncated]\", \"new_string\": \"def test_mechanism_free_production_jobs_preserve_total_video_duration():\\n jobs = build_free_production_jobs(_asset_plan())\\n local_jobs = [job for job in jobs[\\\"jobs\\\"] if job[\\\"provider\\\"] in {\\\"loca...[truncated]\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYZZVCP4FUq6L0MI6zZgrJEo_0yBYVppQUz-WAgUktPHxYFUwUiZeAiZEmYM3CdE05bPPYzOlGs9bxxh7AaZI2ec8fDEeFV2js3FMm9ty3IDnafQaQkKNTR1n_boT17w1R0L48cPWSp8FYzZDREJ0xssXtxAYK28xtN0X5ToE5PHSdk8761aLT4ZbCQn-GnSiPgc27XX7t9hIEvZvsUiSqEdcxbcK9TeuVbrk9tVPGiWoVEFir0V7_-5uJA3ZsdqxAeBBTd73OGHFpkuDV7rOtw0qKi-RswVhwrNLBpduHJ-o-OiKdr1akZ587u7INKl7jHa2VTnZkVVf7I16eB9b1ujr6jdjXhkmSqXFISuS9LkzA5yYyIkbtUejJaHPTuqnit78NAKIGPrI6hgvHrko8Gjoz2zc1Xg1EunoPqSytUytHaSomIRBFhCtRH6DHI1httkj6OkMkj8ZQ0D7U1FxSnYOf296wzQ0Ea5yX76sE8FBq35nasOvqt0zAipmiAKjuPjqHHAtr-Nc1940a_bUfiE7m-Yczq6sSd9yOkdjq1koSD8qdGZtnhrkaoejgVG5qBMaV06bV1byZsOuORUoodcEqbaHPQ9_gZqd-uNEgr0Ri99kpNKjbTDl57yXJiU1npmHKGAxAm7Ij9PP3efBRjhLIiG2Pp9xSEj37xGccZNNHsFB6jvloZ7aD1FVM5jatvs-6HPFv3aI_sz5OKGa8Bd3nH27rIhdKUW73GyTSwHwP7Fmirz-GOwkD9l0_Yb25ziipLVq_lOYvjUCbfcTfpavqf0BZ4BZl3v4ur1KsGoPTBHGajPSDrsYjpjWo_jjvI8ZKdNb2_mVKh6myj6yK-dyRVlL_6bcerkB4iiKCfAIlwcmr3bPhVCakrjWa4qgTg45cUUaRLXTA3DeUVvHaj1m1fseGgYCgBK4AwxQwI2vEq5pgQ-vgsaQZtzs7_UwKsbw8rlzOwWlLHGKrj39fPdyA==", "id": "rs_07cc2be4859e7741016a118658555881918b9564d7405da212", "summary": [] } ] }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/tests/test_free_production_jobs.py (952 chars result)", "tool_call_id": "call_D4PaeEUXE9JoYdZgExgO8YYC" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_jr6PcWhFYIrkxjo0WVfmz2o7", "call_id": "call_jr6PcWhFYIrkxjo0WVfmz2o7", "response_item_id": "fc_02d6cb1f4baf09f2016a118663ecfc8191a5a32d226affa8eb", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_free_production_jobs.py::test_mechanism_free_production_jobs_preserve_total_video_duration -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `pytest tests/test_free_production_jobs.py::test_mechanism_free_production_job...` -> exit 1, 1 lines output", "tool_call_id": "call_jr6PcWhFYIrkxjo0WVfmz2o7" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_G1cVRg3Bwjl8flbYkVlYJJu0", "call_id": "call_G1cVRg3Bwjl8flbYkVlYJJu0", "response_item_id": "fc_092d83855517ff98016a11866d73c08191be4cbf9e5518a5e6", "type": "function", "function": { "name": "patch", "arguments": "{\"new_string\": \"def _duration_seconds(item: dict[str, Any]) -> int | float:\\n seconds = int(item[\\\"duration_ms\\\"]) / 1000\\n if item.get(\\\"type\\\") in {\\\"cinematic_ai_video\\\", \\\"mechanism_animation\\\", \\\"kinetic_text_overlay...[truncated]\", \"old_string\": \"def _duration_seconds(item: dict[str, Any]) -> int:\\n return max(3, min(6, round(int(item[\\\"duration_ms\\\"]) / 1000)))\\n\", \"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/autoshorts/asset_plan.py\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Fixing asset_plan function**\n\nI need to adjust the asset_plan function because _duration_seconds is currently rounded and capped. I think preserving the exact values for hidden_money and mechanism style is essential. I also wonder if a function should accept an item only, potentially changing its signature with pillar.\n\nIf an item's type is either \"mechanism_animation,\" \"cinematic_ai_video,\" or \"kinetic_text_overlay,\" it should return the exact duration in seconds. Otherwise, it'll cap it. I need to make sure it can return both int and float, so I'll conduct tests to verify everything works smoothly.", "reasoning_content": "**Fixing asset_plan function**\n\nI need to adjust the asset_plan function because _duration_seconds is currently rounded and capped. I think preserving the exact values for hidden_money and mechanism style is essential. I also wonder if a function should accept an item only, potentially changing its signature with pillar.\n\nIf an item's type is either \"mechanism_animation,\" \"cinematic_ai_video,\" or \"kinetic_text_overlay,\" it should return the exact duration in seconds. Otherwise, it'll cap it. I need to make sure it can return both int and float, so I'll conduct tests to verify everything works smoothly.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYZt_SxC2yT7F4i72M-NvqKyGQl5vP3wvmnSbpleKEf3ucq69dnUS4t4RsJLfiys7BNgwptxCP_iUXXoObbgg_piT1cfnTMTkC0G9x7PYpIyNq0SpEDsltatqzrJfoW0S1l_51nutSb6edHX03mHdecmUZjPo-wkl78HvFrbDFjIZ72O4hZYxJeNeXRSNRNvC10sFJbeHyoTie_1chuLgU6rE9jXI4fD9lTrknlgH2F1y-OEdvSAZfQY3DrjtSV6l7Hlz49aWWgmY8j5ntmMKaQ4Bqlgzoe0s-0H7DWqmM3GbDDNq32VX-O_CsOL-KZROfuzVlqzYpOcRQUFw5kvXQgmvx_KlGrXC2UpI2n-dTpaARQPdh2JRXpst2H5TaLPSpjwaemFYkU6KBGlMUMj4tCYXfBvbtbOVy2l8Rw4UX4BtQyz7rmKQIScqbCS6dRnsfAYoegR9YWpaQq2O9-ETToU2bcOczo0Li96V_yBbdiNvLtU6t8XTiChfyTVg7A9-ehi9ThxqW_IrG1NSP3Rk1O5Azy4EvWmabLOqTs71nkBjCzEkadr19Py18BUSCcpdTziWZ4jmbXyR2nNvTrqatG9tWehbXgQhIjMzmmxDmq3aXaQLyDg5SOp1PiaVcx5UBv0MmuLixB_cn4o9vTLXy-L7755pbEmKnRtU6_3lHD2jrzIpV0KEjpeoDdKV8mF7p500ewopxpp0Dw4kVA3YV2WPoE7U1YkBjXuuPXmDwJ0pfxZUi7k2s9mp_MOu717koWmFCITV3c7iM5z3gEsImnhZar215_qEM2zqeUSwNI1pm6v3Dmt3Y6oZf8ldzRGXBUsj6cDmBT7f8WXtfajt2pB3kVHLxawMUXHUVDM54lxO-8mz1RoBl1of0JHi_jD5HatEmhZByf_IAWcTRbZMw-xJ3aVMWMlIQq94ZM9wI7_6sTeQh6YStLTha9MnJgPNBfLDExAdM2dvSmohyBkqivzhlP0Wq1TmFxw93vwwsdQIhJdj0GBmKlHsyWYo7hGy16uLIZ-nFLLX0tlHBySjq4XMgjMn0YCtNTg9p1Rr9F9MzAlj9I24ca4Vupqzoq_YiaDrOSKA_kgFV0Qa4Jf_PTHZwREJ--soRWPubI1N8P5D3SGKbL1FAnv-evdI3h53cYqXjlkPjVcVM-xF6B08QB0mbaadCESXivho1j-eX6UNUjnmPT73YsJ_azjWTzIggcT0Qvnom0-LKIuZLuiciALtPVd3blaWfmd3tO1kvCiczbpHG5zs65boEWGXFnYpOjFTLr23sOxruguQQ839J2fwOiwFCKOz88sATE_cIFMx374QQdkNVl9pmVZ7KxkD-RsfKfbib91mJaRU3nwL27vk3Bg1a_hDtDxcoq6fqIgMnXZ02gEQV1zkx885TQELhzTwdYdJFcUvHC2jY1WSQZVhheCQPiSlo0Ru_6UR6jqmOzJScHgMTD7GorXY43oIU3OPj6XwcYie0LUnTLLzY9mVQiXPLFr3dGiYlt-zPxKlkNT-CxeoRIiubjKoGNDbEuG5HyIDaO8E9n592aJm0CGXD7SEJHH1ra-9usR7eH9p0DuEEyu2yI33IU-iXsPeRGQ32pdBLA4q-W12SaDDZ0S1oT-PvNkiYsBrvepcNRhq5j_ZcCFvEUJvKAm4el3wp4Rs7VVr2Pt-JUsykGwfwgwVozY670dt65i_DRgFUcrIcq8x706MR3zcF-e1fs_rB7mlyrUc4litvD7dfEdqXPJ1YgRabqIX8u6jGtbZQWvx93OqT95XNKAb4SsE30oSAMZUBRJ1s-plmxNTFg1hvFYVE2_QHt4u5EAZBvNTHY80g5c5V8bU3o5lzCJOpVkr5jcH5Khs5OSNcvfgRYlmpK3igNVxpcFdXhssXddvsFQ9M_YjEzfaeJLybQf6W12nS_PQ_-Uehh8RhJRIzpmFwIXyxdOrTwekv_yQn95eIS4bY4=", "id": "rs_092d83855517ff98016a1186679ae08191b37d2f21bd7ffcf8", "summary": [ { "type": "summary_text", "text": "**Fixing asset_plan function**\n\nI need to adjust the asset_plan function because _duration_seconds is currently rounded and capped. I think preserving the exact values for hidden_money and mechanism style is essential. I also wonder if a function should accept an item only, potentially changing its signature with pillar.\n\nIf an item's type is either \"mechanism_animation,\" \"cinematic_ai_video,\" or \"kinetic_text_overlay,\" it should return the exact duration in seconds. Otherwise, it'll cap it. I need to make sure it can return both int and float, so I'll conduct tests to verify everything works smoothly." } ] } ] }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/autoshorts/asset_plan.py (940 chars result)", "tool_call_id": "call_G1cVRg3Bwjl8flbYkVlYJJu0" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_kqGoW9yBX3oqQgtmwOayz3Yy", "call_id": "call_kqGoW9yBX3oqQgtmwOayz3Yy", "response_item_id": "fc_0979536b5e11d800016a1186736b888191883090833bd172dd", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"python scripts/generate_asset_plans.py --manifest data/render_manifests/mechanism_pilots --out data/asset_plans/mechanism_pilots && python scripts/generate_free_production_jobs.py --asset-plan data/as...[truncated]\", \"timeout\": 180, \"workdir\": \"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `python scripts/generate_asset_plans.py --manifest data/render_manifests/mecha...` -> exit 0, 1 lines output", "tool_call_id": "call_kqGoW9yBX3oqQgtmwOayz3Yy" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_9pP1WbOZqMS7IXWMnNMAw7lr", "call_id": "call_9pP1WbOZqMS7IXWMnNMAw7lr", "response_item_id": "fc_0b0a580d46e9cd16016a11867d96288191af8314659054a500", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python scripts/render_free_local_motion.py --jobs data/free_production_jobs/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json --out-dir data/local_motion_renders/mechanism_pilots --width 540 --height 960 --fps 15\",\"timeout\":600,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Calculating test duration**\n\nI need a local test now, and I expect the duration to be 34 seconds since the JSON has been updated, which is good. I should render the actual pilot and maybe use a resolution of 540x960 at 12 fps to save some processing time. The script defaults to 24 fps, which would mean 816 frames for 34 seconds, but I want to keep it under 600 frames. Setting it to 15 fps seems decent, and I need to produce an MP4.", "reasoning_content": "**Calculating test duration**\n\nI need a local test now, and I expect the duration to be 34 seconds since the JSON has been updated, which is good. I should render the actual pilot and maybe use a resolution of 540x960 at 12 fps to save some processing time. The script defaults to 24 fps, which would mean 816 frames for 34 seconds, but I want to keep it under 600 frames. Setting it to 15 fps seems decent, and I need to produce an MP4.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYZ9Bl5QPXvdV0_xnC-28qPhesmDoCbaDVzETvlnR0B_1yUkkQfHSt5f3rl1EFq99vRHK168oR1Bhe5nXU6SEo5HRv7hM3coAXr7WArleoZF6LB1S6AZyHslVk9skyr_HFwjPPOWMSJVVbQQTK1zYapFB1xJ7c7g7SSYTOy040i10fc-N3Ybfl0fc2LdGJLAz_sXupp_cZ7uSToOcv2leVL9PeV1v3YxNPWtNfwFnLMcCWWbADRiwsJcU0cdju0pz7sQM5RDgPhaG-F8SPYnlEZUVFbZAcyuFLTTFtAprRxZLrQKmucYWGCjySWgRO3rkobKvln5I2GZNiDl8qYGqGlmL6I7oWVJrn8rKeQ1b4tJcVuTjr00PcQZrpPlB_P0ttmnGQs0n6L3ZgnWP_Oe5lu0oa0ceuepJYg3UZL9nmiL6HzROVoJAGETzKcgVTYGUJZCdKyjDRPzlSm7qiMrilomiUyA4CJ4SgLDbXAQCFF8z9PKHX9XQ8bPv7nf8ZKgRxGy4DBe-Rru3hrB6ZTPIcpSUrnFzwwD71knkyMXaBh2lsVKK-KoXQgI_R58eU4Lwhk_8ci692yKNvISBq-9u9pVw48SkFL-PHKCvottm4IHPoG00G_IYCI-TK8LQ-irnATP1XyH-EsqtPDROGJ_GTvXDAdmvRoua81RN4u39fTTwnq6T8aMAiCh9viBrm-xw_Iexx6RlYAsPhJcBlWrQBEOFpxpTWpcC4XkGMAGAT-xGJSn0_BtD2Ko0WQBz0tPuCTxMC5_QxvEXxE8LLekncGXvJpejkgiftyBBLsPzMseGCsc1Rub4-7_lO_V3p_O0UldzO1TSVGeMQsO-zjia5GEUC4zUsmtxSOPJVIJ1-pf8X3IwRwPXJ8l6WSrCrt-TX1uGmmZI0RvZ-p2yzFmckt-AMhMhzfyxdGnXzpE51P4a0wC4e8dS0WZJEx2GvHvwpBoavbD47OSHXehStxzVKgNqFR1Yx631GkAxs313Fn_VcQnyJ0xfYV4BZ3vRTlRfWD_LWUSjzYnyqEQ2lR2vd5Hw7hlzIIcbefl-q2pTv__rX2K4siuXnLSoU9lEjNELeY1gRkg_fsDug67Z-XW6thPlw9vKI3Rh9YOh32qUzdDrtMMZPy42Kynt68uBrGeyNITJKCMpNJ0JDLGtc2BgimxMHRrxfjyeQR-vvJocq8BGBuLx8HCzAC26OYVTIb4-jmyOg9lJ4XT6Gha8aX5PN50TQ==", "id": "rs_0b0a580d46e9cd16016a11867a55308191ad7ef6dcab28ef2b", "summary": [ { "type": "summary_text", "text": "**Calculating test duration**\n\nI need a local test now, and I expect the duration to be 34 seconds since the JSON has been updated, which is good. I should render the actual pilot and maybe use a resolution of 540x960 at 12 fps to save some processing time. The script defaults to 24 fps, which would mean 816 frames for 34 seconds, but I want to keep it under 600 frames. Setting it to 15 fps seems decent, and I need to produce an MP4." } ] } ] }, { "role": "tool", "content": "[Duplicate tool output — same content as a more recent call]", "tool_call_id": "call_9pP1WbOZqMS7IXWMnNMAw7lr" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_q0ww5wrvrGuzdlzrtiOEa2Ze", "call_id": "call_q0ww5wrvrGuzdlzrtiOEa2Ze", "response_item_id": "fc_0b044a14a2d9b52e016a118693dd1081919a4c32a39b14f661", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } }, { "id": "call_pRX8LGtykUd8OGq9bUXPgAVv", "call_id": "call_pRX8LGtykUd8OGq9bUXPgAVv", "response_item_id": "fc_0b044a14a2d9b52e016a118693dd248191a8dbce0067f1b37f", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"ffprobe -v error -select_streams v:0 -show_entries stream=width,height,avg_frame_rate,duration -of default=nw=1:nk=1 data/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.mp4\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } }, { "id": "call_sAUcAqhDkFhO2qcPJa3sO3Ee", "call_id": "call_sAUcAqhDkFhO2qcPJa3sO3Ee", "response_item_id": "fc_0b044a14a2d9b52e016a118693dd2c81918ed116eeae535a7d", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":160,\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/data/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Verifying media with tools**\n\nI need to check the media details using ffprobe. I should run some full tests. It might be a good idea to grab a screenshot as well, possibly using vision tools. Then, I think I should also run a git status command to see the current state of the repository. It's all about being thorough and making sure everything is in order before moving forward!", "reasoning_content": "**Verifying media with tools**\n\nI need to check the media details using ffprobe. I should run some full tests. It might be a good idea to grab a screenshot as well, possibly using vision tools. Then, I think I should also run a git status command to see the current state of the repository. It's all about being thorough and making sure everything is in order before moving forward!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYaR8Tnk4geI73pOLldmhn8wMUpbTF-uL7Cr6e5O9bbkLeGEQbKfnQxMlpjksI35yJNPWIFGgA3ZhgZWdKfdeNew0gG1z7ajnwM0isRJLTm5hRWAkwkaxpZfSNYVJpovojuSYxM_7vAAnUoGQqOkky-ga9Pomci4OI07NYdeY5L_j-dap0VImmdVkTAi25aL2VZytSJqvUiVM8QvhewfK0y_n3-kohlt5JMNUntTw-9B09NxD_eEzulyC6zDnH4-KrNOakCfqUZ5UBgPUHmzqXH8HciT-5scr_K-wrDoGC4mKnuHDcUvcdsrDiP-RLPVJ6YLBMWsXfpWNYz1LCbYOnPhsi3YlSGlCIUq4DWOrbLwhoR0v2RAXQqKUBu32Bav8WzqFy8saqUkBVijnwj1eq8ClcVH_-sOJJCwdaIapB1xHhoEmSH8Z680LGbmijTQv_Lois3oohmibIqU8w8yMLMft0HOgKSfiqPONhVwuUj-e-6WeFKfw2mWr9hjENr-XO1khF3WxQEIxftjq7biAtBUnJsp8dE_X3PuXllYIB2c6AlinzyBCr6Wm8UZVawo3a43MvritgZ_AVj3DmfEW1nTrPfUvV0B3GAsZWekWBP_SwCuaVHl45Pd_71uSWuEk_tjGMjcXAE_o4yuHpB80fogOpwtoLtLmH4-E5bl0Gm0oZQMPTl_0BSkiknJToIf5XZtfBpQ6oCvE5gRBtG9zxQivgq40j4GY7ROD9aYmOVFMbGh30XVjtO8T7Dmw5OIRr2aAMNlzEjJexp09V5RM92eK9Q0PdwCSAVlcytqmKPVsLlS7udSQwh8kLy_E2Y3Ok9-kyhmbIFs5B9R2xCzSQQnYoh0Vd4E2-2pR1hxfR-MqzjxQp_CP--sYkvomu3sH1TfporEitCtTPAfI8e6PMEOd-3ZxuFj8ZBW8nBFw1C1c_S1iqV7P1bsque0MBwq1kWroFLYs6CdNS6dW3JjVS49lhD5WX6pkwI4-jLmxqDHh0houbAZgSXjWF8XJ53IZIwbv8TTFfD2vOoNZ88QNegqemsqrVKovUfYpAhhzRxzdgM=", "id": "rs_0b044a14a2d9b52e016a11868f132c8191854bf05734b54ab0", "summary": [ { "type": "summary_text", "text": "**Verifying media with tools**\n\nI need to check the media details using ffprobe. I should run some full tests. It might be a good idea to grab a screenshot as well, possibly using vision tools. Then, I think I should also run a git status command to see the current state of the repository. It's all about being thorough and making sure everything is in order before moving forward!" } ] } ] }, { "role": "tool", "content": "{\"output\": \"................................................. [100%]\\n49 passed in 2.19s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_q0ww5wrvrGuzdlzrtiOEa2Ze" }, { "role": "tool", "content": "{\"output\": \"540\\n960\\n15/1\\n34.000000\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_pRX8LGtykUd8OGq9bUXPgAVv" }, { "role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/AutoShortsBot/data/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json from line 1 (5,056 chars)", "tool_call_id": "call_sAUcAqhDkFhO2qcPJa3sO3Ee" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_YDTqczetVVWUe2HOly4k4mzw", "call_id": "call_YDTqczetVVWUe2HOly4k4mzw", "response_item_id": "fc_073d3259c9bafaa2016a11869de1148191af4bc76f50452bcb", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"mkdir -p /tmp/autoshorts_preview_check && ffmpeg -y -ss 00:00:08 -i data/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.mp4 -frames:v 1 /tmp/autoshorts_preview_check/frame_8s.jpg >/dev/null 2>&1 && file /tmp/autoshorts_preview_check/frame_8s.jpg\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering screenshot extraction**\n\nI need to create a vision preview screenshot. To do this, I might use the terminal to extract a frame. It seems like using ffmpeg could be a good choice for generating the screenshot and working with vision. I’m making sure I have the right approach, since it's important to capture the frame correctly. So, let’s see how it all comes together!", "reasoning_content": "**Considering screenshot extraction**\n\nI need to create a vision preview screenshot. To do this, I might use the terminal to extract a frame. It seems like using ffmpeg could be a good choice for generating the screenshot and working with vision. I’m making sure I have the right approach, since it's important to capture the frame correctly. So, let’s see how it all comes together!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYad5L-aqYX3wMchb8BlWHg9WwkbiR_I0iEG3OBFI-oyHDQVbTw50Izm9m7U-hUmU8XLs6jbsdDKF_Of1jKe1j_gLpDxvB51FlyJtZ2fR6IgsqkRMy8_SMmtFFgEqa591ZwuDKHj-KFo1RTExGmuGUWSjQ0Lk-jbaOiRq8vphk4xZ-7a6YEW8Q5UyfJxe8cVRZYetT9LHzNP9q9nF1WnrcBzpLsH_O4_6FHfgPh7v-7G5ZCuIGrICuscyTob8_lOaziurpNwOD2NjU54D2kA_SnsyeK8CtA-SrFbDB-758f2P1n8D5NBOP4SGP3D8SLOUhkBePFBHGtMHisTWE1sk2Jkt73CGHZMKhif4SoGzkABrRD4ZHS1kHbkZs0eOPa_aRRDkXttnO0xF_pmJxRIqaqBwJJAU3zgn1VD33-ZwN4KJ8Eb8zX2qYxWonhLU7O56kSFTucD6qqIkx2zIJowPqg9ueUXKpHkCwn1_90uqEUkLZcfRDHs7veQQSPuoPWYXsGXZap6tzon69SCmQI4AMRB8COSq-XRYYSabzvSfE81OeJuE6gv0YXSge_ZYBENMye_qo1YW34l5BIolAogUwUsSKxynXsg4300_xOgb58IVv9Le04GrhbtIsPNoaPSZUl_ywOmuQnHC2SHzScbE4yvAv1Y31HPcXqi75t3Yuwq4t_E8w30LkYqjYwxd44JTncH3wxLVi-2X5VPgIN2CV10zu7LKBza0fGh1c-KAGrvuOYOuslSotXPlFLU3U1oF0m3t-md9oxnbtPUa9ayx_ZHqRpKIzt2i5Bvy136vto9hduuU3YpHRkXrEt8XqEMAUzrS3CoRpfoX9DkpkGeWmyE9a38g-LPkv1rf1JfhWikvClHVWH4XD0NtIQfKfRiD0691Rwuuf6UuVf_WgX5juCiUAeFCw3ps-fc099FZ3n_-RQohsCLl_CovwVwAbe0anHuPsV65b8_cjqt5fknRIx9NTNxFekfOCyJDuEFyZP9o4jRQF5TGMkrdGdRNxbrZpHmEuOsUrv1QpkzK9KslUKCKUYjxYZ1utexUnEh3g1kyrJ9MFhi-n7lk9BCrmI6jT4q", "id": "rs_073d3259c9bafaa2016a11869bafcc819181015d5f726985eb", "summary": [ { "type": "summary_text", "text": "**Considering screenshot extraction**\n\nI need to create a vision preview screenshot. To do this, I might use the terminal to extract a frame. It seems like using ffmpeg could be a good choice for generating the screenshot and working with vision. I’m making sure I have the right approach, since it's important to capture the frame correctly. So, let’s see how it all comes together!" } ] } ] }, { "role": "tool", "content": "{\"output\": \"/tmp/autoshorts_preview_check/frame_8s.jpg: JPEG image data, baseline, precision 8, 540x960, components 3\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_YDTqczetVVWUe2HOly4k4mzw" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_9gfOBsYgBQVCB8SZIQiOL0Uz", "call_id": "call_9gfOBsYgBQVCB8SZIQiOL0Uz", "response_item_id": "fc_055f1fa8c47384a3016a1186a0c44881919bb119d249484d66", "type": "function", "function": { "name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/autoshorts_preview_check/frame_8s.jpg\",\"question\":\"Kurz prüfen: Ist dies ein vertikaler Mechanism-Explainer-Frame mit sichtbaren animierten/layerartigen Elementen und lesbarer Caption? 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"id": "rs_075311f2fb8b3d42016a1186a4d2388191a8eaa42a7de99738", "summary": [] } ] }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/tests/test_local_motion_renderer.py (1,014 chars result)", "tool_call_id": "call_KdXU1ITo9togoMCz95KZhD55" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_pEbh8Pipl79A6qzOglhwCxet", "call_id": "call_pEbh8Pipl79A6qzOglhwCxet", "response_item_id": "fc_0e5638e2b7649a65016a1186addad8819181d5da808f2dfc28", "type": "function", "function": { "name": "patch", "arguments": "{\"new_string\": \"def test_caption_layout_keeps_long_german_lines_inside_safe_area():\\n layout = _caption_layout(\\n \\\"Röntgenblick durch Preis, Reparaturrisiko, Standtage, Händler-Marge und Liquidität.\\\",\\n ...[truncated]\", \"old_string\": \"def test_local_render_jobs_filters_out_text_only_nvidia_refinement_jobs():\\n\", \"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/tests/test_local_motion_renderer.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/tests/test_local_motion_renderer.py (1,020 chars result)", "tool_call_id": "call_pEbh8Pipl79A6qzOglhwCxet" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_7zcciHADsAI8rJXKkteegyJs", "call_id": "call_7zcciHADsAI8rJXKkteegyJs", "response_item_id": "fc_00b06af645999e0f016a1186b72428819181e441b4b0a5ae79", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_local_motion_renderer.py::test_caption_layout_keeps_long_german_lines_inside_safe_area -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `pytest tests/test_local_motion_renderer.py::test_caption_layout_keeps_long_ge...` -> exit 4, 1 lines output", "tool_call_id": "call_7zcciHADsAI8rJXKkteegyJs" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_yafiiOEuhmwjbteqFWFXsLmU", "call_id": "call_yafiiOEuhmwjbteqFWFXsLmU", "response_item_id": "fc_09434e827969d7ef016a1186bcb8fc8191b2e3768b9e270a09", "type": "function", "function": { "name": "patch", "arguments": "{\"old_string\": \"def _draw_caption(draw: ImageDraw.ImageDraw, text: str, width: int, height: int, accent: tuple[int, int, int], pulse: float) -> None:\\n size = max(22, round(width * (0.062 + 0.014 * pulse)))\\n fon...[truncated]\", \"new_string\": \"def _caption_layout(text: str, width: int, height: int, pulse: float) -> dict[str, Any]:\\n \\\"\\\"\\\"Calculate a caption layout that stays inside the vertical safe area.\\\"\\\"\\\"\\n text_max_width = round(width...[truncated]\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Implementing caption layout**\n\nI'm thinking that I need to implement _caption_layout and replace _draw_caption. This sounds like a straightforward task, but I'll need to make sure that the new layout aligns well with the overall design. I want to ensure that everything looks cohesive, so I may have to test it out first. I wonder if there are any edge cases I should consider. Let's see how this goes!", "reasoning_content": "**Implementing caption layout**\n\nI'm thinking that I need to implement _caption_layout and replace _draw_caption. This sounds like a straightforward task, but I'll need to make sure that the new layout aligns well with the overall design. I want to ensure that everything looks cohesive, so I may have to test it out first. I wonder if there are any edge cases I should consider. 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This sounds like a straightforward task, but I'll need to make sure that the new layout aligns well with the overall design. I want to ensure that everything looks cohesive, so I may have to test it out first. I wonder if there are any edge cases I should consider. Let's see how this goes!" } ] } ] }, { "role": "tool", "content": "{\"error\": \"path required\"}", "tool_call_id": "call_yafiiOEuhmwjbteqFWFXsLmU" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_gwZ2UiFKGxVo3kgTWluFzM8N", "call_id": "call_gwZ2UiFKGxVo3kgTWluFzM8N", "response_item_id": "fc_08c88ea2a01708bd016a1186d805a08191b2771d52a9b8b019", "type": "function", "function": { "name": "patch", "arguments": "{\"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/autoshorts/local_motion_renderer.py\", \"new_string\": \"def _caption_layout(text: str, width: int, height: int, pulse: float) -> dict[str, Any]:\\n \\\"\\\"\\\"Calculate a caption layout that stays inside the vertical safe area.\\\"\\\"\\\"\\n text_max_width = round(width...[truncated]\", \"old_string\": \"def _draw_caption(draw: ImageDraw.ImageDraw, text: str, width: int, height: int, accent: tuple[int, int, int], pulse: float) -> None:\\n size = max(22, round(width * (0.062 + 0.014 * pulse)))\\n fon...[truncated]\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYbYQNgupSa9Jw5s1OvoaNPAV61gCqL00ClRZEMcgprXxypqeWqUNtR0kZaV5o4vDMrVmS3ZkCgRNk9_4_KJLbJbrUWejYNPv3qx22gIfLV77I61-ztdAS8x4bsLLw8mbLCaYm8ZLlnNlotflRIHGXeYim-zH2_32Y32TytLGM-eom1cTCOhHABwOuLmwMqk7DuAwGtJKbpfuflCPZZVRbRgb1zcy-rI_4nJnOIuO9mqKgvCSv0TWiyCabfgCYIRgp6lCqF0f33wLWURg1g0i9rCE1DL8A3ya0SH3RIsYaYol3bPi_eDkvNcbodlyBYynn6Bze0t2KzYapobMFORaq5XgiQ7HBNfv1M96p1eCsNMvhLjMnoUMywxtwztfOZfDFgXp4_X3MmLi3-HEZGUN5rzdnDLCzgBMQDWBMP8aXKOBf7SCaNMMlE03M35I5wx6PRR2XhrkTZOHC2xkQnQOiUJOb0R6z6w5nQw1uDsid-DTutoJBoMSfykWhQZeQEtNvk1uVRvo2NFpNsfqC7ZqECkoa3G89SexljS7ziB2Qd4QG_X65Uwv47d4kn6vJeI8vJvTN-QaejvGAChNXoq3EYzk_xsnkCEte9AZeyZQDd5BdU4t-iczudyC0c3AEZMTeZRj3rIcSpR5jKtciR-63Wii0L0hgEKNXXtYrxg3ToBpJ5OXTgUuVfEBWKFFHpxmrW_mAO_vkDARf9IKDp8AauscMwTdAjoZb9IQkBjWimwIDblIqgiWqZYF3LUtXohMd_eDmCt6af8ZLHvZTR6_61GlZNkkDv7siVzM_yCt1_zhB21s5LkvOOTx4Fj6uXOeVXE_VWVEE2-lXoDs61Fxs4JPb_AIIFTBZ39gLnvlWfA8cTmHVzseIadVRHnDQyJcM26gniM_AiYxQSM-XH-hHs26WYVze0yN_qerph5AOijaaU=", "id": "rs_08c88ea2a01708bd016a1186d7662c8191b6a20f5e0e4ef3ca", "summary": [] } ] }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/autoshorts/local_motion_renderer.py (5,038 chars result)", "tool_call_id": "call_gwZ2UiFKGxVo3kgTWluFzM8N" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_qDXLPUURAe9YB2DyA37eR9IY", "call_id": "call_qDXLPUURAe9YB2DyA37eR9IY", "response_item_id": "fc_0c2900c6bc47b1d4016a1186f6686c819185cda5d97f00a45b", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_local_motion_renderer.py -q\",\"timeout\":180,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `pytest tests/test_local_motion_renderer.py -q` -> exit 1, 1 lines output", "tool_call_id": "call_qDXLPUURAe9YB2DyA37eR9IY" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_T3O5XbbSpVhdlS6kFJb9ByFB", "call_id": "call_T3O5XbbSpVhdlS6kFJb9ByFB", "response_item_id": "fc_0efb1829cb98b433016a1186fd661c8191b26a42808793eaf2", "type": "function", "function": { "name": "patch", "arguments": "{\"new_string\": \" font = _font(min_size, bold=True)\\n line = text\\n suffix = \\\"…\\\" if len(text) > 1 else \\\"\\\"\\n while line:\\n candidate = line.rstrip() + suffix\\n box = draw.textbbox((0, 0), candidate...[truncated]\", \"old_string\": \" font = _font(min_size, bold=True)\\n line = text[:42].rstrip() + (\\\"…\\\" if len(text) > 42 else \\\"\\\")\\n box = draw.textbbox((0, 0), line, font=font)\\n return {\\n \\\"font\\\": font,\\n \\\"font_...[truncated]\", \"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/autoshorts/local_motion_renderer.py\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Truncating fallback line**\n\nI'm realizing that the fallback line is too long. 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I need to make sure it fits, so I'll have to truncate it. To do this efficiently, I’ll implement a helper function that uses a loop until it meets the desired length. There’s probably a clean way to handle this! I want to ensure it works well to avoid any errors or issues that could arise. Alright, let's get started on making that helper!" } ] } ] }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/autoshorts/local_motion_renderer.py (1,427 chars result)", "tool_call_id": "call_T3O5XbbSpVhdlS6kFJb9ByFB" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_33WaXUX9J1QyJKj0NyCqN4fy", "call_id": "call_33WaXUX9J1QyJKj0NyCqN4fy", "response_item_id": "fc_0fc4be2aa452dede016a118705d5348191b060516611045231", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_local_motion_renderer.py -q\",\"timeout\":180,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"output\": \"... 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Maybe I should set the caption to display fully at 540 instead of truncating it. If the layout doesn’t fit, there might be issues with the lines. It seems like I could tweak it to improve the overall presentation. I’ll go ahead and try rendering it again with these modifications in mind!" } ] } ] }, { "role": "tool", "content": "[terminal] ran `python scripts/render_free_local_motion.py --jobs data/free_production_jobs/m...` -> exit 0, 1 lines output", "tool_call_id": "call_ABxRk3qybitSCcTVNjo9ga9Y" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_FMUDPBvHNxqy0HAlB72rLqTP", "call_id": "call_FMUDPBvHNxqy0HAlB72rLqTP", "response_item_id": "fc_09af77c0cfefed21016a11872423d48191b4a7c151d5be365d", "type": "function", "function": { "name": "vision_analyze", "arguments": "{\"image_url\":\"/tmp/autoshorts_preview_check/frame_8s_fixed.jpg\",\"question\":\"Prüfe den gerenderten Frame nach dem Caption-Fix: Ist die Caption vollständig innerhalb des weißen Kastens und des Bildes? Sind Mechanism-Layer/Auto erkennbar? Kurze Qualitätsdiagnose.\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[vision_analyze] 'Prüfe den gerenderten Frame nach dem Caption-Fix: ' (315 chars)", "tool_call_id": "call_FMUDPBvHNxqy0HAlB72rLqTP" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_83FgQEDBjnzlqQP8RPi0iyCz", "call_id": "call_83FgQEDBjnzlqQP8RPi0iyCz", "response_item_id": "fc_090ee1156d1af73a016a118729e3d881918815a7a564e5fe9f", "type": "function", "function": { "name": "search_files", "arguments": "{\"pattern\":\"Röntgenblick\",\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot\",\"target\":\"content\",\"limit\":20,\"file_glob\":\"*.json\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": 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I’ll need to figure out how to fix it. Maybe using voiceover could be a good alternative? It's important to address this so that everything displays properly. I'll start by inspecting the details and see what adjustments I can make to resolve the problem. Let's get this sorted out!" } ] } ] }, { "role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/AutoShortsBot/autoshorts/mechanism_pipeline.py from line 1 (6,358 chars)", "tool_call_id": "call_Il4P6jg3BXtTHz3wwFFM9r4w" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_86qZuMd3nFXCG9wOfAzAyQOm", "call_id": "call_86qZuMd3nFXCG9wOfAzAyQOm", "response_item_id": "fc_023daa51548d6826016a11896702c881919fac603972503fc0", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":220,\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/tests/test_mechanism_pipeline.py\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Improving text truncation**\n\nI'm realizing that the text often clips at 72 characters, and it ends awkwardly with \"und.\" To fix this, I think adding an ellipsis could help. We want the renderer overlay to be concise, but it shouldn't dangle at the end. So, I'll test adding a mechanism to ensure it includes an ellipsis when truncated, avoiding stopwords like \"und.\" I also need to make sure \"Liquidität\" is still included. Maybe I should add a test in the test mechanism pipeline for this.", "reasoning_content": "**Improving text truncation**\n\nI'm realizing that the text often clips at 72 characters, and it ends awkwardly with \"und.\" To fix this, I think adding an ellipsis could help. We want the renderer overlay to be concise, but it shouldn't dangle at the end. So, I'll test adding a mechanism to ensure it includes an ellipsis when truncated, avoiding stopwords like \"und.\" I also need to make sure \"Liquidität\" is still included. Maybe I should add a test in the test mechanism pipeline for this.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYlnygGZDPzbSZ7OD_yyB16hy2K8AbfYVJdLw49kyOtlrJXQd1O3wu5DPfm-zmAQAA2mTrqWAahfl0r1ZS3525R_O0Io4xT4ktjc5KsAX9MhgPfmjPxeyH1zPfl2qj-hI-lW1nZ5Waq_CqEXeVu39D2pUGeTj0HQm9rPaO5fqjKdvgnxPx-PSAtUOmFucvcAjAixBHoPy4rvnTmSbxkIW-cS1_Mof7gHrHB_2Ub-ZdoVzkdlb8k-iP-4Xc4C9vfV83A-MVsQkG3l-vxAPh37CNtKHhOPmDdGC6A4ymfJNT8MR7HTPhap0UnSh5bWlto1lu_gWb3WDFSR8VxIVOrvxzLlzXcAm2Nqjr6XH5kY8GQggvBmR9l8i0jAQ-cSx7fuRg64Gff3QfHi9v-Zbqf377JVT9aAUZPg5HKrahfavO5oO4likiNPX4Ubz4UCb1FPjS30EuVMQvZcSH1doFRDg6OQPhMrU7Rui8B7F_uXr8TuBYlfxWPtDLzatIBpDKVEZEkE0c7Bm6ME_f48sUDWvvbLaXQBTKtukgbav8E87FDFD6ZzjfILakP5c8DDen1SXC1U7EoSo4pHlvu5TB9s7jlvmYt3IrMRePrCmbXOBxmv4Ab2HTlcZ3zrhqerCXHINUvGiWBDHqOE3VoXdp9VeoXfr9lu9qVXf9QJ-oJhCWAQdTs5dFcuVVht0BUh2AZXQkeDlJwz9WL0tY5wM6ypFzt5ZiXm82IJc2l29zWBxx8FFwOtMgpuqKk3wOkbsuiq1r6cT9ADWFtU7iIcQGnyddFMsEpLutvj8RgwSUWAy7SQbfhQCtTEKfXm0CwIpYLBr_mkP-Z5iT6Dw3BBUUyCzOdf9P0ceje31fNJ50QYt0yPYCNFHdh9CvMU_mbn16_YgSe6W3dfx7jA1Y62cnDJDRl0hBrdntgbFnLwcQFFA7bo8AV4ui8aJ85-39qmqfBfsHGQHKDwEMkyJTe0iiYMLNzB2VidgJa8IN2f9mgvaIbGxq6yfwX_YD9WfOFIsbjUGbxllJh7A33ogT4UqnpPnnaYY9fSZwX4sQ2bRViCRImaGb-ub0UqadDK-t4Z_VQKhYYBG8uBDWK43-a4mS-xKjTBNQewUnPE-kDruqZ9oAnjrWiecEQyuwEbHc_Yd8_mqotiNr_RDFz6PicTB6j0iwvVD2q3OB7sF8Ep41jXnEVhH5l8HiZm5SIPPC-II-d-iQzaVQfJioijsV479a0X9oBntHx6hyGfE637ipYk_MzMbb9VVH3DvWHJsdSuWmOY_5gJgpZ5EY9McLiC9qujGJZOf4bICyJDbVX_AgtSxSX6T-uYEZwuOTMbT_P8EgLpfpLww3-BSQJeeihr_rulNGN3S_9W4LHKXe40fw35rgueFVjas1V5upWmyU-pUoh81fmiqGIu1Gu1-jb_4V-CFisZ9Dz1vqQr9ihoEpjm331aF9FlYOigxCQVjZlAtI0ZpNW09b7BNVNwPoQIBYvNast8OKKxfUSlwf80s-Xm4-DtGtXqBBfqClfPxgzzxwLg2r-4rvZxByRvfb0PG-CJU9JI2UqxcQicXWy_mLPDG0vk1vR-b5E2IUnayllAO_9B_KkiR5OWTAQHmM1yZhohojmiTtntCBvj8X6xPk-F1AvOVRafOWKouruV1wMRyuv-qM28-PHnigm8aZT2VHCT_aTN-hXHP8_YAiVLM1Zl8zPsU4E=", "id": "rs_023daa51548d6826016a11896263bc8191bfd81fdcde4ee833", "summary": [ { "type": "summary_text", "text": "**Improving text truncation**\n\nI'm realizing that the text often clips at 72 characters, and it ends awkwardly with \"und.\" To fix this, I think adding an ellipsis could help. We want the renderer overlay to be concise, but it shouldn't dangle at the end. So, I'll test adding a mechanism to ensure it includes an ellipsis when truncated, avoiding stopwords like \"und.\" I also need to make sure \"Liquidität\" is still included. Maybe I should add a test in the test mechanism pipeline for this." } ] } ] }, { "role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/AutoShortsBot/tests/test_mechanism_pipeline.py from line 1 (3,226 chars)", "tool_call_id": "call_86qZuMd3nFXCG9wOfAzAyQOm" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_GhFAkX57sVEHOfhZJaYvWiIB", "call_id": "call_GhFAkX57sVEHOfhZJaYvWiIB", "response_item_id": "fc_00ecf5534a2032ac016a11896c99888191b70a39129fa81fab", "type": "function", "function": { "name": "patch", "arguments": "{\"new_string\": \"def test_mechanism_scene_overlay_truncation_marks_open_sentence():\\n plan = build_mechanism_shot_plan(_auto_explainer())\\n overlay = plan[\\\"scenes\\\"][2][\\\"on_screen_text\\\"]\\n\\n assert overlay.endswit...[truncated]\", \"old_string\": \"def test_write_mechanism_shot_plans_outputs_markdown(tmp_path):\\n\", \"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/tests/test_mechanism_pipeline.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/tests/test_mechanism_pipeline.py (810 chars result)", "tool_call_id": "call_GhFAkX57sVEHOfhZJaYvWiIB" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_I265trRh0GnliXZaFI23foLZ", "call_id": "call_I265trRh0GnliXZaFI23foLZ", "response_item_id": "fc_07dc20f6c5cb3bbd016a118973d2f081919ca8163bbb4a06d8", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_mechanism_pipeline.py::test_mechanism_scene_overlay_truncation_marks_open_sentence -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `pytest tests/test_mechanism_pipeline.py::test_mechanism_scene_overlay_truncat...` -> exit 1, 1 lines output", "tool_call_id": "call_I265trRh0GnliXZaFI23foLZ" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_udM2mxAp2KW0WWlUMZP3Sj2A", "call_id": "call_udM2mxAp2KW0WWlUMZP3Sj2A", "response_item_id": "fc_0fb308f2a387872e016a118978b5f481918841d7a77aed8a4a", "type": "function", "function": { "name": "patch", "arguments": "{\"new_string\": \"def _overlay_text(voiceover: str, limit: int = 72) -> str:\\n cleaned = \\\" \\\".join(voiceover.split())\\n if len(cleaned) <= limit:\\n return cleaned\\n truncated = cleaned[: limit - 1].rsplit(\\\" ...[truncated]\", \"old_string\": \"def _overlay_text(voiceover: str, limit: int = 72) -> str:\\n cleaned = \\\" \\\".join(voiceover.split())\\n if len(cleaned) <= limit:\\n return cleaned\\n return cleaned[:limit].rsplit(\\\" \\\", 1)[0].r...[truncated]\", \"path\": \"/home/agent/jarvis_runtime/AutoShortsBot/autoshorts/mechanism_pipeline.py\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYl45MLnMvEH5x4GewV0sOkaLSVtLaeUhD1_4r4C65am7j0sxEhcm6yySRf6tr512WlrYISZlycZK89y714QhLuKIjYmNJgzvsAy7h7viWu2EBb7HrJUJ46NQ0-_9PzrLr1vociA1_7gV5grTX8Q91itXIJ0uxcE8psgV_1fUALNZLDKCDpwwH-utDGti9Om4Xk_veJrGcaiupee23ynZ7OTKfCynvzs9ew0XWRJTVnm1jHWqZ8K-rjUZNIxvDVRXJThxsSyldMZykLdfdj91lVqBF76ZPxER_bAOWURTyGYJwAYmI1Cj6mqGyfAD5uudqZmmEVNybQ3lXzX77bt4apRNM5uGJ9WT4q_4PMMfvR8BrxNBm-6S_jOdM1MqIyorXVZwTsSrSrDHwc5p7iLXAYoDT6q9k7eBmdpWrfa6oC0NkcmhdcsFQKcJB9rRl2iyFD-3pC78gFyAjuupNRVaxbXoFKzHCPqE5ocPL2FpkfbOHq_DtyGiWMXis2srauOqkolM5j0z4FeiDbe0CcHulg-yPlV4SshKMmkWlMC9-1LB_lUojAmJdOk-PwWsMY_diPw1UZbe5zoOz64pR47YARo0HZcPnpLQiYkIO2OmxpNShLgFQZTK7MBOTo3X8k5h_sSoKu5eNM9de7g2-haGfhqgrEWYYsRyERsB7OHqYJba8J3HRRam3veGSAcSziGWSFQJdc0tqwDi4EHim3Ly_fyg8q1_CHJrzlN0z9TERR9v9jh8a8dlsS1uawzAqeCieP-2_x6Sm3ZVHAQ8p0ShRWTxFaO_Ap6qUBXV66n_1GPdOesTvcCMQGFzLBAqxzJPcUkem0_VZGc10d7dIGPoYEolmpEltWKABrteJVIKWTWqz1kmx_h8HNfjfFanDZh8LTMQj4DFZTQGSfJzPw6oKdV9vwR9y4MOBXLlFA62VJ1w14=", "id": "rs_0fb308f2a387872e016a11897853b88191972e40d0aa319ec5", "summary": [] } ] }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/autoshorts/mechanism_pipeline.py (924 chars result)", "tool_call_id": "call_udM2mxAp2KW0WWlUMZP3Sj2A" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_fudqgMtSV3vovyHag2f1DuCm", "call_id": "call_fudqgMtSV3vovyHag2f1DuCm", "response_item_id": "fc_06e352364b1a45b0016a1189826aec81918229be18b2dc75fc", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_mechanism_pipeline.py::test_mechanism_scene_overlay_truncation_marks_open_sentence -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"output\": \". [100%]\\n1 passed in 0.03s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_fudqgMtSV3vovyHag2f1DuCm" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_NEOJXuBg1R29ksnxZNCAZ5yr", "call_id": "call_NEOJXuBg1R29ksnxZNCAZ5yr", "response_item_id": "fc_0a92726500efb3ce016a118988e6a88191b14b913f00ce3a68", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":180,\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/scripts/generate_mechanism_render_manifests.py\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Assessing artifact regeneration**\n\nI’m considering whether I need to regenerate all downstream artifacts from the shot plan. There’s a mention of scripts generating mechanisms that render from retention. I think I have to run a specific sequence to generate the mechanism shot plans, possibly just in markdown format. Then, I need to render manifests from the script and inspect the arguments involved. It feels like a bit of a process, but it sounds necessary!", "reasoning_content": "**Assessing artifact regeneration**\n\nI’m considering whether I need to regenerate all downstream artifacts from the shot plan. There’s a mention of scripts generating mechanisms that render from retention. I think I have to run a specific sequence to generate the mechanism shot plans, possibly just in markdown format. Then, I need to render manifests from the script and inspect the arguments involved. It feels like a bit of a process, but it sounds necessary!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYmIkhG8ICrvo7A1Fj4I671TkfUX6oJ4ZOaB2Xsfr-yU5vHFX-72-IebKfwPoJEFyawXdiY_EiSIVDQSzb02l4iAD51pF8JkON2_m-rogQFzpkJjrR5rhI_zWQrfwpMZ4QTy3loeOcFFZ3i4afEueIQsgE-raxZNAJASV-xJWAft2jke6xBddhtJ6rWlX7v3ceSZq6Uqrnexf1p0J4j0uRTG7TQdscYFcK9K56zWrgo72j9FMY2Ki9keDsXMTfGZwsleeSBpKyhewCp3HfeP1ncEyRyypc9zAxRUR9vYlDR7hRtEYevDorVszS5aTigMpHjaNOLIEYq8WEiU7XRlLq5NDxTBQLtEkt14GB1BO2TJ-N0ez-ObwMbwWY7s2kTOkP6_ksgku7mywm7M_wtfKv8Nwyf_9L7MNzISFDBsT1jCpUAoKTZHrGoH8stgoGzQR_v-hO_1DPKizG-oBlJJkKS3tNim6p0eyjBRThICNfBfMaVLL3M7XIsz2LNtCvhMU629VK12rf5Rh7YISDrU4AwZEg0aT87kGbHIL18fHSfLFAZ9kYbX4MZfKqoY6MG8OTcDwR0qA24400xxbIededsGnNcYYe_loDemkrht55nppoxBTsdU6HV_Hhj2BZ1ZnEck61TqwS96O254shy_mDCzepkq2iYw_68bIYEamjZmmnmsMwN8Yy-m0HT3MVDo4p_o6j1y3GIOqAHuoeIbS05HkydqFy-iCy7sTJusJ2fG-lPinB1-4OrPAt3EbbQEpZfi9KWlyBGAk35rqwGn9Bktlxu4-7RYAua7RQM4FwRKvTQHUZJEbeRpWcxk8P9Cp8astiEmgSejVgbKFnynVFR4iPuSrKSin99OXnMg9YqMrRSrwWHeMkiyNmM1ESmv_H6ycEQkF-Teb18CIoRI8zQOSKFyney6lhm6AGsC7ZdhLdynXu-rUQFgUf9YSRPcg7H4EKC5awST5pejP06xYsQfCW9U4L9G2iwU3OD_uAYOqhtECtYvbzBK4_SZgvUibBnewQ1Ank2dFmkwJv6Dd7h8pfZ6ywGbJx-dIQQAX-EqI95UP9USDt7_N5VWe_1WeaT2vYoRoLgadh-xMPQuAHA5j4AIDmMloV3dwSMRtzWqmZDtBi4yr32yYMY8b8jhSaQPPDWj5EbFUeFBkBtKY49bfO7iJUY0Luk2sooANEeah7Un-QffPhpKYx1COcH3cEbQ", "id": "rs_0a92726500efb3ce016a1189861a3881918f00e5142e6b2fd2", "summary": [ { "type": "summary_text", "text": "**Assessing artifact regeneration**\n\nI’m considering whether I need to regenerate all downstream artifacts from the shot plan. There’s a mention of scripts generating mechanisms that render from retention. I think I have to run a specific sequence to generate the mechanism shot plans, possibly just in markdown format. Then, I need to render manifests from the script and inspect the arguments involved. It feels like a bit of a process, but it sounds necessary!" } ] } ] }, { "role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/AutoShortsBot/scripts/generate_mechanism_render_manifests.py from line 1 (1,811 chars)", "tool_call_id": "call_NEOJXuBg1R29ksnxZNCAZ5yr" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_N4zESNO8kj7U4S5EkRFtEI1Q", "call_id": "call_N4zESNO8kj7U4S5EkRFtEI1Q", "response_item_id": "fc_01b57cbf55ca1cd7016a11898d6b9c819199afba6d61bccae0", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"python scripts/generate_mechanism_shot_plans.py --out data/mechanism_shot_plans && python scripts/generate_mechanism_render_manifests.py --out data/render_manifests/mechanism_pilots && python scripts/...[truncated]\", \"timeout\": 600, \"workdir\": \"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `python scripts/generate_mechanism_shot_plans.py --out data/mechanism_shot_pla...` -> exit 0, 1 lines output", "tool_call_id": "call_N4zESNO8kj7U4S5EkRFtEI1Q" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_p2E7SkY2vzIU9mEAuOq56IgK", "call_id": "call_p2E7SkY2vzIU9mEAuOq56IgK", "response_item_id": "fc_04c906f9eb5f0c89016a1189a89b2c8191904d0259f3a18ebf", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"ffmpeg -y -ss 00:00:08 -i data/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.mp4 -frames:v 1 /tmp/autoshorts_preview_check/frame_8s_final.jpg >/dev...[truncated]\", \"timeout\": 60, \"workdir\": \"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Inspecting generated plans**\n\nI accidentally generated 10 plans, which seems excessive since it used to just be one. I need to clarify if multiple files were intended. The summary mentioned only a pilot, but there's also a chance we need retention explainers for all 10. Should I include everything or is that overkill? I'll check the git status and see if the file sizes are manageable. Plus, those German slugs replacing umlauts with hyphens look odd to me. I really should verify the screenshot again at the 8-second mark.", "reasoning_content": "**Inspecting generated plans**\n\nI accidentally generated 10 plans, which seems excessive since it used to just be one. I need to clarify if multiple files were intended. The summary mentioned only a pilot, but there's also a chance we need retention explainers for all 10. Should I include everything or is that overkill? I'll check the git status and see if the file sizes are manageable. Plus, those German slugs replacing umlauts with hyphens look odd to me. I really should verify the screenshot again at the 8-second mark.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYmoeU-gu1Y3XmZ1uYVVF3_8-BsDnzHTKGK2825BlTIp8Rf-mqrQ21upSI0QFUYDMU8YCLhSa6usgS9uI3h3lDqsT3LlFaUqjH8JIbaGtawq3F3UN2WMUCRSYHDYiMyekp9V_OxDB6nRJ8FK1BmOhoqIJ4gZ-jTqYmyd0vB7IkrAhefLevDt669je-x_YyF3DoAzX8frWm1ZZKc2kfTWl_V7Q7SZUpCew_9vW8fLGqIvKmpZbbZq07mXAaKOwFW8VB2SdQnuYJppZhoEZuCw8pkvWSSIU9uqjZRlBsCzjnd2mmIDyQoFvuRE53gkh5gAk8xwDQLccuh42ayZCVC7sdtZItEmT2abHDz5o3anb3Cl_UvEXskpuBfgQKEBn2wC6XQhMBV5yKd3WsdDRlsbcJdw4ssNCSRQtWB_U5XFjhCjWj5YArGY26crcP5m2vHmVBGSfNE3U8W9UkBtaCft2j0GednhhI_ImoZ7VDjjyQ0KjG9uRbqHv91DFdMj_6dv5BIovbvgxRS8iR1PwhZPoco_wkA-Hb-WISo8Vyj5s2AGaw9_8jhfxL52cD1RgOCOR6AXHHuBAXt6lBeSBLXW0IeReGVqQedQZcQkjM7nQTucP6eY1cDfsDxk8oaESzaPTEOovebobVNodDyKAUweQl6aFNfRDPCaRZDJ-5_MH9h9vEo-6q1wO0XMAVRIuEy-9zLb_UE4lzlgtGqYfsdq1gjJv9tt2-bHX3FSb7_Q8q0T02AZre2F-RKU116q5JpfRaE3BsaF-jV3tPnD3XTlLw9OhWNqo7PN6MUuuCG6Lw9Q-Dop0PIzEuamBtUGeiUqzoSrB7rnrrNVnpEpJeY-VjonTjBu6NNMvX3ITnIHIJo3l2j_iW8RW78VKYkeD9VAcgv5v6pA9c_biumD5j_uNofgQ6mNgP8P75Bmkj2jnhYhzbaiBlFRatjC3DS4WgRI-RhQVORfb0QJadRoIOtWDqMbshc4lHuj7jN6iO8KUYr87oP6QUmlrO74jYUIzlDxl9ZG3ggqjtkvxz8nkpDmS9zhLpL9AnUSbWus3Sn1xfqD48TONn0gT0y5W7uEMkmnDFwtMnsVTz-nAeGn6Xga1qsi1kx3HW3OUL8mcX8M76hPA8SMwhLBPAMLlU1tu7kX4d6S0i0Vnrs7R3la9T3pTYn2vZd32MjF1udeTefLnOaRjIi5paYEglryn1PSSJm9ab-g4rTImRK0kraKF3xUG55mliRmh0jSNMdNyQIg85Cefvmb-tbsfG1eH79xXwlWZUaG6o8M9Z3gN1ALbd0GUDQJTjRXyCGFUJ_-XIqpQdJefnvQvlCZPGpaJtJdXtOpmNRf4o8PPBnT1Ip0GufWhXBxG3siSTtQncZL6jQKu0ZhlztaKVxWOpYVBCUXvd-32-xeNvXt5t1iBu2JoOVhyNU7XoBiNSmaFVHTOQqeboOJj26v8LMPgHeY61KDsL_2u_-9gj_pJP0NsU9sO81_K1kyzwUI-lCxx_2HDKPl3FUGI-oQQi4Eqpf9KXHe8VF8YyL9CQmAeVnyG9w7IrsjUz0uIudHqm0Y2sjHTq4rpyD20-CazkOjAmAU5QfXdM3SNUdsuE8hrybI7JRloXuhF-PoKHiYPZlJD6kMKkkO3xh-fktOiUifbHfy2jhGOj9zVVuNcGfAv07XPdYMNwfyv3pjZw==", "id": "rs_04c906f9eb5f0c89016a1189a42c948191b2f4b1fee90b46bc", "summary": [ { "type": "summary_text", "text": "**Inspecting generated plans**\n\nI accidentally generated 10 plans, which seems excessive since it used to just be one. I need to clarify if multiple files were intended. The summary mentioned only a pilot, but there's also a chance we need retention explainers for all 10. Should I include everything or is that overkill? I'll check the git status and see if the file sizes are manageable. Plus, those German slugs replacing umlauts with hyphens look odd to me. I really should verify the screenshot again at the 8-second mark." } ] } ] }, { "role": "tool", "content": "[terminal] ran `ffmpeg -y -ss 00:00:08 -i data/local_motion_renders/mechanism_pilots/hidden-m...` -> exit 0, 1 lines output", "tool_call_id": "call_p2E7SkY2vzIU9mEAuOq56IgK" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_HUCkD1gYjYuwTLDIowfAYqe5", "call_id": "call_HUCkD1gYjYuwTLDIowfAYqe5", "response_item_id": "fc_00498405f1f60d86016a1189b1c5c881919a6acb0eaac6a6d0", "type": "function", "function": { "name": "read_file", "arguments": "{\"limit\":200,\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/.gitignore\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering artifact files**\n\nI'm trying to decide whether to include 10 new artifact files. They were generated by accident, but maybe they're fine to include since the previous activity was only for the pilot. I think it's better to remove untracked files to keep things clear for other pilots. \n\nI'm considering using a Python script to safely delete those untracked files, making sure not to touch any tracked or modified files. The .gitignore could help with managing these generated files.", "reasoning_content": "**Considering artifact files**\n\nI'm trying to decide whether to include 10 new artifact files. They were generated by accident, but maybe they're fine to include since the previous activity was only for the pilot. I think it's better to remove untracked files to keep things clear for other pilots. \n\nI'm considering using a Python script to safely delete those untracked files, making sure not to touch any tracked or modified files. The .gitignore could help with managing these generated files.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYmx5MqZV4tWjtk6uaPiwdslAES6hhrQ8A0uoUQsRX1R9LBrgH8CpiXtTMr9gQKzLGyXF_i_S2IaBaS0g4ts2mGFzUDmDIHTO84POwRV-BnKAnTrg1E5Idp9DdsObYUfQWaRghLv_lfp3vXEB65IKhLy8NYQgD2OX7cM_im1O-3MvydDDfoh1sl_wKEE4dl7elCzzVTYTpScwjXqERCeexJP3T4E5wuXDiEqjtbPfPaSigmM2gU4fLzsl_0A5FuyDD6uhQDf-Dd3dOOp5OSuolbHwaemKD4ei_ceMJC7r40K_2x83acGt6vcdX3ibW3_lTqRKTiVfIDEpZTGyRIi14ll0xrd3Dj-06QfIwROkNHDiUr_MONbhlc3oReeaTridds6P9wGoD6iHkMa4JUp1FvyX3hC3O06dIN6ETJBPSiSnh5kXm_qdQpFGLTcIpl8enOw9QNMcdmgITGpUMHVA-k_DBYIiQ1xeVNeAFclhciNHYrcQZziIlggNikY4WMvXBzTHAs6Qsad_UF7xa8y7QZQHBZQqARgcmspvnNZ2MUi7Kgm979-N0QY-ox2dWjL11V2nvExf-F1hR7TTVJxPfS2VrFZJfzWrrQRNkuRqQR4dowslDuA39MnMGE_RsUWQhV9vVTo3NGa-4kgj-M_1-3hzLs-PKBWJ98hxh0OSpigh7RcLJZ-A8bytPCq6rp2jA5ihNmB3lR4DbxjhrzlrLcYk-1pO1L30fH5Kq9a5ixy0CMGGlHQU0rMnXZHB9eNKxKZ2mgZsWDNeH1o04DpcSJ6OGnaWOeOM9UAh0Jhx3gaaTgeklH9XNhb-xq6iM_PKeQG93YRcTl7LEPL8dMRPUARHq8DIPZgyu_RdggzsmFklHhBu1GnBAkLS8UhnqO3T5M02_xikZFs4s-EptmaMTZx2o3XenxRocu6eJmGJynYWrjcOtlELxkYAj4rZ9EdeTn8sN4a94gR-1lJgP8HriwGZ2yFL9svGb15SJH4S24OZtEnEFQ2QOrzIUrDJX1Ka3ckJnzGSLqs4FSofD8PpBzGAt3uzOlDmd1Lvw_iyxgflK_fwK_DjXsYINrGpHoncWcWEg17L8MeiAs1KGDy_JL-lSUk8MOOQt_1yzvI0BsSUOd-7jY8mEgaJhotuw2TuQD9wLm7t90doCGIhU31WY4GCVtC1boYf5GiXwii3VXBYgJnvLpPW0TvhvzdbXa9Wiy5j96xgRHs_4hRYrWZzssMBJ7ToXjYE2lD8uMRmIbzgiuNnzJaTolK8hje2-UrIeRkqVYqwZn-c30r4laDSMVa7mXWgEoUq3NHOcFEXTq75VsOBe0sz4ojUcQsJj907H2Ry6jLJzq2sWtmRK9bM3XxB39QGd-Yprr0PH2AoCORCeC4-GBXmh52dPeOqyETnDCf5NI783ldzGsL9HUcRSMK1D9BKsKI3gNunb9oD7AhgIz5vBq9dX0-Upo-jiKpEtjyLXMTG9NhnQ7AcsTvNxsxctCT6A7N5oMKLm5FGWV95duaKtX48A6df2NBms-vwuXC9Ywhccd5s5smkVG_Hu5ms3V9Bvqw6UhgnWEGLY8Xh2R01-RHEIzRbKSy1PdDs_bCqXBOnEdPvLscBhCkximtkd0EZYdX-_UeacDn2bx1hT6_vfED7NbdDReHDZfGgU5QWeZgyRoBf3D6wa0BG8WPAMhZF8flKtzJvTVU_K3H4aFUKhtIIarIiMEo2z5IL1puKSA1Uqta7RNBoT3v5nE4azfX2i_xm46U3Stczj8SFhEux7OhynzvyaoW1Q2nDmQEOqRsjtHhciZ8jqioZxiddI_n1hLwmXdv2EcVC95vfTKog4ES90hNqIAyv4TpyRJjmU0vgUxEVUyAM_iiH8CbQuopXqj2cti7dxcfBRTgEmR3Q09VXijFF-cNkfNSdPps7N_y2X8tlsx6zxbY7MQ2ugsQpIXCumqni10rkt3AekXPiOJK9QmeCFVvEWzMdcXfmH-pDD-NB9toC-sthHMIJTvnLDu0vP6A-vcl2t8wBIjhGZTV0CVRbrGQnwe57eql7TKogVXQJPpX62rUFHkOyxd5Q_9Em6w1WaYUU7vOn3M=", "id": "rs_00498405f1f60d86016a1189acd358819187f52d9868c3c28f", "summary": [ { "type": "summary_text", "text": "**Considering artifact files**\n\nI'm trying to decide whether to include 10 new artifact files. They were generated by accident, but maybe they're fine to include since the previous activity was only for the pilot. I think it's better to remove untracked files to keep things clear for other pilots. \n\nI'm considering using a Python script to safely delete those untracked files, making sure not to touch any tracked or modified files. The .gitignore could help with managing these generated files." } ] } ] }, { "role": "tool", "content": "[read_file] read /home/agent/jarvis_runtime/AutoShortsBot/.gitignore from line 1 (740 chars)", "tool_call_id": "call_HUCkD1gYjYuwTLDIowfAYqe5" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_NvYW6BItQSbyWAK0teCToIrF", "call_id": "call_NvYW6BItQSbyWAK0teCToIrF", "response_item_id": "fc_0a274b9bcb9712b3016a118a722c4c8191a993d3d6c67170ef", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\": \"from pathlib import Path\\nroot=Path('/home/agent/jarvis_runtime/AutoShortsBot')\\npilot='hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann'\\ndirs=[\\n 'data/asset_plans/mechanism_pilots',\\n 'data/...[truncated]\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering code changes**\n\nI’ve noticed that the .mp4 files are being ignored, but the JSON metadata isn't being tracked. I could add `data/local_motion_renders/` to the `.gitignore` file to fix that. This involves some code changes, but I’m wondering if I need test-driven development (TDD) or configuration — which might not be required here. I should also consider deleting extra untracked artifacts since they’re JSON/MD and not ignored. Additionally, I should remove the extra directories. I can use `execute_code` for this.", "reasoning_content": "**Considering code changes**\n\nI’ve noticed that the .mp4 files are being ignored, but the JSON metadata isn't being tracked. I could add `data/local_motion_renders/` to the `.gitignore` file to fix that. This involves some code changes, but I’m wondering if I need test-driven development (TDD) or configuration — which might not be required here. I should also consider deleting extra untracked artifacts since they’re JSON/MD and not ignored. Additionally, I should remove the extra directories. I can use `execute_code` for this.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYpyCJ7TYFJJEud35_RNEkhENSlFvgEK_RkD8mX6ERlj4B0oE_cGNEfmRQYZv5crhhX-9Os4lUtgaDa3a8WfaW76P5qFCgRVHWRYLJsREYEM42Ex6DQ8jbPMT8wtE5OavsbB_wdUMlQ6nk1KEI1F-OVpgswQR6oDYgIGgKhqoImgjOYjlqSeVb_MeQUWq2NVoEmaBHFOzZVQh4omaAE4I619iCEAppLHhFylUptZvLFXa_y4MlUqRuinCvGE9TMOYPdguVxU1D0GuzfHMsbnlqjtCgJwiqmG-89kr52HJyKdTy7ujV6Fw2fbld7O2LqJ5ReMqucHi9nrbyESFX6cBfQjkToPSM07nfI4Dl3-OAn4FU1FyPq2ZJk9ixPHESD1RDdbi_u-NNkbE5E7KQdjpDJfDvqwqFTjYQ3wb8-RGvhDb_qYPW6eBvQt3baJd7lVGuhSM5BF7BCclxfce6YxASZuSqAyNVcMEwJyJX4VrGLfrshVsRANiclrVrxDvD99N_DJFOKvzLRcSxdgSznh4UiNH9zZgMwFL3h9KCHHq9Xvlw3NcffPm7SEjAy3r1m2A2ITp1pyskf1jvVUmQCTePWCKsAbS1_YYdWbG3KBfWcC7PKFRLnKn0IJx_niiBy0ha1JyMxJRKU8o-0TV5iMeP2emq5o2a7PvZ30dnq5nAMgpqo1vynp2FuqYK_XvFtxenQ0Zui9DyeZjKOk2hnElIS68GugNaEz394TwgEDXHqoLxZlXx6qjGXgP3eIhwHe2nSqrdyZkeVp8K7QuW-Eom-xh8TyCToMp8mviFF_XDJR_wclvDWZVUszy2DaZkgAzq8QtSlDE06D6JV8lEjrt7JheIi3dRvO7fZMO5PnPtWfsKeLFBaQh_pxdfAMwzGcQWOlCM1IKez3YpK-R83yYX93XTu-DKaIpSMgwCBM76WFfUZiN64YCqU7GZEKus4ba46cSYeyAJ5uSQf2Vs-Ugf0sGtJ1rN9aU1B87BTPJrfj-OJWUDkQ5QieYb2CsDYWQuZR2Ej63df0aU9pHhJcvl6nwEnNy1uP_v0tUbH0UnP2WrontnZJxJ9okDrFDyi74J6LuwS7nqEUcj-GT1FvbXMLESqtd8ZWx8peFxFyKBR2dWktrlFxxrE8mLWhvyKs8WWx6FCEwJKQ150KHZ84osk38GJ8R0W58y4pMjTknkqIyAwOKzzMQNhK-5ZIPV8Vu5CJA-hTmm4g3aPTqN9aNPCe9bawUq5XpENwc8hEozj9IBcA6lnQ7MQVqDKjxuITYhZjjwL5ccACeP4O-fuqoPnRZA==", "id": "rs_0a274b9bcb9712b3016a118a6eada08191a0bbacd726a2d4b7", "summary": [ { "type": "summary_text", "text": "**Considering code changes**\n\nI’ve noticed that the .mp4 files are being ignored, but the JSON metadata isn't being tracked. I could add `data/local_motion_renders/` to the `.gitignore` file to fix that. This involves some code changes, but I’m wondering if I need test-driven development (TDD) or configuration — which might not be required here. I should also consider deleting extra untracked artifacts since they’re JSON/MD and not ignored. Additionally, I should remove the extra directories. I can use `execute_code` for this." } ] } ] }, { "role": "tool", "content": "[execute_code] `from pathlib import Path root=Path('/home/agent/jarvis_runti...` (1 lines output)", "tool_call_id": "call_NvYW6BItQSbyWAK0teCToIrF" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_yL7BYfKIscDxotfMNx3N49i1", "call_id": "call_yL7BYfKIscDxotfMNx3N49i1", "response_item_id": "fc_0931243020da8856016a118a7a904c8191b7bef6cb23f1a903", "type": "function", "function": { "name": "patch", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/.gitignore\",\"old_string\":\"data/performance/*.local.json\\ndata/generated/\\n\",\"new_string\":\"data/performance/*.local.json\\ndata/generated/\\ndata/local_motion_renders/\\n\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[patch] replace in /home/agent/jarvis_runtime/AutoShortsBot/.gitignore (409 chars result)", "tool_call_id": "call_yL7BYfKIscDxotfMNx3N49i1" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_YzLeLT4e4ULMRbBE9irXs8hF", "call_id": "call_YzLeLT4e4ULMRbBE9irXs8hF", "response_item_id": "fc_09668b18fba65115016a118a829b608191b101a9155993ddb0", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git status --short\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYqCdB7OCc1qpEa9eeG6N9IdFvd4RjLga_EaXtvCli7M_GSLFmdNFvMFIj4Jk-6fSjnaJXpgq6XLy3IXCr0he_r-p1AkhQxTLVLYLTAmVF5UGF5JgEZ1gu7FrwcfBZ-xp6aIsV6So3fXdojJ0zhbC-m3tDZDmfDQFDTaAORg2r46E3yWfimmt-ovo3P936h2IqhOAg1SpfwPnOuin-zbRiSdl3whCXHDHp4ADjy1nRKCyqAQ5ivNFCYcbSnQzo-6pIF-EZ7eHdjQa9_VYxITFY3jNqLNSCq01naWqG2-ZBgqwt85Ph4H8jPVaWx6XvtBlaQa14gejXGE5iFWbAopPDWXnisuDwIPwgctUm5tAfCX4xAlsbq5luckVxjC1BSkoaJCD8mfTr8qbcC0leLA23DvVZQwUPNpe95Eyew3RuCpR_VXLkXMTQf3lVrymkpsoIr9pSJAHP0upJ9z6idNSYWxGU5z--8X_w1fCyfeoK8-8ChwcJY-3_5J4WNUZd_rpsaoFICEkmu6-lSeLsPrghPiw3uUF-1fzO_L79bo7NfdD2fxyDJ5CzVkDRm2vES3uTsjgOsbssVVonY99gSn396GhB8ilNJsYeSe9TYk4jO0rUl-fuZS2oF5mIwiNSyysbWG1lbQV8D3emIosJJeUETCWKcGcRa8-RGyVB0VtLe0fO9x81Ds-jdo0APAQjiEW__bIAG_l9EYaNAfEMdLYxV1sKnkl0dsTHsXjK0NMrg2wDfkXICL21UoH2eT0hCwnvbNealisz9SnoamGH0geN03BdWZaUMt5_dEK1fflna0Vh11Lljon8UZ20PcXuhzS6p2uWdwYXNsm_9Rn9hSS9XjRH4NP0cyp0S3GERJniiW64YrGOr5lRUx30y1se8Z2PswRlb8hk8AW3mtWBppWwdY2oeMGSvf4KTbSaApW44GSUR_0p4fqwPHJKWxwEWYm0H5", "id": "rs_09668b18fba65115016a118a822ab881918bd36f58dc4b1b2a", "summary": [] } ] }, { "role": "tool", "content": "[terminal] ran `git status --short` -> exit 0, 1 lines output", "tool_call_id": "call_YzLeLT4e4ULMRbBE9irXs8hF" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_UXjlZZR9ozHQAVQD8eYUcX1t", "call_id": "call_UXjlZZR9ozHQAVQD8eYUcX1t", "response_item_id": "fc_0f5c877e4eeae650016a118a8a78f4819189683659c27bd017", "type": "function", "function": { "name": "skill_manage", "arguments": "{\"action\": \"patch\", \"name\": \"social-media-shorts-growth-engine\", \"old_string\": \"Rendering and external API calls can be integration-tested separately.\\n\\n## Pitfalls\", \"new_string\": \"Rendering and external API calls can be integration-tested separately.\\n\\nFor this AutoShortsBot/Retention-Studio workflow, prefer a free-first renderer path before any paid video provider: `free_produc...[truncated]\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Updating skills for workflow**\n\nI see there's an untracked review that needs attention, and I might need to update my skills. We recently discovered a free local renderer workflow, which could be complex. I think I should patch the skill related to this. The social-media skill might need an update as well, but it's generally applicable. I wonder if I should note anything specific about implementation quality. However, I notice the user didn't ask for this, so I'll focus on making sure the skill is complete and patching it accordingly.", "reasoning_content": "**Updating skills for workflow**\n\nI see there's an untracked review that needs attention, and I might need to update my skills. We recently discovered a free local renderer workflow, which could be complex. I think I should patch the skill related to this. The social-media skill might need an update as well, but it's generally applicable. I wonder if I should note anything specific about implementation quality. However, I notice the user didn't ask for this, so I'll focus on making sure the skill is complete and patching it accordingly.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYqKg5RDszaOeE-q7tnVP0zY3Z8X1BfmPtbKDW8bNly4BDZ3AxJ8BXcB4wcGYXuGQFkK5MfluMLetM1fwkAhudzjqc1mOPvOqitcJh2CwYZK-z0OAoUDYOh8tRWLBpGrpS6IiBReIRyOoXqBeYfzgPkmkhteyT-kccXGiYwOeMn0U7Q1-ojyqufWpHkguwMfSO2FYJ42ljzolboERp4bONXZduvhEaWJMlwkA2hdDoph1TESSxVfUgx_FSry9UVBRfX1n7cvkQX8rCR4HhqVbdLKrPDlSoGDdUiIjTcKA-r_kbWXoNPq3xufj3pMlOd-VFZvGjqh6G5H4Niw1Mx0YRW2saGQAijEi4Y0pxyoruYqHIHXztZ5tVHRKoJlhOGNXRE-4Xy23DPipNliL5Es1-w_ixEFwxQe89cqC3mHy3R4cjrvLPBYe9TPuM1WyxyGulrktRFrKGJNtOtCLD1ATjGGTc9NXKzbGBR37A8YdDE9g89cQSOmcsVVi5mPrIeRsEXf7FAtva0hV-o6-Q-A_wJEdtGxPN1TfdD8nyp8Z4DniqBLBJTHQevyEo0r2BUp2yCbbmy8A-5Htuo35cp0Ff9n2DthkJOycJu-IsHSgO9BzPcq6v4GpbW6uipZja50tsQxpVm5xoVWcoWzGuCiEKFFnsL83yNv1RBovntQ3Hi3nmk9ouIuWmA1fDFzjimTRjzcy1p3eaDrR6nJvJanCkyPrVzXwVFj5IDHQYC22vkq1E_HggjTr6DuDtfzdn9v_wtDAYxP7CGL_EuxRoUoSGQhxE7WpPRIaobZQFKW9A4sAhhDpOBkiGU9zYACrErggRbxfiPo5pAP1QpKgXneUCnh4A9pnDYv8GdkGpoqxRsFzA8S9nOUTLBF7vTJWMdZDz953u5fHvAIZUutTLSn0s9YfSXbMAmgWrE4Sg2GJKync_sffPbBV5q1r4f_4_jdZTV3SnrusQg0EaSz7eBzwPxKmiCbIhgQEiBaeR6NiF6CuBldbCt5HvTU6mJsgMTwycNFcorVypfKvr6jOH4poDJ7GoyldxUmlLMG3G9LGeepb0ymSUYm9cwsFui9VlJhz1Qh2KxVrYwIVotCzdVxPx6dMznIYeuZSsLXJ7tG1o-e1hxomq83lsRKf0dlwUWnRVeN64ze1XUKxM5GsLhrGI4MUhdFagthlDdLl4g4HMrJhhBb6FVsQ9CGzsIlAP3a6q27uR1HQz3ZOBlcMl03wIfZK4vRfZs2pQkdPC4w8o193dblGLb3R61mZqG5WC-cHCwkxkzOcKPsBSZ1BARo-6_mf35fW5K0JwdOlag42iBeJi2HOBdPfGt6nQzsKcHGosB2zcaOTgFnCmALiNb6rWBnMOkAFuS7wBQo8OGfYodLv49L_yw53-oaJzPfKnnvutgY1Y5W-w9ttr3ymLQk-y1dG-Ly3AmFPyqc12NqNUntYFc-wrOhPCai01GDl8T_cHTmjybBdSh6OKii8qIqQ4dvYqz-HXJvUDNb18BVSF9Sx_cSInR27TTEhI16NkJGKNq7ifgHKncoPDXPR-LEHOlOYvad_eJ5pLkEGQ5h6dVjhsmRhge5YLfDkb9fzMzF3GWTewx7XkhvhdYVLDuC4-o-1FAvtz3Om803brjdQNPGUVhIFklYOTcAQos9bhKd-0NVbQZ9wnfpqUmV9LqeQ6a0ytDEsbZYCSo1Y9KCVLBxmrU=", "id": "rs_0f5c877e4eeae650016a118a870330819193480736f9849282", "summary": [ { "type": "summary_text", "text": "**Updating skills for workflow**\n\nI see there's an untracked review that needs attention, and I might need to update my skills. We recently discovered a free local renderer workflow, which could be complex. I think I should patch the skill related to this. The social-media skill might need an update as well, but it's generally applicable. I wonder if I should note anything specific about implementation quality. However, I notice the user didn't ask for this, so I'll focus on making sure the skill is complete and patching it accordingly." } ] } ] }, { "role": "tool", "content": "{\"success\": true, \"message\": \"Patched SKILL.md in skill 'social-media-shorts-growth-engine' (1 replacement).\"}", "tool_call_id": "call_UXjlZZR9ozHQAVQD8eYUcX1t" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_58Rhvi7JGrCECM6pCnXwSMWl", "call_id": "call_58Rhvi7JGrCECM6pCnXwSMWl", "response_item_id": "fc_047ba9792511a92f016a118a943fc48191bbacfc52c4b8d3c0", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } }, { "id": "call_uluMuRvirwvE9qgGSorTWD5o", "call_id": "call_uluMuRvirwvE9qgGSorTWD5o", "response_item_id": "fc_047ba9792511a92f016a118a943fdc8191981913e7b0f25daa", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git diff --stat && git diff -- . ':!data/local_motion_renders' | grep -iE 'api[_-]?key|token|secret|password|credential' || true\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } }, { "id": "call_VuPJgVu3kwP4DsYPUfBLONOS", "call_id": "call_VuPJgVu3kwP4DsYPUfBLONOS", "response_item_id": "fc_047ba9792511a92f016a118a943ff081919beb8a877339ab1c", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"ffprobe -v error -select_streams v:0 -show_entries stream=width,height,avg_frame_rate,duration -of default=nw=1:nk=1 data/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.mp4\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYqQZFtXbS7BOtn31aF5laPUejzcg_Zub8vQFS3jNbeRGVleiMdwtUykrIXDUYQGQyBSmmvUzeko3ePaDJyQBq5beyDK60uBit4qVmbKx2CAuPY2zOBCHGmKO3XS_D0220kaNirwtsGI4_FRwTvwu96Dm6Oezmi5GIvGkCCT3NHnos54vYGGkPBECslgvwIn2yYC4SdqBdoXfRUj6WBK09lsPDWHGB1jYeFDahAou2ytpRsQadU5qMHsq-vhvOgRlpOeW_Am3o7Ce7niE1UstKoKVgs8EP8xa-MDKq_NhrND_ymh-Ri5Ppo1qBjvPEaXh6egid_AfciuQMR8jkYeXhnHVQELCMgtTxKaQJkS2svv_pk4Ps-eJX4TabJMv3M9rAwNeYOtwGm9wHb0o2WDENE967fAChNIKhHbvikXL6I3IP8AaFFRBT0NlhtktYR1eu1bdA-eH4V9MiG3occIQ8G_slhmQ2o7wqio7lzh12sixziRkET7i4HN9_wem29289tCOMr2g0t4mxLetOTi1LpxnmJMw8dEBEqqXP36nVxbF6azLP4WJnT3JnqnTf3RUy7hJaHVmKA4OdSpEEorsuPcy_af80_ibBAyGu5krzeaSWJOkrqFk-3wn5fkQKAnysST6WEGkSlLNKPcvVsrJLUa9nn8PTgv44-SXMqKeiQTUNF2A38X64HUUuoAxEEjYnYpIBLQulspEK3ShQcbMp-TAcz93xxlGGUYCBFm2paudN5GavRMod4adKNOaqxlWSHzqegVm3GQPVlItkAulerqHlT7YMdOM6M7eWB3izLLu-vLNu8DM_jxqEbdtMncs7SaCR13yFBp0Ra8l4K24ay-uQtkfOqUbC_sa9GL09VHQOG_I9UNyRtTK1QDlXuTBpYC8deH6sQBLCGyhYYmsC0X6CMMpNq-FVW5W0LaztKjAGuoy_18kOJBC8QpX7yT_MA9b9ESvZwUEuGheEA6M6iqbktaT4I9eYwnCFNZuE6YmDZUU0VjBXGtIWZGQgk1dse-0rveOE6p_Wd6_5D6yNCPzQ==", "id": "rs_047ba9792511a92f016a118a8f4134819183e3c6fd6778ffc1", "summary": [] } ] }, { "role": "tool", "content": "{\"output\": \"................................................... [100%]\\n51 passed in 3.32s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_58Rhvi7JGrCECM6pCnXwSMWl" }, { "role": "tool", "content": "[terminal] ran `git diff --stat && git diff -- . ':!data/local_motion_renders' | grep -iE 'ap...` -> exit 0, 1 lines output", "tool_call_id": "call_uluMuRvirwvE9qgGSorTWD5o" }, { "role": "tool", "content": "{\"output\": \"540\\n960\\n15/1\\n34.000000\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_VuPJgVu3kwP4DsYPUfBLONOS" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_HfZ2Y68F6t80J3u8biGLN3ws", "call_id": "call_HfZ2Y68F6t80J3u8biGLN3ws", "response_item_id": "fc_007475096435aa57016a118aa0b9b88191bfe2b7d3ad300157", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"git add .gitignore autoshorts/asset_plan.py autoshorts/mechanism_pipeline.py autoshorts/local_motion_renderer.py scripts/render_free_local_motion.py tests/test_free_production_jobs.py tests/test_mecha...[truncated]\", \"timeout\": 60, \"workdir\": \"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": 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"id": "rs_007475096435aa57016a118a9f0e8c819195f8030aa3f289ac", "summary": [] } ] }, { "role": "tool", "content": "[terminal] ran `git add .gitignore autoshorts/asset_plan.py autoshorts/mechanism_pipeline.py ...` -> exit 0, 1 lines output", "tool_call_id": "call_HfZ2Y68F6t80J3u8biGLN3ws" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_lKBostwnOkO6kCOwSvIHhQgW", "call_id": "call_lKBostwnOkO6kCOwSvIHhQgW", "response_item_id": "fc_024279a308100a8f016a118aa9cb888191a3a58601aeae7ddd", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git diff --cached --check && git diff --cached | grep -iE 'api[_-]?key|token|secret|password|credential' || true && git commit -m \\\"feat: add free local motion renderer\\\" && git push\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": 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"id": "rs_024279a308100a8f016a118aa869508191a980c5a4a8f3cb6d", "summary": [] } ] }, { "role": "tool", "content": "[terminal] ran `git diff --cached --check && git diff --cached | grep -iE 'api[_-]?key|token|...` -> exit 128, 1 lines output", "tool_call_id": "call_lKBostwnOkO6kCOwSvIHhQgW" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_LUzwjyZlAqQFaet2IwxbJDZc", "call_id": "call_LUzwjyZlAqQFaet2IwxbJDZc", "response_item_id": "fc_0ace8ab644415577016a118ab013ac8191bda648d03da654cd", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"github-auth\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYqw99Oq3jt61cjR6e3mOGqB2TjzdTCF6nTlaw_rIQ2o4YqWRMZVlRHZH3-E4G9dSa7FKIO77DfGNKO0RFUNGUuj0qo5iG9lRzUKvtPz4s_Fov7xOEB2TZWX5OVGDnvgCTYzAnxcu-fOszy_-kJJ-9poo7m6uq_0r09BtACLHLqRZot-JkgVvBacFlSdpm4nQ6ACvHeNrg0i8acN1oIuQk37WBnZHxcAn0Wbh056S2WNFCbSInAAHUzW_3zSBHztJJM4Xk4PawICVUAP2Inwvf_bt_elOdvMcYTgkOpHqha5ctRnoHUtP5fpyTpOpJUBMFv5_DcHfKKxV6Jdu1OpKNlvw_2BBSvLkhbN-u_Q6B349FQL38sm3T9lcfj4uZsXUndwEURme1uKvMUgvqnpuvFBTk2d3DYydoEZLI_YR1fqgk974CDPcgMFw36V2Sk6MFvHm9R3oYU3LyaJtQGWwIYjVaJSFUHyrDi0zAgDIDmrP8zJ6M1iIKsGhs4RrY4jm6yETriBSWxKkOaGFiT060ZMnIFs96OsQgsHIAMQkR7TIuTkys1OeXMk4X0HODhon3Ax4QtSLWjG-JBl73a14dzgnGS9rFHYdScsP0u-zcyt1YpLa1Y5Wxfs0ubBXfYW5EZtf7LbUpNkDnwVatCFSIageSQQP9f4oZF3qyNkX2vwRDQdo_ylLyvs5iyfDLzFBIq_VK_Lq3iNPENWxzl2uEV6b7u_fMKUtdgta8mq0rvY7--KdmeIcAy4f4E_2ZkLe3wrlUKwwffRCO-MgO5B8rs08g8r_PDCe5XbJ_jXMiNskzEJZuBL20wYmVC4wblXUewL_4_FvL5IVsoZPKBmbxVtpcu6WwduHH7xfiQS8K6iUnlwW8De7TAv6Xfs_fbR00JkmldOMF-VtT-9m4uKM81qlaoZh4InfM2sedtetwv2GQinCfvxSUZcU3o1UuOpMqQ3oxGEISaJsIYuM-JUv_6Ny8pa67BFYcIM0OJ6lOyqfYYFwY7C14ZpaxBAxjmoHXaP9Bob5Ht3xBpaGlNB24IpDxs_e6RpLqu_Pvx667T5qOmgwQBK3Gs6Pz3eE7jXaFgXKEJhG3e0JRuH9HixMCBtRROfvhRsM2SJ4tbcV7xjfZWAPIaFPiONJWqNgE74c30RI2mImQkO0qBTWm7ds1U-oAOdoJKQgXYbinmAR8jM-K7OiuQgN6khlmXOWQ20-BbIgJVusbwZ-ucFkQ_2IZDYfyQrD3XGsgISTkSY74FEKtGxVBG_V3v2OIIa-asRO1DKg_cMK4Q0GC8s3Rj3Uro5V8CMtKvSFmdTx18S9R4UwlTgPDAuqW-ZqWmJkxHUO3Wf", "id": "rs_0ace8ab644415577016a118aae20c481918f73e4a06482bf9f", "summary": [] } ] }, { "role": "tool", "content": "[skill_view] name=github-auth (11,442 chars)", "tool_call_id": "call_LUzwjyZlAqQFaet2IwxbJDZc" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_IGGjz2rzd4zN9beQEuRCEiJr", "call_id": "call_IGGjz2rzd4zN9beQEuRCEiJr", "response_item_id": "fc_0b933a621a780345016a118ab2d7d48191a60a4b90997b9078", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git remote -v && gh auth status 2>/dev/null || true && git status --short\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `git remote -v && gh auth status 2>/dev/null || true && git status --short` -> exit 0, 1 lines output", "tool_call_id": "call_IGGjz2rzd4zN9beQEuRCEiJr" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_LiECv6HhCVVLnOcmiLJHlVYE", "call_id": "call_LiECv6HhCVVLnOcmiLJHlVYE", "response_item_id": "fc_0107e2cad3bb6e1f016a118ab828948191ac93f132f5a543d8", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport os\\nfor name in ['GITHUB_TOKEN','GH_TOKEN']:\\n print(f'{name}=' + ('set' if os.environ.get(name) else 'unset'))\\nPY\\nif [ -f ~/.git-credentials ]; then grep -q github.com ~/.git-credentials && echo git_credentials_has_github || true; fi\\nif [ -f ~/.hermes/.env ]; then grep -q '^GITHUB_TOKEN=' ~/.hermes/.env && echo hermes_env_has_github_token || true; fi\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Checking commit status**\n\nAfter I make a commit, it looks like there’s only an untracked review that remains. I know I need to push my changes, but I also need to authenticate that process. I’m wondering if a token is available in my environment variables to facilitate this. It’s all about getting this push done smoothly without any hiccups. I’ll have to verify that token situation so I can proceed!", "reasoning_content": "**Checking commit status**\n\nAfter I make a commit, it looks like there’s only an untracked review that remains. I know I need to push my changes, but I also need to authenticate that process. I’m wondering if a token is available in my environment variables to facilitate this. It’s all about getting this push done smoothly without any hiccups. I’ll have to verify that token situation so I can proceed!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYq4bXIkXQJevpDHk3_zq1E6Xm_SZPazvVSU3riSXBQ2gBtZIlKUajToybrsG1oPMAQxQwU1fb3d8P-mI4cu7PR5a2bp5NbXXv6ntufHY7ZTEavSc_9hs8qNLivK3TqSM-xCs1PirdVv8LkaX6B28glFre0DO_7R2RE9L6YUL1pOoKvWTPlJFizcKABZEz0Unw9AzTF5OSC1qBolkUS2-WT7NYwO2vnrqt7JplBeNpeuP8zWtFdRFMRifed_7f3dedaN9EPQeKoyWTSEiMsNgj5JhyAapS14c8URPLHR_xq_HlzUdA1Z3QJ0s6z5HH3mjTbp40uTwGovNbRideIhot7upXPe4WIcJ5QZxWYUXXQTGwvfHUuiGGR1gasTfHRskOKnwYmGeywMSfzdKlD46_vwdTq7C-HDWrg1IQzsqE2XBo74PvkJYkGloPuH5Ki6QWmM8QHFMNyinlhr0KBW2sTLQpE7yjJcNIzhzB6DMmf8B8QPx0S8lryey31XyD3cS05pfEIP4XKhlSxw3jI7LXXOFYTUbkfSV1QrojUBaOlREkuDyqDPRC2fvsZnEGq7TFXiCkU6jSUZB3FBEHb7F5xEFRde2hdarKUZiqb30UJeq50BGxQoJDdIh7twV59hFm6BADxI6f7KgSbmnx-f1gYphUalm2xEz05VGrsBjhfLyHfUKwLju3F_z5kXbOwoz0QoElDP5IDRuEP5lIV_hfCeOw5d2bFl2uXoIBB3VjKhImYQfCC0xJTS4HkgJIV79vHMDHmU54fy-RVk2K4ua655LX35dSnRdC8Gl65vgP66L2rE8kDeiyjAzl3-m9xRghP2lh-5ZV0L_Ser_6AdpiqQkol7v6J6Ak-sLKsufkb2sCAB2jT14w9MJ1ri8BBxdfudzQugfVrOER286iZsppxBaAl3k-Q-LNLuCqelZSHz0a0OIEsnlkBAD8-J-xnvil5mzV_9lv4oN11AJKrUTb46rnuHPc3OMqN0a9fDFTIs3yujCVscM59NPi3p1tLdnRy5WbDDizJEbZEl4TtdxtIfsQ==", "id": "rs_0107e2cad3bb6e1f016a118ab5e610819180be74d04549dccc", "summary": [ { "type": "summary_text", "text": "**Checking commit status**\n\nAfter I make a commit, it looks like there’s only an untracked review that remains. I know I need to push my changes, but I also need to authenticate that process. I’m wondering if a token is available in my environment variables to facilitate this. It’s all about getting this push done smoothly without any hiccups. I’ll have to verify that token situation so I can proceed!" } ] } ] }, { "role": "tool", "content": "{\"output\": \"GITHUB_TOKEN=***\\nGH_TOKEN=***\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_LiECv6HhCVVLnOcmiLJHlVYE" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_dYLXspI9E3Px6A1jVcqOVBst", "call_id": "call_dYLXspI9E3Px6A1jVcqOVBst", "response_item_id": "fc_0a495d8bbb431dc8016a118abca3c08191807d19ae385bd4f1", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"set +x\\nBRANCH=$(git branch --show-current)\\nTOKEN=${GITHUB_TOKEN:-${GH_TOKEN:-}}\\nif [ -z \\\"$TOKEN\\\" ]; then echo \\\"NO_TOKEN\\\"; exit 2; fi\\nAUTH_URL=\\\"https://${TOKEN}@github.com/Gamexgit/AutoShortsBot.git\\\"\\ng...[truncated]\", \"timeout\": 300, \"workdir\": \"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYq8L9yfGHHHCoLdQWa9QsnAYINKOBEzynh_7sbrqp_2qEuhOWmsYYmav2h0GCNmfC0Sh4X6m7Meho_RrJPjtryuBwGcBdHfloeC769cJEjZNARZ6PqZrz5GksY89zpDICdlYIkOkBQRhrCg0bGTs8siwv7xKKIu88RKLozH5F032Rpn65VjrOYoNBfavwJVjdwCmgRLD6UFfdkjxjnFX7jS_aXVBAKZ1JzvEyyb6w2EVDGBW1hsB6mKyOfhBLND-74JY3LICyL7S9nYusbza_uH6GnY5_Ag6YeEb90ZLpj-yhxiuXfqAiaAKDGKvhbE1KfXLvXhLXkGCX7eaf5_9rN0gN7dZG6w06HjF2_gi8SvXLommK0jbCsgebJv05orG7tp-8da_ilUY8HQGe0OSWBCxsLtQ_oq5-J5IQx_kA84GXkVJGzUsEwYrG2HmT8qMc4SfYeMpDt-v-OYAFeJUlzqf5-hsG_0UbdyBsoQ4p4lv39Evy1cKJAy0Cn-f9KFrYWxtxLXwC62BVPT10oxU--Cn7UOVDcpV41RXNf2y4SbuikKYjLbCHKMk84p8cLOdls3WgT7HZuYFqoYB97KVfXaMeH2GOd0SeWyr5kx2Ij3zlkh_22iVlWg7TzzpC7IR3XqZdZGJlnOodZwLHg06ztZv3ndGCf4azkPb4BM4ZlDwxeoaVPCTMhP6SXbVqTFA7bgD3-HXsrZnZa67O-Naqwtp37iTRJpSOa4c9ygVUoEI8UijV2jy7un1IsH8qQIfPYqX7zR3w51MvvCLoO0mYurilEOabTQvzrzFAKF4fls7iubyhNNbGfLYVx6G_jf1PNeI2FlB0_g0uY9VuGFMXQH36tycQxsZMAkifnm10qkeFY4ukeebJ-jR95UOl2SBmxNhyxoyyiyTy6SEa2X6pdjr-HeevIxkjaspPIAW5TGw_gcQug4dIXSKIoqsk0sINxU41p8SQsmstv4o9y5C4RgbTOO7UG6UrJLsDHf3LUGe53vXsXhyeD4Da0psRAARRqqi3kj4hZmzqV-i_SVqaUhvw==", "id": "rs_0a495d8bbb431dc8016a118abbdab08191b713309069ac8713", "summary": [] } ] }, { "role": "tool", "content": "{\"output\": \"NO_TOKEN\", \"exit_code\": 2, \"error\": null}", "tool_call_id": "call_dYLXspI9E3Px6A1jVcqOVBst" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_YKRIUM6fPxX1TTOH7upbODv2", "call_id": "call_YKRIUM6fPxX1TTOH7upbODv2", "response_item_id": "fc_01b8def93e9bc999016a118ac5e1408191b71827808455b349", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python - <<'PY'\\nimport os\\nfor name in ['GITHUB_TOKEN','GH_TOKEN']:\\n val=os.environ.get(name)\\n print(name, 'len', len(val) if val else 0, 'prefix', val[:4] if val else '')\\nPY\\nprintf 'bash GITHUB len %s GH len %s\\\\n' \\\"${#GITHUB_TOKEN}\\\" \\\"${#GH_TOKEN}\\\"\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYrF5sY_TG0aVUhAVGT6j_2sGKKIDR03x-4g7pjp4YTxCt0son3G5r1EngCCJNqkm1DOcjTAOlkeepBfm8SAsJW9V0-_2y1zYzEnDC1OofZxiplNC1zbzxw3oTIwEfRuMNlb_jtyYm4fxUNEjwu8bpcD_KMpWXdashfbOx6R6N3AQQUuhl5waw8zGWKOE8suSv48qomFCvnHXVlzNxt-6BLTdgCkBLsQS12EYg9XFcMZkWVL1a5iEqfpGSwoGouA4_2yx7yDLB0EdHXp7ceICdeFeEomVCZ2DwTzzjxMvYR5glHPjqDBZuWdooi3LPot9kh1Kw7Z8Yaw7HyPO2fM7Tj3b0ALeX5GtidHqlvb7tFp3Eq70rnFtCoF2wybNc53ubsnWns-26bLGoHM07vtw2Stb1A3-BEGKTxaULxkpJDV0UGCd7S10ZoY1uFvtxiWl4C2A9qknhTkZmCs0Iim05GUgvMw-bH0sXc3NDbDHMtEw3SAj3ueIQ2qbCOHTFZypA_1IFkcXKsPEl3Z_9-cmCkEK3l7WPiOj4ydVNkf6FlbGneHurp2H__YZn-eC0NX4aLaeklRDHmRPt1tvirX0RYJUxtiwjQFYN6Xn_tuL67eiMtxn7q78W-sV88BUBArVyhdPveBF63Pc0UDwseFEzOnytX2wSvTr9Vc8ePVyaWL63KR6CEskJeiOFxA5fW6kgIa87-C9SGtfuxYNvVMUpTxz8YiTn8gacoad7ZhFwYU-we5en-nMBfbDCQW3L2k1x-kr-koq1iousXA2R0PifRSfPd1TR98x5jy_Ac-Ite2VkXbkcLiXT1ogc66Bf5EVuRyRq-Z73knSgD7kk4JKwLN25r8ci3STlEjLI-SheNOskk7CNw16O2S19NyeRxs3St2adFqQgx8NZnfVp-JBK0DApZd82fPlbsr9gc7f3FyCPpQ2EQAXXZFEiFVbRdc4_lKJ9BArQdovN4z_Lj-fmNvXtN3xC_sb3shU0dvHgBN9xEDfHGTWnmPfLjWDIRi7T4lE4t78wqXdT6830K9P_9QRj3LC4QujupkQ9CpZUKqJ1YiZx4RJrXm0wcVue9vduCdDqBk_PDhXX2cP45AALNM94wMGletqX_qnd8jgq9IkVYPNrQikzqYO3d7XBpsebaqMP85m4uAhqChINl4P3btdvGkE7OiMDTIxqHeoFx8VCYip5KWrGHiP3kyKeIhqqPZjRibm9mFuHOSVZaKkesUl6mdq3W9zrVa2l9GvEW52NWuVAD3LYFvAqmjNP9Huz1xK9ibB4CgiRz6uyLyKAyjfxfVzO7qyD86izexNaL9d4bIfiz8dQoa7GmBxdZrwfI08r3f2nH6UUJh6oq5m2TthRk9TwULhJ8HK2S30HJ06qvC4xBoQ3u29wTsAVOWGLxvQ1wguP3VrSHYlBvtmE5Ht1pWwevARI8A4L-_vI3NmIEb48OpE3lTP4IPCOJOCMkeHfVemOotEZotV7oraAjg7_K5qByzONl0HwxL2-nW32Rk7E8DpkCXk2KTLEAwlBJWbClRJ15TyCVFtnq5emc5cAi741FHxWaG6uLHrmd5Dg8hzEnRQFwoPN1pml8nlx5NEUQcvYXUHSAFd4ZqeN2vIoKfjEOgzfXf3V0-ia_zm3vof91b5DBQY5GsmOcRR_QFmOkVZOY3FNDUbyUW-2z1Yy4t1Zr3kMnZlJdKWBVhVEU=", "id": "rs_01b8def93e9bc999016a118ac30bd08191a0e70b5bae9c66d6", "summary": [] } ] }, { "role": "tool", "content": "{\"output\": \"GITHUB_TOKEN len 0 prefix \\nGH_TOKEN len 0 prefix \\nbash GITHUB len 0 GH len 0\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_YKRIUM6fPxX1TTOH7upbODv2" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_7zPHPM4xRABfaG7lngx2Zs3G", "call_id": "call_7zPHPM4xRABfaG7lngx2Zs3G", "response_item_id": "fc_03d676cb9e8df55c016a118ace27408191b8596f43ebeca08f", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git config --global credential.helper 2>/dev/null || echo no_helper\\n[ -f ~/.git-credentials ] && python - <<'PY'\\nfrom pathlib import Path\\np=Path.home()/'.git-credentials'\\nprint('git_credentials_exists', p.exists(), 'size', p.stat().st_size if p.exists() else 0)\\nprint('has_github', 'github.com' in p.read_text(errors='ignore') if p.exists() else False)\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYrOmvl4oiK3IHtNxuEYAfZd1l-g3V86tjzKqtpd69suDUicPReq4eaOxreW9V3VjjBlLb1KgpWNF1dLdaKdwVfG3ICeEXzncnkluZRGmdOuSEGkNU_4_WkK_pxOyV2lTjrmsA5SPOIqB46UxD_j6u6_wHmqD9r4rGmWbIzB2N0pf2qs62BPHOQZ38qev_cOpXKOKjnZsTmaGlQMsubd49CqknRjh9_DoenksfO-rww77q_i2e4C-VUCY2xLq0ZwjJ2St_3k-myJKJQ7JBEpWH3fOp_6D7y_p3GsXNu0iE6GkcsLNI_Ro5GzF8esgvxBJ-FoMKJyMEDrz0pcah6tvxbCro6QUbSXDSmHnbLw4qUE_lPHimXcxeKUSrzp1yCITlvKedQbeIsmqZhdBuxTz_8j__6yqfCW5a4DXhuBD0j5bbbB3WDQ84ayp2fv0TkyFpqvs7zGccV_6y2s9xjgYz63OD4u8RrbnGj5Ar8sK8TpDF-5bo99Y2mcwJ8tY6Nv1qh_ntq_-kgV53sVAj3oOVmghKKn5t0UTOOG-NxMZcC1hf4_9ynp2iunBAqdtcisnMF4fHjrDE1THM49qKfyBJCtx7ozdcFtNQvXQImkGtOeLoj5oobyP24gvZq3KCosqyTFpndaage61Ej24bl1gTb7f9NOCSMePKx7DHAzvhEluIkK5xm0g7e8XZhDNHxmoXVz8SS9eCpbDEJEzD5ow7LRFcv70nKGCn8pvcPSxucSlB4d1Bqlc---oq6qCCxswdAZiptTnhqFhEAEXwRuKMWVqHPzfpcPN6sakkc47Vg9XzXqhtg9WGpDgdjfnRdl_jTVA8FMILkiSESxCZD5QnOxx1LohJJijqXp1mkPLIHDoS9x8IOb-Xy5dvEIbNnVfS9rwS4eujFUghtBG8cPG7hBGy1mp0PGVm3j2rPLx_CocclSn2ISaqtQamcyNmEQJbdJCl226Mp6fEOy4DkbkG5hga80pWeAxN-LfDJ8AUmhfQblDBegyqigtB3yDq_QUVfQ6HuMXrMpsw-Y8uYRHLd8L2nFHBCXpjrEiNDyV-80rVkJvEjrBtjjoslNKNRTDK6XIhXDw1cC4ROnzBBvJVrgDAElhWbWMbNJ-yROFjCiPrnMo4TNTKzowMO_DBM5K_pukV5sg7Trxw3xWErQT9_2lplIqcq3Z97egtAgXRyWTyybA3gQEDZEjmvww-evQtddH6yPeFBAZeeUTxFbW868YITD-5kl29isryumA-DKkRlZjZ6uIuiuxZvpPHjUsPyiuSQR1wlytVv2CK2jxADIO245u44Bce6oYf3tSbxhVsioXXu7kBCNhLah3GCEluowIw7oRRHR63G_w0kGcqY00Eo64jt59UjYY8X67RoPoEEGnKggz3Js37J4hMxrBmDtrvh59M_BBQy99QZlED-cVXWXlcP5xIJdyZH21OIIZjpZUA4nbD_-NfrUoB18PPpOu3S_XnzwkrzJY3SCVMGiATQiN2c-h8O2b0jSyl8_vB6vcFLqYi4R6f7vmiLYyRH4ms_Ey-6eDP3MRNb6nZC5WB3DKDpnH0mTcZHPjjTar3so5W1wOoaUAvFRQvXZ4VnToFHmeDouiHW2ww4UiCWfEfgrSykBrNkIBmQqbD9eG1pecwzU5YVUN8EryYASHQYFsRQ74Mq-4cHRc7V2Ev9qUluyakpXLe63uxQBihzKMwk6fH802kqAd_j-GeOCR4mOIYtettQ7VvLY-B8pg4y099bhzLc26Sz51oAsp357R5LhA4_ZiVPHf5NHevj1iSyo38v5RnX7SkOSnGLuMj50G6KUXdx5JwXIPjbwxJXKRLf4xG7KbaUVgzaknxdVhjYaKfBAwPFehhkIRnKkQWEJ79SkY4l4fRrUcO-5uSyZxUNPatZLaZvziD8Lm5EeJO_1v5L0skHaVjYfmtOXV4R4KgJGaGCqum32BbIT7jAtKnmxTLq6BM-B_g93a-ToXgUzAqM4Mi6O2IyQLuvGphvYQXOmDZMMC-HnUyONq3qp-Lg=", "id": "rs_03d676cb9e8df55c016a118aca8d748191b92f85d5f25038ff", "summary": [] } ] }, { "role": "tool", "content": "{\"output\": \"no_helper\", \"exit_code\": 1, \"error\": null}", "tool_call_id": "call_7zPHPM4xRABfaG7lngx2Zs3G" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_dEyYkYE5tUWdM7788zXKKEOM", "call_id": "call_dEyYkYE5tUWdM7788zXKKEOM", "response_item_id": "fc_004d0d07f4c4dce5016a118ae56b188191a9dd2d849211a426", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"ssh -T -o BatchMode=yes -o StrictHostKeyChecking=accept-new git@github.com 2>&1 | head -5; true\",\"timeout\":30,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering SSH options**\n\nI’m thinking that maybe I don’t need a push if I can just ask. But if that doesn’t work, I realize I can state that the push is blocked. I ought to consider using SSH remotely. I should check if my SSH keys are configured. If they are, I could successfully use SSH to access what I need without any problem. It's good to weigh my options here!", "reasoning_content": "**Considering SSH options**\n\nI’m thinking that maybe I don’t need a push if I can just ask. But if that doesn’t work, I realize I can state that the push is blocked. I ought to consider using SSH remotely. I should check if my SSH keys are configured. If they are, I could successfully use SSH to access what I need without any problem. It's good to weigh my options here!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYrlFbhZEuXOhdnk9RJoIrUO6tLm-AJbxtM3ZkCgCEUGXA9HSgAno2pt6crFwZmHhNLSzn7E0OjMmXWJimPqXKRZRdwprj1wxDVvTe1sOpXtbkMvUPJXpKpGAyEt5QkUqWmmhX_bLWTTtSqWP-MmjxUN-UikB7q5MzfeqsEsuvTF7H4EEAmhOMEjw8Ni4OiR-QAyDOBa2g9N0U70zDBxcFFP6xQ-_EnrNjr0yo3vyozKn5e73YPFSn8DRoEO9_gcdIvXuh7Lj-DKg6kr0PozEx8ylzsnNQckLq4vxUABSYumvbmgezI8P4PmC44N3nzaJ9lHVj8kgVrzXdbOscqyoJtbBdIUbtEPQD79YLYkXrZt_FxapZF3nIAPdr6MAJ2xtNBr78j64hNsZ54HjhPo_8bid814Ul4numUeub-fSMPmpTAB7-ER5-2jb3cZ799hRLCgeGKeIXD3kxmV5NLA380UevkbC3xjM1pCVEAlc3CzTp6kcL5cZFcVEKB_qVmZKI_41g9YOpbqLy8V_EvPiO_QGJTz_0DpxgaLIMSoz9K7kd6JdCKfYfyGMvo92f7-tkEdt_OBYp2cJxm8TF9SVkNgKrrqneB1dS52vw29jwrPi9dZ4x2C59AXg-rjBl4ZOhmhnj7zrZtbMhE6qtqcn_TVaJP1UXjS4MxPd9TXTZuCixBMbOeTpFQ44oSAoHX5omdJ4vpju8lEXlCHB4_9dspKv9GHPMMCbAywil2psuP0maSAzkiP0P6SySUFff1smJnKctuX3mf9soRK9F8e_050IIItgIOXR8oRHTLxcnMdFSBydYmQfnhV8CYiDx6PejYmA3VczIrNvVHIionpzxNv5nHMpIOO9vZqW0FRaqkSJHJTN3tEH5qAtRTdncqTLHxCAamooH5wMLCVMBeVlKCBp7CI88Ys1mBDNbNymV9omGMG4LvOjnIkhEQKYVkjKLGcOj9yrqUkLVbdKDl9g5oTYnnbfpOsRyLfaKnmvOgMpJgDuyM5PZhkSz3wnRlkmW-JiVKjbxUYbNfr2zs_LrjfEu5P2gvmSyCGCvidrLU_UjVnNVKIKZqNEoZD8iq8osfVDUWtJSjrJnLVJahhvltm8A==", "id": "rs_004d0d07f4c4dce5016a118ae34f0c8191b1d547acded89b7d", "summary": [ { "type": "summary_text", "text": "**Considering SSH options**\n\nI’m thinking that maybe I don’t need a push if I can just ask. But if that doesn’t work, I realize I can state that the push is blocked. I ought to consider using SSH remotely. I should check if my SSH keys are configured. If they are, I could successfully use SSH to access what I need without any problem. It's good to weigh my options here!" } ] } ] }, { "role": "tool", "content": "{\"output\": \"Warning: Permanently added 'github.com' (ED25519) to the list of known hosts.\\r\\ngit@github.com: Permission denied (publickey).\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_dEyYkYE5tUWdM7788zXKKEOM" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_suydXT91R89LchRI8vCh6EDl", "call_id": "call_suydXT91R89LchRI8vCh6EDl", "response_item_id": "fc_0c22421588f067bf016a118aed00008191b7aaad4adb8e40cd", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git log --oneline -3 && git status --short && git rev-parse --abbrev-ref HEAD && git rev-parse HEAD\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Finalizing media and testing**\n\nI need to make a final note about committing changes locally that haven't been pushed due to credential issues. I might also want to deliver the MP4 media. It seems important to inspect the final screenshot carefully, as I’ve already done that. I should probably run full tests after the commit too. Plus, checking the status and log would be a good idea to ensure everything's in order.", "reasoning_content": "**Finalizing media and testing**\n\nI need to make a final note about committing changes locally that haven't been pushed due to credential issues. I might also want to deliver the MP4 media. It seems important to inspect the final screenshot carefully, as I’ve already done that. I should probably run full tests after the commit too. Plus, checking the status and log would be a good idea to ensure everything's in order.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYrs9W-nQ-cJcOG_XJwxvaHOv87aqCRrmh-kZfbt24rq6MlysIcOfA3KtUWBo29fi1OTi4JnGWUE_IH_MKKDAWHgLriJrgx2hIk0JmJugj02EckTCLIZ7ohOGKySENGVriyhX8q_8xCnEeHVIbLkSAIq0scR-0F1qtaCroVPgnmC8vFtwXnCVmnzse4Uq09S0FivK6JTqW2ZXspbAzTzW-6LkptZAA2svdm3zz73a2eJYByaig2w0KVrMfSRKbC2UJM8OMmYEJAdmJVI0jaqvHfR6VoYJBWZAzXwx5vu5rFAlZAwLtYjT1zrCj8KaFGAe9IKM0F2wnLWjS6lj2gbLhaFQRDQM5w80TZg8OIASow0Q6c_vrx4ITLd94pje8tiEgCyXjyknAOGLkbzg-8lv2iqXzkw8h98ohszELZNbuu2hu6v0Fvfr_0-bV-3MZIHdQAGCQa7f-FoE5r2LjYbwxJxX5jbJYwaI6hGBvyPR2F6HRkiax6LSphS5svKo1Ex1N3Kqr97n8Enfu2BaqmH_oeSiGmYcfg1nbcCUJvq-1TnB5ItHcHIqeH1cjBRhSyzRbUJ3SdymKQ0lSPIgLZaRBGR6eK-G4nQH_yDyR585OrhYP6yctix5cfNRhydy4-Xe4egok6prLMX4XGvqFbWoWsuz993BkV3kim6eXi-c4T-CRsChwManJ1kedeiE-hNexOeulXxXxHw4V-c21HHHXerPy03Bxiq_pBrPhIYI1TcEDcRnBNhFqA4vQ277ItRno1tXSXZvT23Eyh8T6o2RKGVYpq1M0GW1wwPQNW_SE1yp6f_T--Aidz29z4K5IoDiSjH459o4Hw-GA6MqQF9fddMqW-Ea7zpK8_nNIkFkbrlHP0evBmdf84ruiuPl9PpZXqkJQS_Vg-4Bl9Be-HvkxqfapTfgeGEvtIY6bZVKqqkAdRTN1uvwjFWSIbplI-jjU_GU6qa_jrjh0GPR_zl7gx3cGvf_ykPDmaR-d2xD1jZEbdLFI8-hCnQ0PzcQ7gtajRzWDhsBNCfyurLV9Wxq0qP-O_6C16hntAt2gEYsGY4YK5XDRY9ZFteoSf6DArEoxOSRdtkfWfUMzNEy7lbyeves8bSrQl36oTtiy-GY-Sa70qCT39s57l8jeubr_QPtFlbaOpRZQfzm1xcovdfopJYeySOKMvWuClHgB-ykZQMqvI3aBsIhL-HtoTuLP6mffStUkI4iAuIK1lnV2fRdH6WXw==", "id": "rs_0c22421588f067bf016a118aea6ce88191bf2162e7bb19553b", "summary": [ { "type": "summary_text", "text": "**Finalizing media and testing**\n\nI need to make a final note about committing changes locally that haven't been pushed due to credential issues. I might also want to deliver the MP4 media. It seems important to inspect the final screenshot carefully, as I’ve already done that. I should probably run full tests after the commit too. Plus, checking the status and log would be a good idea to ensure everything's in order." } ] } ] }, { "role": "tool", "content": "[terminal] ran `git log --oneline -3 && git status --short && git rev-parse --abbrev-ref HEAD...` -> exit 0, 1 lines output", "tool_call_id": "call_suydXT91R89LchRI8vCh6EDl" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_3bWyFmhw9r1ETXZXv6LW3eNA", "call_id": "call_3bWyFmhw9r1ETXZXv6LW3eNA", "response_item_id": "fc_043833c46c0d4b6a016a118af05e408191bd7aaf628aaa3d38", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Local Motion Renderer v1 implementieren und Pilot-MP4 rendern\",\"id\":\"implement\",\"status\":\"completed\"},{\"content\":\"Tests, ffprobe und Git-Status/Commit/Push verifizieren\",\"id\":\"verify\",\"status\":\"completed\"}]}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYrwLfTU1bjk6rbh7v4usjmMXfFaeMQlUxfUVaIpwEn_47vMzlSCMtFu1hSz6ipbvuRq5VZgv_TcKEswlAzHIRZJBt5hpj1kz0MtmAVSLpiDfo_M4uCtFHEulwXkK4TUV51UKAv2vqqf7veAEXTJ6I3pTck3bAR3YSRg5tiBOhs3LZAqXLJramSbVyzjzG2RE_ueRa9bq3VsaOxVqA8iF6W45neev6SxIDYgQ9FWWhvMJfsIB4Yu1Opm3Npb3xmB6u3oVSvENs0VzBPwo1RYQMcGuJyRh9SVLcb5EHScE1x5Ge0FuP_xRnk301vpk-_hIKtzKaGF-w0-IIuYgx-L8dtaSS8uDoMepclwKegH9YGCq_B058A7hFyFVn30o3p8IsvcdCcQWb7Vy98Zj5uxkMsY8PpQJp4EQJhS9lMgHE5h77BFt_cH8kvTIf7rpm1NdVS9IzFjK0IXdrgDmBxCmRP2_OFiVM5GpcEhHbaPpZXNazCOCzZmOyEGpuEY3sKIZpTSoW1nUoPnqFmmYD1ucF1FCjoWFyMJbNSdVPyN3-quLQUQOQJ3eQJUsXlsFCJ4XOmkYf7kOqRyqWAcdBYnXLTEeMZ61RGUpL1FvUd05umRACQCCJUC192W0vGkdC0HRvjNGZResR6MdEb9-m0taJo01I5FCpCuD3F7i24_Im3Csc2hGM85pT8xG-Nz391i_GydnFF_3WTwp3STB3YvIzakqXCj0IpDiImiyBHjDGTSwyOJf37kYygDLC7wHC3B9vXG_vtxSlp-TpGq0KQJ1lViMYMuLnqGJ08X_KMvcG4OwG5fyga8tqBClZL6sSzmeOvuHACod4j29kIHkUJWoFKjRgQdeeaTgJNebUdeaPNX6SykTkWncuMu4Ep-ToiifXFOe1sKJ8A39JNNe3ox3_40cS6-TIis6jsI0lV2kecqnJheKW-olnOGXoRrTFQpk9U5Hw7SWL2vKd9eiDopKndSEQ==", "id": "rs_043833c46c0d4b6a016a118aefca248191a272498a6332eb80", "summary": [] } ] }, { "role": "tool", "content": "[todo] updated task list", "tool_call_id": "call_3bWyFmhw9r1ETXZXv6LW3eNA" }, { "role": "assistant", "content": "Erledigt, Sir.\n\n## Free Local Motion Renderer v1 ist gebaut\n\nDer Workflow ist jetzt wirklich **gratis**:\n\n```text\nFree Production Jobs\n→ Local Motion Renderer\n→ FFmpeg MP4\n```\n\nKeine Hailuo/Kling/Runway/Veo/Pika/Luma Credits. Kein bezahlter Video-Provider. Nur lokal:\n\n- Pillow\n- FFmpeg\n- procedural motion\n- mechanism layers\n- kinetic captions\n- optional NVIDIA LLM nur für Text-Refinement, nicht fürs Video\n\n## Neu implementiert\n\nCode:\n\n```text\nautoshorts/local_motion_renderer.py\n```\n\nCLI:\n\n```text\nscripts/render_free_local_motion.py\n```\n\nTests:\n\n```text\ntests/test_local_motion_renderer.py\n```\n\n## Pilot-Video gerendert\n\nFür:\n\n```text\nWarum ein billiges Auto teuer sein kann\n```\n\nOutput:\n\n```text\ndata/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.mp4\n```\n\nTechnisch geprüft:\n\n```text\nwidth: 540\nheight: 960\nfps: 15\nduration: 34.000000s\n```\n\nPreview:\n\nMEDIA:/home/agent/jarvis_runtime/AutoShortsBot/data/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.mp4\n\n## Was der Renderer v1 jetzt macht\n\nEr erzeugt lokal bewegte Szenen:\n\n- Scene 1/2: procedural cinematic motion mit Car/X-Ray/Preis-Risiko-Tags\n- Scene 3/4: Mechanism-Layer-Reveal mit Preis, Reparatur, Standtage, Marge etc.\n- Scene 5: kinetic text overlay\n- Caption-Overlay mit sicherem Text-Fitting\n- sichtbare Bewegung über die gesamte Laufzeit\n- Metadaten-JSON neben dem Render\n\nAlso nicht mehr nur statische Preview-Cards. Noch nicht „Netflix“, aber auch nicht „PowerPoint im Witness Protection Program“.\n\n## Timing-Fix\n\nIch habe außerdem einen wichtigen Fehler behoben:\n\nVorher waren die Free-Production-Jobs auf Szenenlängen von 3–6 Sekunden gecappt. Dadurch wäre aus dem 34s-Pilot nur ein 25s-Video geworden.\n\nJetzt gilt:\n\n```text\nRender Manifest duration\n→ Asset Plan duration\n→ Free Job duration\n→ Local Render duration\n```\n\nFür den Pilot jetzt korrekt:\n\n```text\n1.4s + 3.6s + 13s + 10s + 6s = 34s\n```\n\n## Caption-Fix\n\nBeim visuellen Check war die Caption in Scene 3 zuerst zu breit und wurde seitlich abgeschnitten. Behoben:\n\n- adaptive Caption-Layout-Berechnung\n- max. Safe-Area-Breite\n- Font-Fallback\n- Tests gegen abgeschnittene lange deutsche Captions\n\nZusätzlich: gekürzte Overlay-Texte enden jetzt sauber mit `…` und nicht awkward auf „und“. Ein kleiner Sieg gegen deutsche Nebensatzmonster.\n\n## Tests\n\nFull suite:\n\n```text\n51 passed in 3.32s\n```\n\n## Git\n\nLokaler Commit erstellt:\n\n```text\nff5df62 feat: add free local motion renderer\n```\n\nBranch:\n\n```text\nfeat/initial-growth-engine\n```\n\nWichtig: Push zu GitHub ist aktuell blockiert, weil in dieser Umgebung keine GitHub-Credentials verfügbar sind:\n\n```text\nfatal: could not read Username for 'https://github.com'\n```\n\nSSH ist ebenfalls nicht authentifiziert:\n\n```text\nPermission denied (publickey)\n```\n\nDer Commit ist lokal sauber vorhanden, aber noch **nicht remote gepusht**.\n\n## Weiterhin ignoriert\n\nDie versehentlichen Telegram-Review-Dateien sind weiterhin untracked und nicht angefasst:\n\n```text\nautoshorts/review_package.py\ndata/telegram_reviews/\nscripts/generate_telegram_review_packages.py\ntests/test_review_package.py\n```\n\n## Nächster sinnvoller Schritt\n\nJetzt würde ich den Renderer v2 bauen:\n\n```text\nLocal Motion Renderer v1\n→ bessere Mechanism Visual Grammar v2\n```\n\nKonkret:\n\n- echte Objekt-Layer statt grober Rechtecke\n- bessere Auto-X-Ray-Darstellung\n- per-scene motion presets:\n - hard zoom\n - layer peel\n - risk meter fill\n - wrong-answer collapse\n - final map glow\n- einfache lokale SFX-Spur via FFmpeg/Sine/Noise/Clicks\n- danach wieder ein neues MP4 zur Freigabe.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEYr0RIa-vibCvsI5_3VcvR-rML1XR7oiB-Lupu8inqpbH8xYl4xyyONo6xT8bmDh1E33XSPVPHf2e21idZO-fmAnSICdyOVdqS8mS1gR93DC9-OeLO2xY2_6n4-1IuVMzcYZDrAyE1OkO5awj5yGPtxnwkQGRHf3PyRSzVB4InC842Vc4k8GkqKqTNkd6Q-2ApufqMoicd4kH82ZI8mFYyk9MHOYnc6q_YZfCnfjXLtyjG_PfNkfQ94t69ptFN_MuTs2PLht8BJVa44ATQu3ryrlbt93XIKFZyXOQel-YX2V8PQyn6DPa7Q1dnlILyd59znBGSbRduSqWdgkNPy6pHFzLXJfk0h05McycYP2pWKl75-89DQV0Z5bM7-6NYauQa0L4Pz-VYwKQ82FRufQbF_orGYiGp3pjnnnLK9tVyUbP2yySHjVpuHfQZ15T32SHQNoqndW4KppBMUMBiKt_ATs59bZvEGG3os69r2QTizjcOc8BCojlOETu44Mqpjq2Iw_B3ZFDedIlU340o-Q01iAcZqIi8lDGUDbH2C_7kJ1VamNJoB0JDQMzQveGYQSwO-t_1BLYOh-t3mP4uRN6wHhmhXds0q6m5muDr1NaG6Y9Z7mCtPIPy7KiRHan5FievtEI_570IfI_CUcJ93YR9hCcLWrZg4ukKXIU55_zNK9XALwcljv6S8J6c1ANMDVyltn5in3U1_nnTUgtk1AyrLBEl-98BCdc08RLwdkWijhoVHLP2EKqNNkyjwU-1RXmNT5v1bhJCmk-YrBzv5aDNkiD5NnF7YUqB_nVHw46aBy906vAhmBG_2ZiReVSIwJjk1JizolPXINNzrbqOd3F3MZMxR_pqO6XbWYUT6L7eIz6jFYzlQ3AJg1g9tvL5zhXGnKWYIAWja_R7kh2YDIRMxZ-fhle_hYISHECrwJLgkO28VBg0m98tRRnMbXB7yLjOtXZuljJ0R_CmPw9HANaIp5N656MD5RdFU17CzZbbXnHGk1uXbPmcjtWB1_slYOHPyEyzSegNNZDg2GohyVorteVoIjRzuqH8toQvfRw0La43aMfRg2BmbOI9ON8C-wBGBuhfxD03Q0rtaqeZ3syXWd3q006KIk_tWA6zoza9BRfyt_cKWNeCZdby1TtvLygBOTRnyKc4fiqWzoHdlciuyLc4fAxvOEv3Jf0xBUu7TFA-YuNZ2U9YDX53PvujeCQFZt2CukFN7tZ5cYW8HCRwv2kMWaANGNos4Fh3M2dZxjWiBDUQ8umv69wAJmaiU64dD3UaFas6kB0IpWX17XHScLaw==", "id": "rs_0d1a4d10654d56b4016a118af390ec8191a42e816e4c752c28", "summary": [] } ], "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Erledigt, Sir.\n\n## Free Local Motion Renderer v1 ist gebaut\n\nDer Workflow ist jetzt wirklich **gratis**:\n\n```text\nFree Production Jobs\n→ Local Motion Renderer\n→ FFmpeg MP4\n```\n\nKeine Hailuo/Kling/Runway/Veo/Pika/Luma Credits. Kein bezahlter Video-Provider. Nur lokal:\n\n- Pillow\n- FFmpeg\n- procedural motion\n- mechanism layers\n- kinetic captions\n- optional NVIDIA LLM nur für Text-Refinement, nicht fürs Video\n\n## Neu implementiert\n\nCode:\n\n```text\nautoshorts/local_motion_renderer.py\n```\n\nCLI:\n\n```text\nscripts/render_free_local_motion.py\n```\n\nTests:\n\n```text\ntests/test_local_motion_renderer.py\n```\n\n## Pilot-Video gerendert\n\nFür:\n\n```text\nWarum ein billiges Auto teuer sein kann\n```\n\nOutput:\n\n```text\ndata/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.mp4\n```\n\nTechnisch geprüft:\n\n```text\nwidth: 540\nheight: 960\nfps: 15\nduration: 34.000000s\n```\n\nPreview:\n\nMEDIA:/home/agent/jarvis_runtime/AutoShortsBot/data/local_motion_renders/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.mp4\n\n## Was der Renderer v1 jetzt macht\n\nEr erzeugt lokal bewegte Szenen:\n\n- Scene 1/2: procedural cinematic motion mit Car/X-Ray/Preis-Risiko-Tags\n- Scene 3/4: Mechanism-Layer-Reveal mit Preis, Reparatur, Standtage, Marge etc.\n- Scene 5: kinetic text overlay\n- Caption-Overlay mit sicherem Text-Fitting\n- sichtbare Bewegung über die gesamte Laufzeit\n- Metadaten-JSON neben dem Render\n\nAlso nicht mehr nur statische Preview-Cards. Noch nicht „Netflix“, aber auch nicht „PowerPoint im Witness Protection Program“.\n\n## Timing-Fix\n\nIch habe außerdem einen wichtigen Fehler behoben:\n\nVorher waren die Free-Production-Jobs auf Szenenlängen von 3–6 Sekunden gecappt. Dadurch wäre aus dem 34s-Pilot nur ein 25s-Video geworden.\n\nJetzt gilt:\n\n```text\nRender Manifest duration\n→ Asset Plan duration\n→ Free Job duration\n→ Local Render duration\n```\n\nFür den Pilot jetzt korrekt:\n\n```text\n1.4s + 3.6s + 13s + 10s + 6s = 34s\n```\n\n## Caption-Fix\n\nBeim visuellen Check war die Caption in Scene 3 zuerst zu breit und wurde seitlich abgeschnitten. Behoben:\n\n- adaptive Caption-Layout-Berechnung\n- max. Safe-Area-Breite\n- Font-Fallback\n- Tests gegen abgeschnittene lange deutsche Captions\n\nZusätzlich: gekürzte Overlay-Texte enden jetzt sauber mit `…` und nicht awkward auf „und“. Ein kleiner Sieg gegen deutsche Nebensatzmonster.\n\n## Tests\n\nFull suite:\n\n```text\n51 passed in 3.32s\n```\n\n## Git\n\nLokaler Commit erstellt:\n\n```text\nff5df62 feat: add free local motion renderer\n```\n\nBranch:\n\n```text\nfeat/initial-growth-engine\n```\n\nWichtig: Push zu GitHub ist aktuell blockiert, weil in dieser Umgebung keine GitHub-Credentials verfügbar sind:\n\n```text\nfatal: could not read Username for 'https://github.com'\n```\n\nSSH ist ebenfalls nicht authentifiziert:\n\n```text\nPermission denied (publickey)\n```\n\nDer Commit ist lokal sauber vorhanden, aber noch **nicht remote gepusht**.\n\n## Weiterhin ignoriert\n\nDie versehentlichen Telegram-Review-Dateien sind weiterhin untracked und nicht angefasst:\n\n```text\nautoshorts/review_package.py\ndata/telegram_reviews/\nscripts/generate_telegram_review_packages.py\ntests/test_review_package.py\n```\n\n## Nächster sinnvoller Schritt\n\nJetzt würde ich den Renderer v2 bauen:\n\n```text\nLocal Motion Renderer v1\n→ bessere Mechanism Visual Grammar v2\n```\n\nKonkret:\n\n- echte Objekt-Layer statt grober Rechtecke\n- bessere Auto-X-Ray-Darstellung\n- per-scene motion presets:\n - hard zoom\n - layer peel\n - risk meter fill\n - wrong-answer collapse\n - final map glow\n- einfache lokale SFX-Spur via FFmpeg/Sine/Noise/Clicks\n- danach wieder ein neues MP4 zur Freigabe." } ], "id": "msg_0d1a4d10654d56b4016a118af4fb808191a62d6cf14f15f054", "phase": "final_answer" } ], "finish_reason": "stop" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_2XUgbhw9kh3rtgQRNxuZpgQt", "call_id": "call_2XUgbhw9kh3rtgQRNxuZpgQt", "response_item_id": "fc_0d1a4d10654d56b4016a11903b7a808191bb9d3711e8c12efc", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-growth-engine\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Researching video providers**\n\nI need to gather current information, so using the web seems essential. I’m considering relevant social video providers, and while I don't see a specific web search tool, I can use the browser for navigation. Additionally, I might use Python requests or other methods to access the web from terminal. I'll also check if I need to load any relevant skills, especially concerning social media and web scraping. Overall, I'll focus on researching and updating the registry with free tier provider specifications.", "reasoning_content": "**Researching video providers**\n\nI need to gather current information, so using the web seems essential. I’m considering relevant social video providers, and while I don't see a specific web search tool, I can use the browser for navigation. Additionally, I might use Python requests or other methods to access the web from terminal. I'll also check if I need to load any relevant skills, especially concerning social media and web scraping. Overall, I'll focus on researching and updating the registry with free tier provider specifications.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZA7e9G1QtD4hbQaI1rS2Gt_N4ryh3R8gasJAlNBMA2-828kPAGMQQV3c5uvesxJhhYD2pKokR94mJGzc7UC_XvAERlZZa1MpJkEhdzKtYE1DtC_gtpivsHpgO19WzRgLr0UiXEZktdSRcpR0DqnldDy2Wxm844w_ydKCGNGj06QoDutBz3qgvPjVJ3rgMooLV4f9_vduW6UFabvx-__9P4AZhWBVofBwBl0vugRazhEVZZ_ks4o4opd9pjMQC-ngrQ9wBnMgmdh4DOe98h7K-BbYr0ERcg8ETJlKEbSScfUaAgqBrY1FQlYzgDOhOIwSrea-T6-NXw9V5BGHI08a1aXSkM0D5X4Avexm_40oFuJJqsldf_ufxaaHssk8_i-SXV3zEkeUAyNBac39TrR51Lt5L4wO69DVhfaBSe5rY8YXPAgTiZ5DGDYe1RSeeKbdazkJkOU2nJqDk1WZRtQ7ONzK_gd8qeBZcV5NKH6B2i_R9X8p6IyQzYF6LVYhoq7df9z5PZBdoMVSW5vYiBV1QkMiPMo5LkcxR0eZlLvIx-tC1Htg5HnZZfbCGDl8Qc4nWTByVA2b5k36xTKghta0A-2uQzOkvsIIgfAYM811nAlovimfZ4_M2Z1AwlHiko7Imm4_xOzVOKEzy_2vgByh9JgMP1NTgDqVdW3yhd7iyWGPrt9oqbQNrU98ijGVFhwwW0ZYjTutxDLt7bVBTIdTvrYneWQtLw280UirK4gu0hPM28l5Gd3SykgE6pRObOfxzmApE5Bso87HKotOMdFNDx4IpYryNdBlkdRF-2NAtulN30Co_tCSvKIczhrU6b2hIxiQRBNRzpVkMDlu5tTIX7HysMU5sPnzw_jlFMgCBaO6DFqxb1tKk7dolmiQkPT0-7q56Rhmrp9Ws-jsEdRTBspGVfvmUfihTCA3hDJbgxgck5epVSnPfQloy9xZJWWQp6Ewqvw4IZz92dFHQ7SJFcJE3jAtUph2PJbMvjUHfXaH_A6viu-R9n3OtDKrw_twxROmqsGw1Kfj_qEXeii-eePELZDVhiJSGX4m-ZyUqOHejrjLX3VGQSSZaSQ1eOq-MfnFiKD5aPnnfS0HPgukQGDOz0QqtLvLrmxi-v-1F1KYVtftjkZkyRpwzNPmsdu8ty8LVspmC-5xaj-sL_8dI6W2B1TrTl5yV1D8_yZzBc2Ua_9KNHheMffa0H46i23eHNU6kf2tpv5Nov7yzbOAp2gR5BOH35p4eb579sZar-Yk2qgZRR6rHYNUSgpvt4qp2HyfAGpdySnKPkfikN5zmfUZsCOpQQMcFzElMwYfPJsHxdMW8IC-bODPcpbru20gBT6WlX2UcCwDweQlVCR7vIU80gEsmV-CiBrE7GERD63kjNf5z2oybU54IxspW0WtyHiw-PWHnceQ4D8UqLufzstG0krk4iJ-YHZ9SwQTTdJ5eyagrYu1xY2guD27lqgn9vIKvYiksfbPqZNPkRcnpVpva_NpC-7kxGcTbfAvCwNJ8N3ZTfk3iagFPbw_rFLkwrIqhTGQui3KpLeI_YN0m1DgV1u9WZHJPoca_GTHjy-ieH4qdP84bof_rEehhpJgPLuN4B1QvTpHmtDvaIMe4xVvYOk0L_-I9TuMX7QvqqTjplRso1EwX2vKHY7YaqirR1H4aCj-ugBRs3E-sAzJ7NyuA0n-PCUkSa1YV7sp37NIdfUtx3Sm-24wvfIfNOMeSeJGdYdFsvLAdeFteAGYOG39nOwIikgsJraSANciuiEC8zQCdGgs3gLBZ6VQTNeH8gDddyLI7xSFisbVglSuhOW0TLfzN0UKtOABct8UlAlw-zv5Stj1PzK8_2tGT0kgSVB-oiRzI0Usjf3GgWUYZISaZnRkJ4mKCJisVa8Ennb1PfdsPMMolNjjvT7j3xVJxOUuro9BieGDCjscDJ0nC0L6D7o8G4cTZDaUsrtVwhDJ18=", "id": "rs_0d1a4d10654d56b4016a119037086c8191995124ce9bd4fb1a", "summary": [ { "type": "summary_text", "text": "**Researching video providers**\n\nI need to gather current information, so using the web seems essential. I’m considering relevant social video providers, and while I don't see a specific web search tool, I can use the browser for navigation. Additionally, I might use Python requests or other methods to access the web from terminal. I'll also check if I need to load any relevant skills, especially concerning social media and web scraping. Overall, I'll focus on researching and updating the registry with free tier provider specifications." } ] } ] }, { "role": "tool", "content": "[skill_view] name=social-media-shorts-growth-engine (8,591 chars)", "tool_call_id": "call_2XUgbhw9kh3rtgQRNxuZpgQt" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_uu6MMkTuQw4JDJBLP5FzVNKz", "call_id": "call_uu6MMkTuQw4JDJBLP5FzVNKz", "response_item_id": "fc_0d1a4d10654d56b4016a11903f37a88191bc33bf555771b8aa", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"web-scraping\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[skill_view] name=web-scraping (5,754 chars)", "tool_call_id": "call_uu6MMkTuQw4JDJBLP5FzVNKz" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_EJDz0ZsP1y8hxElQKGrthAVk", "call_id": "call_EJDz0ZsP1y8hxElQKGrthAVk", "response_item_id": "fc_0d1a4d10654d56b4016a11904365b0819182a5048114ab0955", "type": "function", "function": { "name": "todo", "arguments": "{\"todos\":[{\"id\":\"research\",\"content\":\"Free/freemium KI-Video-Tools für realistischere Shorts recherchieren\",\"status\":\"in_progress\"},{\"id\":\"decide\",\"content\":\"Gratis-Workflow-Entscheidung für AutoShortsBot ableiten\",\"status\":\"pending\"},{\"id\":\"implement\",\"content\":\"Provider-/Free-Tier-Registry und Job-Specs im Repo ergänzen\",\"status\":\"pending\"},{\"id\":\"verify\",\"content\":\"Tests, Artefakte und Git-Status verifizieren\",\"status\":\"pending\"}]}" } } ], "finish_reason": "tool_calls", "reasoning": "**Searching for information**\n\nI think I need to do some research, which probably means I should utilize the browser search. It seems like the best way to gather the information I'm looking for. I'll start by searching the web for relevant details. Let's see what comes up! It's all about finding the right sources to help me get the answers I need.", "reasoning_content": "**Searching for information**\n\nI think I need to do some research, which probably means I should utilize the browser search. It seems like the best way to gather the information I'm looking for. I'll start by searching the web for relevant details. Let's see what comes up! It's all about finding the right sources to help me get the answers I need.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZBDW362V26kh0tgD5Q2s2N7gb8hXisi5s4PWsCVLKe_qxgRtRQJ2qX1RotcsdAEZFSduM9iYKylgHjQ1ebue9mjTdBjXQa7YByg53RRxA2GQkqkhK4GSulkhrsUfmhzT26kR3A1HZ_WePzIptzD6aPz8hQ4V_-XwhgyPAq8_DvZHL0kvd-V0lWK7OmjjaE4onm8Fth0np3xJg9OvFQFM9iiO4FAOXJyareIxykDOiVezVejjUhJYFP_LSUdAmY1H3WL5J-FruiFK6Ez4q1TtFWVwMjmO9m-CTGvuWJ152ZGFxuk4_4p1FunagGmM4aMG6OBOAYQxpdC42_AY1i6ztgX9J_aoOS6R25kq6csdXxfuDCkBYCTdr-rZxT8U2utL46zp6ykyglM1i7w3DqE8yhcRyxfmi4STsxzn9XKS5bOfwK-F8uIvDk_hzRDW-7uTUGGQckVIZ-0Ezt261i21-Gua0VqooxlxlCpEu26YRLhCnPoYdhRcnSzNzVW9_aMXH6zkKN4q6losn5SoVQf8eEbBuoIg3Oys54koblvTCKaYuj8eYoWro2-AIDVfMpKAHQSnay5NqyhVLH8XiSY-ha8QTy9HjPpLFAePtmYqfB4v1sPP-dO3TG2zUfz3Y2dSUHmuu8Tb5cGD-q99gEBjLMEu1TfbVKHWRvmNvXp9lef9p-Wl_WzV27Lt58gQlrbY-pCPzDnIv1IFPShe2CjeVv_Szz2o1DFJMQDPsvyc8__VlY3eq0kUTXkYPat4cnFhVzjPTIlyLZ8dl3fN59LSOjnuxEYZL2tAmONoO8ptrchTAOrrNpCyMQpSbrxw0eocQ-mUDbRuH4M8Cs1ZW382FJm2gm84RamKFmtVljYzGi2G2kiTDkmyLbGtVQK9MCZSEUGlBSXK9mDqkz5S-MMUTqHRo-RpPv1h3U_Gx8-yS19aDILfxLWeEjhNLjV05aAQJ-Pp6GjmIeeORp-KpHDMmyPou72T2tbOFyBRiIXKys75R8=", "id": "rs_0d1a4d10654d56b4016a119042194481918fc9af8136f91f3b", "summary": [ { "type": "summary_text", "text": "**Searching for information**\n\nI think I need to do some research, which probably means I should utilize the browser search. It seems like the best way to gather the information I'm looking for. I'll start by searching the web for relevant details. Let's see what comes up! It's all about finding the right sources to help me get the answers I need." } ] } ] }, { "role": "tool", "content": "[todo] updated task list", "tool_call_id": "call_EJDz0ZsP1y8hxElQKGrthAVk" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_5xnEAlvR5BPXMGOOmX6TzNcq", "call_id": "call_5xnEAlvR5BPXMGOOmX6TzNcq", "response_item_id": "fc_0d1a4d10654d56b4016a1190484b7c8191b58a083f0167feae", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://www.google.com/search?q=AI+video+generator+free+tier+Pika+PixVerse+CapCut+2026\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[browser_navigate] https://www.google.com/search?q=AI+video+generator+free+tier+Pika+PixVerse+CapCut+2026 (920 chars)", "tool_call_id": "call_5xnEAlvR5BPXMGOOmX6TzNcq" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_3cT1j4EhetqJhjCdFb9PVYZy", "call_id": "call_3cT1j4EhetqJhjCdFb9PVYZy", "response_item_id": "fc_0d1a4d10654d56b4016a11905270008191a09ad3b6a0864349", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://www.perplexity.ai/search?q=AI%20video%20generator%20free%20tier%20Pika%20PixVerse%20CapCut\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZBSswFt1P3ojkDlPkDkeJBTOF7SVLkPv9Ppff697vTOIMRnhKg12EzsFB5Jv3zxa_zYrFxcMl_N2P5F47k5UEuZtN9B_Am68dGvk-g-Q_dQICBKpPuUVi_HBa_LSM2SdxbUpBG1WGDJaxdaC1SHQsrdF6hisRNPwcbsM3XyHoosNnGd_Rpjqc65Ny1HhcDdrkYJAspvKJN8aj_T9J-JeRFWTIbkbKm8sQg_f-QLYL-0EC0LUQnUjf4qYPtGVO1BztEs5kT-V1cCoofMdrmWhzj0LvaTKh1gCTQ-2oH5UBL_dt5TWcKQ9w510ZwnMpcFP0-uBseEZVL_5VEWZ9SeuguBfVbBVjvgmW1pZh5zHR6IvW_QmGt7nhwe10lYbDXQRmeME2qugColG9215wGT4pUWC5wv_jxh6BGp5Z1-uTU742hqZAXCfNdN81-o6ffGGXoWs4263xPEUEcRIc_648w_xUwYG_5r4BmmAg0ClULMqLS54Zoa2lltXSZSQFhjZNJhR-43gnbPXi3iTZmh2mm8JoZfjrJ46jtDIt3Fl3mGjCaZh3ommFTli617O4McwLJtFkMFnzaIKf0jGWS6HeLOYHg9vvHljy3OjE-uOzAqWBGYv8N7nttzJVKp9cXxJzhvaHyKdRwGJeXlR0Db0NuoQlZdbem042akLFuItu2PM3CIgOs3Z99VKp2qiccQGvvVRCeqyC4F3m_0BefEVrwypcObAT_-Rqyme7gzznWakLGpV6bm42wKEGKw4J9vZy5_B0ZbtzjzUe15as7TNPDEsi6kqOhbSw-eUUPdGdLaU-n2kaaA7dGQ4JhNHh1qckJr7LPrL4Z0KWLCpz9ErZk1xxQTszWo-eDgTZo8oqhZuA4MyZZ6fw9jCU-q4jt2-2ow293Qn4ix6iEA6AdP98N-fwwYuG9GPHm44Ez_TPJDaMF-EaNMofIwXMdPa-lNVRsRjQ6M5zeZugqlj4o5CQyZLA==", "id": "rs_0d1a4d10654d56b4016a119051ca988191aeb6764b835189d5", "summary": [] } ] }, { "role": "tool", "content": "[browser_navigate] https://www.perplexity.ai/search?q=AI%20video%20generator%20free%20tier%20Pika%20PixVerse%20CapCut (922 chars)", "tool_call_id": "call_3cT1j4EhetqJhjCdFb9PVYZy" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_GZqN5iJUZRjYV7WOgw8eWUrm", "call_id": "call_GZqN5iJUZRjYV7WOgw8eWUrm", "response_item_id": "fc_0d1a4d10654d56b4016a11905b765c8191ba368c92814d36cb", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://pika.art/pricing\"}" } }, { "id": "call_8AxwgSUcPXB5tkb68DlRrPfi", "call_id": "call_8AxwgSUcPXB5tkb68DlRrPfi", "response_item_id": "fc_0d1a4d10654d56b4016a11905b76888191a413be6a5e801c60", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://pixverse.ai/pricing\"}" } }, { "id": "call_a31wLqT0Ct8mGVwXxJm3CHdU", "call_id": "call_a31wLqT0Ct8mGVwXxJm3CHdU", "response_item_id": "fc_0d1a4d10654d56b4016a11905b769481919ec78b135958c28a", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://www.capcut.com/tools/ai-video-generator\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Exploring alternatives for information**\n\nI need to find an alternative approach, using specific web pages directly for accurate information. I'll consider using a browser or a terminal curl command to access these pages. I'm particularly interested in finding current facts about CapCut AI video generator, Pika pricing, PixVerse pricing, and possibly Hailuo, along with runway. I think I should focus on official pages that list credits and other relevant details. Let's open those official sources!", "reasoning_content": "**Exploring alternatives for information**\n\nI need to find an alternative approach, using specific web pages directly for accurate information. I'll consider using a browser or a terminal curl command to access these pages. I'm particularly interested in finding current facts about CapCut AI video generator, Pika pricing, PixVerse pricing, and possibly Hailuo, along with runway. I think I should focus on official pages that list credits and other relevant details. Let's open those official sources!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZBboAYDo3R19sN8APkcaLK30a49o8FDnCte2PY58eKckiKDq-h4UaTNF6T57COwd7lzuRn3gB0SDXsJWrKny4YuUB_rcK885K0aRVZNfPR4cORez-qm4HuHfVI4rXA52jQxAxdH_9oBhXQ9Xq5ofnV6s5Y8Nn_K17oK9HokuQ5VhaTz8RI0IORlHMUYBrFB7FVRQ1-cbAt8zrOMNJKdg3KMSIn8TrdtI4BKRAuBcN8jKD7lxb2HkXr3LpNiqEcTFKsnxVsBlv6cougazicFpqCRdHqIXlhu4Lai11aXVoBKkUpL7ame7p5TNjDKhaMkJ7KfjhSUK9dsFE43qouhWqzrvvpUXeFwGQU3RJkDxIK_s41NmclZ3JBFHk5plhpSrGWcDHCstYjr-1pMV8eG40YpbFAcGDAWoUOYyDNQWUuCvCICIE4M51NJteAnvGoCu4w6kpZbf0qMdUAayht2Ye2sr4sI6OSY1XnxxXtP8IigXR_arp2sMt2AsktqHWL8S3BLoN4uZj73hzZSytB88PGYGlws56EsOwICWsRcEwkj7KCK20tfmTWfCV3HrUwfnjArZoTrDrjgTqE9YbA75_72Ap4vRLZ0q1oW_uKXXeIdEoZkxvAr-tD58_A3g2PCgT-XD8ibJ3i-kBSpRmfiXqD8C-mTRokabKLZ5KWv3ECavKl693hsrC2wD_8ui0yCeDloG2vjxHI_KAzLgXiutv7D_4Ns-gjccDAMf4YSw_ewmawCp7o9h5eyCTkAHr2few2vLLUi8caG0s4DBOPibyojglyz2xOdMM7g0RwH2rkPNPaG4s_V1CAq4ZljMcpbsqW8muhgpMfjjmrumVJ5U1EqQtx_Zn7RQnWLw7JeNuxM-NwxXjajhgXhhmA_TczSjoosQYKeFdTgjGpiPDK86S5vybE0VO0Wi6fzBCwzmfwdw5Zo5WVznuRGWskDdWw_Ksp5J_qGEApDQSJI9qLa8zZRbA0UmHmC7KVeAWhwBZQCWwyclfoNBtHOJ5LjkwIc1PuOFYawmgad83ePIBzuQ_BSV3if9b4ne4jaqT5Dw0HC6UifC7vVM4yh7x23-BSQy_RRZlE7OXkZzt_esJizHg1DrE1hktgW1ICfep918RxavQlZxzInDmN0Kb6jVCoY9AbYarXGuL6MvB6zN5JQ6QAhPwjCzLeMREAWbBmcwMzhlGRw5cxd3HVtllE7-PgvflJ3DcOHnQNnlXQQHWNBkKlew5EXFGjb3Ag-IWggVh5lSzc1PUEDF-bvRZN9s2-iinGxvwKLWkf7aErIKdbyqAmYO6SbnYxyAbH1NqzR2buOJxQ=", "id": "rs_0d1a4d10654d56b4016a119058334c81918e2e6739f7199693", "summary": [ { "type": "summary_text", "text": "**Exploring alternatives for information**\n\nI need to find an alternative approach, using specific web pages directly for accurate information. I'll consider using a browser or a terminal curl command to access these pages. I'm particularly interested in finding current facts about CapCut AI video generator, Pika pricing, PixVerse pricing, and possibly Hailuo, along with runway. I think I should focus on official pages that list credits and other relevant details. Let's open those official sources!" } ] } ] }, { "role": "tool", "content": "[Duplicate tool output — same content as a more recent call]", "tool_call_id": "call_GZqN5iJUZRjYV7WOgw8eWUrm" }, { "role": "tool", "content": "[browser_navigate] https://pixverse.ai/pricing (1,085 chars)", "tool_call_id": "call_8AxwgSUcPXB5tkb68DlRrPfi" }, { "role": "tool", "content": "[browser_navigate] https://www.capcut.com/tools/ai-video-generator (8,498 chars)", "tool_call_id": "call_a31wLqT0Ct8mGVwXxJm3CHdU" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_2WSHT6ZpBrx4WRjbfnIQWGVW", "call_id": "call_2WSHT6ZpBrx4WRjbfnIQWGVW", "response_item_id": "fc_0d1a4d10654d56b4016a11906b3dcc81918d93fdb59db80b12", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://app.pixverse.ai/pricing\"}" } }, { "id": "call_Wn5V1FrDzZ2l2gfar7Wgvwfs", "call_id": "call_Wn5V1FrDzZ2l2gfar7Wgvwfs", "response_item_id": "fc_0d1a4d10654d56b4016a11906b3df8819184b071aaf42bafea", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://pixverse.ai/\"}" } }, { "id": "call_AOLghzHwF8OhRUD1kSqD6Tj1", "call_id": "call_AOLghzHwF8OhRUD1kSqD6Tj1", "response_item_id": "fc_0d1a4d10654d56b4016a11906b3e188191b05aae1a5d8c011e", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://runwayml.com/pricing/\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering multi-browser navigation**\n\nI'm wondering about using multiple browser tabs in parallel. 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It seems like the last action might overwrite previous ones, but it might still provide enough output. I should try to focus on locating PixVerse and perhaps explore the pricing root there. I need to be careful with how I navigate and confirm that each step is yielding the information I want without losing anything essential. Let's see how this unfolds!" } ] } ] }, { "role": "tool", "content": "[browser_navigate] https://app.pixverse.ai/pricing (1,326 chars)", "tool_call_id": "call_2WSHT6ZpBrx4WRjbfnIQWGVW" }, { "role": "tool", "content": "[browser_navigate] https://pixverse.ai/ (8,594 chars)", "tool_call_id": "call_Wn5V1FrDzZ2l2gfar7Wgvwfs" }, { "role": "tool", "content": "[browser_navigate] https://runwayml.com/pricing/ (6,054 chars)", "tool_call_id": "call_AOLghzHwF8OhRUD1kSqD6Tj1" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_4bKCeBhkQpzcYqi4AeJfGoJD", "call_id": "call_4bKCeBhkQpzcYqi4AeJfGoJD", "response_item_id": "fc_0d1a4d10654d56b4016a11907a8dfc8191932fee24dd610175", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://search.brave.com/search?q=PixVerse+free+credits+pricing+AI+video\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": 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"id": "rs_0d1a4d10654d56b4016a11909c8bc481918548d75b7a966e09", "summary": [] } ] }, { "role": "tool", "content": "[browser_navigate] https://app.pixverse.ai/ (8,447 chars)", "tool_call_id": "call_81cxqNuwd1InmB0KMOAMCMAY" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_Y69A14B8rEVESv8sXl2VsZgW", "call_id": "call_Y69A14B8rEVESv8sXl2VsZgW", "response_item_id": "fc_0d1a4d10654d56b4016a1190ac8ca88191aff7af425869cd30", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"test-driven-development\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Evaluating video tool options**\n\nPixVerse offers 90 free daily refresh credits, which is great. I suspect Pika might work without an account, but I need to check if it has an API. For CapCut, I need to figure out the manual process since there are no credit details. It seems I should establish a process for using these free providers effectively, including a workflow for exports and external AI video job specifications. Additionally, I need to look into my code repository to track changes and implement new tests, maybe using TDD again.", "reasoning_content": "**Evaluating video tool options**\n\nPixVerse offers 90 free daily refresh credits, which is great. I suspect Pika might work without an account, but I need to check if it has an API. For CapCut, I need to figure out the manual process since there are no credit details. It seems I should establish a process for using these free providers effectively, including a workflow for exports and external AI video job specifications. Additionally, I need to look into my code repository to track changes and implement new tests, maybe using TDD again.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZCspLEdNydgzdDJsLIYYSbIjqHLPvBxpRIQB-ziM6IoFNKBC3iHMqrlmlN4WgUIu3273eFisI0IX04H8uMTJZ7BhyQEVP5ieXNM6znl-Uxr14bz1PuouzRnIaxqZisni5Z6FGRNP7-f0Q8_6yOakIOw-Hb1EfxesGna0kJwoL9hIu_zPDin1kNKyHZuYoeF_NeJd7dMRJOE9ZKlfFjVx3rPUIb9b4rCTQG9OE24X1w8Ar-MQY515Yl2RoqVHct3FcFY442zVLC7bKoDWdfzCYB9rMofjnEfTdN3CdHCDkz788fR_tASnM7oxCAWe6JOWFplIJOPR3hMyRmzMqfUg4wwPiUmAEeLdjikF8XA9d0g1OeQCWq5_DT8N4xVdEJ-2BBW4pT4CAKi9N1KtBOB0_jTf19AYDAAlsL86Qwassf4-v39gU6bCUR1ueuoIpSVRuSfZ9BxMdqdvF-g280lJEkdRlSDsumw2eL049R6aYXb58X0-U3wP4u1bXVvs_kARlnykFb_jJLQLhbEdgP_tCAAQ7WuTOnFLQlgmjEPFiWlrmVQLcTbn66zVp-d_OaKn4x_lSSNUBilOn3JzNx9ODKhCPPRrqsyZAEmbhfCcXBjznQvSDk8z97iAvLMkHAagRQaUi-qCpDnpUkyMm3NR2QYXv4HK2ume0Stngvjo1sAw7qggPTr4GwlYsYfyQHEVpcUQ8eWdx1oKanIrM8mNrLQme0CovwgPF_x6YUxprSAx2jZJ7qRq6v12ykRbG2Kn6BygkrSrd9elJZ0X2BfiqIVqhxHNyGJ_Y22VQTHTQAnpyGyqcHU2lCNhvrCkLv0Y8qz7wOHp4Mr3hSP7GRWKntieX_mQD9MKdprLDrh3OzaCHxXuZufiC_EtTJ0vSZUBs9mwGRqKzuNzDl-rB_l8M07lk2DyEPWLMQ0lGhonMc9rfY3Wv_NGMA8xGcGgwHwzj3okO-thR87ci57n4k_boGQrHGfQT8WCr9Y_a_O077PEqMCO_UFybxX9a558B8LRLGlN659TznrbIrKICYdub5ZWEtBwuuED8AZ6wntzPEYB5yjCx_x_spzCc2BdCVL7MYYHV4WwGA16XZPXQvz_TeqhtqIxf7GGFR0nYnh4oUsK8nRb3EO5fJZaspaFYd8vqatvyCKAfd4d6bAxO4MA8ewY3zNGLJIBqI47v5l1wYZByvx8UcJ_TmMqgC3Mdk0Dk3ap4CIMiXNXABzfuxHP9HVV4FdxZpVHj89hXlXe-0vwKpQQu79dc_N5V4-Rv4GowoOLlaikdwl1eiI91qVzLMYthvqEyjL1n9gwxXkmMDEm4Av-j1A89pnEbBvmxTzaMq9B2Euqb6Kwe7gCJ7h46JZrQX7d_1FL0vdng7LVB2j08QUyu8fF_EKp-yMCdL2xWkzBepKB3aL-xinUN_QUn_L-ooLWtBVtbbX0OS6e_VWtXCVWE0WN80VQbawLCcZ_xvVOetuMlKTGHXLbC99EAaIfRKdfBpH38xFfn9rsexjBAxzYYHknFgsZyVIajGneD10sSaywxppcUb8h8Q7fNnFvySX0yvL9sBAjFNXzfrcd5NnWVcujM6DyKDGowHvMrUEiD9L8zKxFoebsBvGewbz5rIJp_YEWD-VtXvrZjo6ZkIwqGTixJRi_F1pTxSv6oepFpgqi1UIdFbmdThXDQ7hVO3dkBEGSXu2WjkQ0vlpfOkKJWdh_kuy_K8nkYHh_CLst1eWTL2mRwuOYtaiozDSDFDDjLGgULYWENEtkM0Gk_1vlERlPFGnp5LFMLcI1tMu8t2hWijp2a_t6jb2aCvItHN3i9IN3V9kxvgb60m_Tp5jYYdtfIU0fl64Zy1NAHLm16dwLBlHqw2s4AIw0HmBQw==", "id": "rs_0d1a4d10654d56b4016a1190a4a128819198ce5df3e89f908c", "summary": [ { "type": "summary_text", "text": "**Evaluating video tool options**\n\nPixVerse offers 90 free daily refresh credits, which is great. I suspect Pika might work without an account, but I need to check if it has an API. For CapCut, I need to figure out the manual process since there are no credit details. It seems I should establish a process for using these free providers effectively, including a workflow for exports and external AI video job specifications. Additionally, I need to look into my code repository to track changes and implement new tests, maybe using TDD again." } ] } ] }, { "role": "tool", "content": "[skill_view] name=test-driven-development (11,198 chars)", "tool_call_id": "call_Y69A14B8rEVESv8sXl2VsZgW" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_ZsqByl8LFs10sLmlevMKLdFj", "call_id": "call_ZsqByl8LFs10sLmlevMKLdFj", "response_item_id": "fc_0d1a4d10654d56b4016a1190b322708191a84efeac2f8d763b", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git status --short && git log --oneline -3\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Inspecting the repo**\n\nI need to implement something, but first, it seems like a good idea to inspect the repository. I wonder if there are any important details or documentation I've missed. By checking it out first, I can ensure I'm on the right track and avoid potential issues later on. It’s always better to gather all necessary information before diving into an implementation. Let's see what I can find!", "reasoning_content": "**Inspecting the repo**\n\nI need to implement something, but first, it seems like a good idea to inspect the repository. I wonder if there are any important details or documentation I've missed. By checking it out first, I can ensure I'm on the right track and avoid potential issues later on. It’s always better to gather all necessary information before diving into an implementation. Let's see what I can find!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZCz9KlVmEGmdRsJbC3aH-PLsq4KgW6z1YE1gu2LztjunF6GIaiXqJK0S423l4w9s_uBF6YiQwAAWEdkCzqknSwMOZdX3m4NROqSRab7JS4fYopyfAcCu-V3tZRiUOWFdLE_NEO9e3gGlhYTPOIYuJOYJC3OY7ya9hnDqcwUkhBdJwIOVM_iTPA3EOq6aSTf3zoYQAmLcXpg6ZL5XNA6oJSnXDnwob6C-rLN4CVOPtsb4IzHBwkrkU9OCtrhVTYE3eKYQbpr0CdfwAY11y8H6upD3thkIuOn0yjvyphokHO72siIKKG872bQaByqiPbU7Db_zEzQeyyD-U3RwV7mzxReh2wft05HEbzDS3DVwjyMQl4rTQTfANZY8Ihx6CcgLYkf8n8CESp4Lh8t4Kl4uSwhDTMjdGoQJSJ21R4HJzZYK36uk-av21hNJCMgcfYDlQje5k_rfs2i8IRJB2AieBmDNXLzLx5CqVFpHuzrOcYeceXhuh91kdvZdUAsZi2ZhzYrsNSIT6xOZ3_PtmZVTmqtwFpjGRthdWKw9dZSppGJsmTLLVscDC9h4NXPu96Yc6TdqkEcejafzL5LrsdwQOjKWyhMbNvRmPbDP81_5PJUbLZkAXOZyr4V22DvDefHEupO5UyDoGVxmj_cB4CTipfbFiLg254F2aQqJ98nchI1wmFJOsZN2dzw2WCafze0_fS-CkYOk8PiYsFaWBUfqdWZc_M8Lyji9BXXli8q0uitrhq5454qVTnb96IwWUe2tjzNqeb6o6guO50dggGoDMpKjUW_07StyihbuowysPw0l46Jq_690kq11q5VidJCzLNT8DFbkLhdUQaSyDTcOOA8L4qOSzHYiCg_BQeB74tnfgBAp35ul5UxLotiSVzy0iOcWxAsyZMp_ppoH0ZEesc53-C6wYCuj7R811Ki6DBE0ffjM2yV3_eRbNZ9eOBiAiyn7NNniGSDg4vWOFF66gmqyg==", "id": "rs_0d1a4d10654d56b4016a1190b11f68819184f17310dabf66d5", "summary": [ { "type": "summary_text", "text": "**Inspecting the repo**\n\nI need to implement something, but first, it seems like a good idea to inspect the repository. I wonder if there are any important details or documentation I've missed. By checking it out first, I can ensure I'm on the right track and avoid potential issues later on. It’s always better to gather all necessary information before diving into an implementation. Let's see what I can find!" } ] } ] }, { "role": "tool", "content": "[terminal] ran `git status --short && git log --oneline -3` -> exit 0, 1 lines output", "tool_call_id": "call_ZsqByl8LFs10sLmlevMKLdFj" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_oL8oxs2G4u1W3wAUg2CqAIjp", "call_id": "call_oL8oxs2G4u1W3wAUg2CqAIjp", "response_item_id": "fc_0d1a4d10654d56b4016a1190bcbd608191911578b12244c567", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://lumalabs.ai/pricing\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering video provider options**\n\nI'm thinking about implementing a provider registry. It seems I might need to compile research into data. I'll create tests for the free AI video providers to select those suitable for realistic scenes. It would be helpful to generate external handoff specs and use source URLs with observed details. I also need to follow test-driven development along with adding options like CapCut, Pika, PixVerse, and Runway. These providers have usable free tiers, which the user wants.", "reasoning_content": "**Considering video provider options**\n\nI'm thinking about implementing a provider registry. It seems I might need to compile research into data. I'll create tests for the free AI video providers to select those suitable for realistic scenes. It would be helpful to generate external handoff specs and use source URLs with observed details. I also need to follow test-driven development along with adding options like CapCut, Pika, PixVerse, and Runway. 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It seems I might need to compile research into data. I'll create tests for the free AI video providers to select those suitable for realistic scenes. It would be helpful to generate external handoff specs and use source URLs with observed details. I also need to follow test-driven development along with adding options like CapCut, Pika, PixVerse, and Runway. These providers have usable free tiers, which the user wants." } ] } ] }, { "role": "tool", "content": "[browser_navigate] https://lumalabs.ai/pricing (8,871 chars)", "tool_call_id": "call_oL8oxs2G4u1W3wAUg2CqAIjp" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_M8BAvPiU6Jim2EKawXiX3lSY", "call_id": "call_M8BAvPiU6Jim2EKawXiX3lSY", "response_item_id": "fc_0d1a4d10654d56b4016a1190c22e148191b1ac0f344228c58b", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://hailuoai.video/\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZDCgNipEXMJhF26NOIjZni6twtrRsJ0ht0lc2ymcWAK4sDHH5bQAwojiwGB7waREyEjiZdS3YiaU98GKb0UGxPQqoa6c3OHo12D9qgFMRrkkgM7InTETDG3vyVW040sQYqLfmdZnkm_5eVkKYqy4awngHwckkjFGz4nQZDFL9lqY1SY8bSqnetyrXoIqNv5H9INPhWkZ08-1H-_pVg8P1AAMXEty04UF7ZtqzfawwNZxs8bxx5h-XdaTALfNCd-WBcqanUrhDr_tGAmkzs3QLRkf0mG149_eGscx3eARYyZ5_qoxXAWwHNszqr2ZCnAQs14c09kxSmdbhFOziGg0QRPT1Xl9H9doar55dPP8-yaYMdtgN9IvvRDxumWpFqTw9Jn1CgR8To8g71qTSajqXmM3MjdJNyc2O_CNRVQ2sNulh61LuEITXs230-urj2-eL1SvF2u6nRujCZ4sIRoLVQtwBCuF61PLoSvafOID_MbOPsRsEyw4ubKCcQcznppW9Ci6Q0DNwPv22b3j0msdIQX8puq_G_ry-PlYGp-D_opKDT9pU3fCejBSHPx-h-KWqy4S01_wJ4rOD1_nouZ6pLMPsZhugSVx9tpICc-jSmaiqpzXVBvr96CYTNstJzJ5hqjP8C290rwwBqHFjKN7gXhD8POuTtYeT20iW0qqqqCybO4ZOPIRDrKo_iAdGbG8gQJvtHWMa05RYqkXTnRpRwZ7eQjGV3ju0gj5F-liUxn7qj0bjbarMvxbRD1oy3gC_-YdEt8k7N9bnVVXTxrmkKsQRhwnECyG3596E8Kh3Sgmk-tyWYkz40rAXi-YgbR8EdD97W_kTzcRrQ9Yk0WVWOxaXi97l_XSoEc5Dmp7xGsDZHGwroZvDmoF3y8KLODZNM1mcD3ENFx6UvoUTrCYpF6pxsEsht08YPLfMzvbi3YtthasmO40V8GDO7zs1gL9523ZoXZTNrdS4qSO_DtEJ0rlmLv4Db2ApxxARxj42nAy4TnZSPIod82UDSwe-3OqW4NU6UkIOhc2myumCnFdReVhQ==", "id": "rs_0d1a4d10654d56b4016a1190c165a48191af556866bd7b2f60", "summary": [] } ] }, { "role": "tool", "content": "[browser_navigate] https://hailuoai.video/ (8,379 chars)", "tool_call_id": "call_M8BAvPiU6Jim2EKawXiX3lSY" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_F3XYnzi6kHxpLuqIMNh8uh1f", "call_id": "call_F3XYnzi6kHxpLuqIMNh8uh1f", "response_item_id": "fc_0d1a4d10654d56b4016a1190d5cf8c8191b84e62c36da76a6b", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Free/freemium KI-Video-Tools für realistischere Shorts recherchieren\",\"id\":\"research\",\"status\":\"completed\"},{\"content\":\"Gratis-Workflow-Entscheidung für AutoShortsBot ableiten\",\"id\":\"decide\",\"status\":\"in_progress\"}]}" } } ], "finish_reason": "tool_calls", "reasoning": "**Planning a video project**\n\nI think I need to create a realistic video plan that combines AI-generated clips from a free tier with a local renderer. 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That's a good hybrid approach! I should start coding now and make sure to use fixtures to streamline the process. And, of course, writing tests will be essential to ensure everything runs smoothly. 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[100%]\\n55 passed in 3.25s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_KWiLkUkuCOgkhUGTNUvCl0VQ" }, { "role": "tool", "content": "{\"output\": \".gitignore | 1 +\\n 1 file changed, 1 insertion(+)\\n M .gitignore\\n?? autoshorts/free_ai_video_providers.py\\n?? autoshorts/review_package.py\\n?? data/free_ai_video_handoffs/\\n?? data/telegram_reviews/\\n?? scripts/generate_free_ai_video_handoffs.py\\n?? scripts/generate_telegram_review_packages.py\\n?? tests/test_free_ai_video_providers.py\\n?? tests/test_review_package.py\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_r1LPjvqWZTa7iHXr7QkJ0KgJ" }, { "role": "tool", "content": "{\"content\": \" 49| \\\"ai_video_jobs\\\": [\\n 50| {\\n 51| \\\"job_id\\\": \\\"scene_01_free_ai_video_handoff\\\",\\n 52| \\\"scene_id\\\": \\\"scene_01\\\",\\n 53| \\\"asset_mode\\\": \\\"cinematic_ai_video\\\",\\n 54| \\\"status\\\": \\\"manual_generation_required\\\",\\n 55| \\\"duration_seconds\\\": 1.4,\\n 56| \\\"aspect_ratio\\\": \\\"9:16\\\",\\n 57| \\\"preferred_resolution\\\": \\\"480p_or_best_free_available\\\",\\n 58| \\\"provider_order\\\": [\\n 59| \\\"pixverse\\\",\\n 60| \\\"pika\\\",\\n 61| \\\"capcut\\\",\\n 62| \\\"hailuo\\\"\\n 63| ],\\n 64| \\\"providers\\\": [\\n 65| {\\n 66| \\\"provider\\\": \\\"pixverse\\\",\\n 67| \\\"display_name\\\": \\\"PixVerse\\\",\\n 68| \\\"url\\\": \\\"https://app.pixverse.ai/\\\",\\n 69| \\\"free_tier\\\": {\\n 70| \\\"daily_refresh_credits\\\": 90,\\n 71| \\\"signup_required\\\": true,\\n 72| \\\"best_use\\\": \\\"realistic text/image-to-video short clips\\\"\\n 73| },\\n 74| \\\"risks\\\": [\\n 75| \\\"terms and quotas can change\\\",\\n 76| \\\"manual account/login required\\\",\\n 77| \\\"possible watermark depending export path\\\"\\n 78| ]\\n 79| },\\n 80| {\\n 81| \\\"provider\\\": \\\"pika\\\",\\n 82| \\\"display_name\\\": \\\"Pika\\\",\\n 83| \\\"url\\\": \\\"https://pika.art/\\\",\\n 84| \\\"free_tier\\\": {\\n 85| \\\"monthly_credits\\\": 80,\\n 86| \\\"max_resolution\\\": \\\"480p\\\",\\n 87| \\\"text_to_video_5s_credits\\\": 12,\\n 88| \\\"watermark_free_claimed\\\": true,\\n 89| \\\"commercial_use_claimed\\\": true,\\n 90| \\\"signup_required\\\": true\\n 91| },\\n 92| \\\"risks\\\": [\\n 93| \\\"low 480p free resolution\\\",\\n 94| \\\"monthly quota is small\\\",\\n 95| \\\"manual account/login required\\\"\\n 96| ]\\n 97| },\\n 98| {\\n 99| \\\"provider\\\": \\\"capcut\\\",\\n 100| \\\"display_name\\\": \\\"CapCut AI Video Maker\\\",\\n 101| \\\"url\\\": \\\"https://www.capcut.com/tools/ai-video-generator\\\",\\n 102| \\\"free_tier\\\": {\\n 103| \\\"hd_export_claimed\\\": true,\\n 104| \\\"credit_amount_publicly_clear\\\": false,\\n 105| \\\"best_use\\\": \\\"editorial assembly, templates, captions, quick drafts\\\",\\n 106| \\\"signup_required\\\": true\\n 107| },\\n 108| \\\"risks\\\": [\\n 109| \\\"free quota not clearly exposed on public page\\\",\\n 110| \\\"may upsell Pro assets\\\",\\n 111| \\\"manual export required\\\"\\n 112| ]\\n 113| },\\n 114| {\\n 115| \\\"provider\\\": \\\"hailuo\\\",\\n 116| \\\"display_name\\\": \\\"Hailuo AI\\\",\\n 117| \\\"url\\\": \\\"https://hailuoai.video/\\\",\\n 118| \\\"free_tier\\\": {\\n 119| \\\"default_visible_generation_cost_credits\\\": 25,\\n 120| \\\"signup_required\\\": true,\\n 121| \\\"use_only_existing_free_credits\\\": true\\n 122| },\\n 123| \\\"risks\\\": [\\n 124| \\\"do not buy credits\\\",\\n 125| \\\"free quota may vary\\\",\\n 126| \\\"user explicitly wants no paid Hailuo credits\\\"\\n 127| ]\\n 128| }\\n 129| ],\\n 130| \\\"prompt\\\": \\\"Vertical 9:16 realistic cinematic short video. a realistic creator at a desk late evening, laptop open to an AI chat, thoughtful but in control, hands moving between keyboard and notebook. Mood: focused, modern, high-retention social video, dramatic lighting simulated with gradients and shadows. Scene intent: 3D car x-ray with price tag layers and risk meters freezes mid-action with warning signal. Camera: slow handheld push-in, subtle parallax, natural micro-movements. No captions, no readable text, no logos, no watermarks. Leave clean negative space in the lower third for captions. The clip should feel like real b-roll for a mechanism explainer, not a slideshow.\\\",\\n 131| \\\"negative_prompt\\\": \\\"no readable text, no subtitles, no logos, no watermarks, no distorted hands, no fake UI text, no slideshow, no static image, no uncanny faces\\\",\\n 132| \\\"overlay_text\\\": \\\"Dieser Occasion-Käufer denkt, er spart 4'000 Franken.\\\",\\n 133| \\\"free_tier_guardrails\\\": {\\n 134| \\\"do_not_buy_credits\\\": true,\\n 135| \\\"use_only_free_daily_or_monthly_quota\\\": true,\\n 136| \\\"avoid_pro_templates_or_paid_assets\\\": true,\\n 137| \\\"export_without_baked_captions\\\": true,\\n 138| \\\"final_captions_added_locally\\\": true\\n 139| },\\n 140| \\\"manual_steps\\\": [\\n 141| \\\"Open the first available provider in provider_order.\\\",\\n 142| \\\"Use text-to-video or image-to-video with the prompt below; choose vertical 9:16 if available.\\\",\\n 143| \\\"Set duration to the requested scene duration or the nearest free option, usually 5s.\\\",\\n 144| \\\"Do not buy credits, subscribe, or select paid-only models/templates.\\\",\\n 145| \\\"Download the clip, then place it under data/imported_ai_clips//.mp4 for local assembly.\\\"\\n 146| ],\\n 147| \\\"expected_clip_path\\\": \\\"data/imported_ai_clips/{video_id}/scene_01.mp4\\\"\\n 148| },\\n 149| {\\n 150| \\\"job_id\\\": \\\"scene_02_free_ai_video_handoff\\\",\\n 151| \\\"scene_id\\\": \\\"scene_02\\\",\\n 152| \\\"asset_mode\\\": \\\"cinematic_ai_video\\\",\\n 153| \\\"status\\\": \\\"manual_generation_required\\\",\\n 154| \\\"duration_seconds\\\": 3.6,\\n 155| \\\"aspect_ratio\\\": \\\"9:16\\\",\\n 156| \\\"preferred_resolution\\\": \\\"480p_or_best_free_available\\\",\\n 157| \\\"provider_order\\\": [\\n 158| \\\"pixverse\\\",\\n 159|\", \"total_lines\": 275, \"file_size\": 11269, \"truncated\": true, \"hint\": \"Use offset=159 to continue reading (showing 49-158 of 275 lines)\", \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_othyUCaZ3YQAiIxXFryZGmPV" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_yvHw7djgfPK7YRkN0LnLNa60", "call_id": "call_yvHw7djgfPK7YRkN0LnLNa60", "response_item_id": "fc_0d1a4d10654d56b4016a1191833a488191a306e0d99871658d", "type": "function", "function": { "name": "skill_manage", "arguments": "{\"action\":\"patch\",\"name\":\"social-media-shorts-growth-engine\",\"new_string\":\"For this AutoShortsBot/Retention-Studio workflow, prefer a free-first renderer path before any paid video provider: `free_production_jobs → local_motion_renderer → FFmpeg MP4`. The local renderer should use Pillow/FFmpeg procedural motion, mechanism layers, kinetic captions, and generated metadata; preserve exact scene durations from render manifests, exclude text-only LLM refinement jobs from rendering, and keep generated local renders out of git (`data/local_motion_renders/`). NVIDIA/build.nvidia.com LLMs are optional text-refinement helpers only, not video generation.\\n\\nIf the user wants more realistic footage without spending money, use a hybrid free-tier handoff rather than pretending local procedural graphics are realistic: `free_production_jobs → free_ai_video_handoff → manual browser generation in free-tier tools (PixVerse/Pika/CapCut/Hailuo only with existing free credits) → import clips under data/imported_ai_clips/ → local captions/mechanism layers/FFmpeg assembly`. Guardrails: no paid top-ups, no subscriptions, avoid Pro templates, no baked captions/logos/watermarks where possible, and keep imported clips out of git.\\n\\n## Pitfalls\",\"old_string\":\"For this AutoShortsBot/Retention-Studio workflow, prefer a free-first renderer path before any paid video provider: `free_production_jobs → local_motion_renderer → FFmpeg MP4`. The local renderer should use Pillow/FFmpeg procedural motion, mechanism layers, kinetic captions, and generated metadata; preserve exact scene durations from render manifests, exclude text-only LLM refinement jobs from rendering, and keep generated local renders out of git (`data/local_motion_renders/`). NVIDIA/build.nvidia.com LLMs are optional text-refinement helpers only, not video generation.\\n\\n## Pitfalls\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering git commits and .gitignore**\n\nI'm thinking about the diff, which only shows changes in the gitignore because untracked files aren't listed. I should commit the new files, especially if I'm also updating my skills with an external provider. It's a good idea to check if `.gitignore` includes `data/free_ai_video_handoffs` since that JSON artifact should be committed. I'll need to ensure I handle credentials properly to push. I want to add and commit everything to avoid untracked files in my review.", "reasoning_content": "**Considering git commits and .gitignore**\n\nI'm thinking about the diff, which only shows changes in the gitignore because untracked files aren't listed. I should commit the new files, especially if I'm also updating my skills with an external provider. It's a good idea to check if `.gitignore` includes `data/free_ai_video_handoffs` since that JSON artifact should be committed. I'll need to ensure I handle credentials properly to push. 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[100%]\\n55 passed in 3.55s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_sWjn797bowTuyeds6MeqXfDJ" }, { "role": "tool", "content": "{\"output\": \"?? autoshorts/review_package.py\\n?? data/telegram_reviews/\\n?? scripts/generate_telegram_review_packages.py\\n?? tests/test_review_package.py\\n9f41a9f feat: add free ai video handoff specs\\nff5df62 feat: add free local motion renderer\\nb54a903 feat: add free production job specs\\n4d1e8f8 feat: generate mechanism render manifests\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_NvpKGhBchBzKkfoVXyLaDW6L" }, { "role": "tool", "content": "{\"output\": \"fatal: could not read Username for 'https://github.com': Kein passendes Gerät bzw. keine passende Adresse gefunden\", \"exit_code\": 128, \"error\": null}", "tool_call_id": "call_6NMVOe38VzA0TmnAqXNeZYGv" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_snPJADNtDsJXAjfg5o5N7YDc", "call_id": "call_snPJADNtDsJXAjfg5o5N7YDc", "response_item_id": "fc_0d1a4d10654d56b4016a1191a888b48191997b63284edcd214", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Provider-/Free-Tier-Registry und Job-Specs im Repo ergänzen\",\"id\":\"implement\",\"status\":\"completed\"},{\"content\":\"Tests, Artefakte und Git-Status verifizieren\",\"id\":\"verify\",\"status\":\"completed\"}]}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"todos\": [{\"id\": \"research\", \"content\": \"Free/freemium KI-Video-Tools für realistischere Shorts recherchieren\", \"status\": \"completed\"}, {\"id\": \"decide\", \"content\": \"Gratis-Workflow-Entscheidung für AutoShortsBot ableiten\", \"status\": \"completed\"}, {\"id\": \"implement\", \"content\": \"Provider-/Free-Tier-Registry und Job-Specs im Repo ergänzen\", \"status\": \"completed\"}, {\"id\": \"verify\", \"content\": \"Tests, Artefakte und Git-Status verifizieren\", \"status\": \"completed\"}], \"summary\": {\"total\": 4, \"pending\": 0, \"in_progress\": 0, \"completed\": 4, \"cancelled\": 0}}", "tool_call_id": "call_snPJADNtDsJXAjfg5o5N7YDc" }, { "role": "assistant", "content": "Ja, Sir — exakt: **das aktuelle MP4 ist noch Konzept/Animatic**, kein fertiges realistisches Video.\n\nEs zeigt Timing, Layer, Captions und Mechanik. Für ein „einigermaßen realistisches“ Endprodukt brauchen wir tatsächlich **KI-generierte Videoclips** als B-Roll/Scene-Clips — aber eben nur über **Free Tiers**, nicht über bezahlte Credits.\n\nIch habe recherchiert und den Workflow entsprechend weitergebaut.\n\n## Recherche: gratis / free-tier KI-Video-Tools\n\n## 1. PixVerse\n\nGefunden auf:\n\n```text\nhttps://app.pixverse.ai/\n```\n\nDie App zeigt aktuell:\n\n```text\n90\nTäglich aktualisieren\nJetzt registrieren und kostenlose Credits erhalten\n```\n\nEinschätzung:\n\n- sehr interessant als **Primary Free-Tier Candidate**\n- offenbar tägliche Free-Credits\n- geeignet für realistische 9:16 Short-Clips\n- manuelle Browser-Nutzung/Login nötig\n- keine paid Top-ups erlaubt\n\nPriorität:\n\n```text\n#1 PixVerse\n```\n\n## 2. Pika\n\nGefunden auf offizieller Pricing-Seite:\n\n```text\nhttps://pika.art/pricing\n```\n\nFree Basic:\n\n```text\n$0\n80 monthly video credits\nAccess to Pika 2.5, 480p only\nDownload videos with no watermark\nCommercial use\n```\n\nFür Text/Image-to-Video laut Pricing:\n\n```text\n480p / 5s = 12 credits Free\n```\n\nEinschätzung:\n\n- sehr brauchbarer Fallback\n- Free-Output nur 480p, aber für Shorts mit lokalem Upscale/Compositing akzeptabel\n- no-watermark + commercial-use Claim ist stark\n- monatlich begrenzter als PixVerse\n\nPriorität:\n\n```text\n#2 Pika\n```\n\n## 3. CapCut AI Video Maker\n\nGefunden auf:\n\n```text\nhttps://www.capcut.com/tools/ai-video-generator\n```\n\nCapCut sagt u.a.:\n\n```text\nFree AI Video Generator\nExport the finished video in HD quality for free\n```\n\nEinschätzung:\n\n- gut für manuelle Politur, Templates, Captions, Schnitt\n- Free-Quota öffentlich weniger klar\n- CapCut kann schnell in Pro-Assets/Upsell laufen\n- trotzdem nützlich als kostenloser Editor-/Assembler-Kandidat\n\nPriorität:\n\n```text\n#3 CapCut\n```\n\n## 4. Hailuo\n\nGefunden auf:\n\n```text\nhttps://hailuoai.video/\n```\n\nDie Seite zeigt einen Generator mit:\n\n```text\n768p\n6s\n25 credits\n```\n\nEinschätzung:\n\n- nur verwenden, falls kostenlose vorhandene Credits da sind\n- keine Käufe, keine Top-ups\n- weil du Hailuo explizit als „kein Geld für Credits“ genannt hast: nur Free-Quota-Fallback, nicht Hauptpfad\n\nPriorität:\n\n```text\n#4 Hailuo, nur falls Free-Credits verfügbar\n```\n\n## Nicht als Free-First geeignet\n\nAktuell nicht als Primary Free Workflow:\n\n```text\nRunway\nLuma\nKling\nVeo\nSora API\n```\n\nGrund:\n\n- entweder paid-first\n- Free-Kontingent unklar/klein\n- API/Automation meist bezahlt\n- oder nicht stabil genug für unseren kostenlosen Produktionspfad\n\n## Neue Workflow-Entscheidung\n\nDer Zielworkflow ist jetzt:\n\n```text\n1. Hermes/ChatGPT/NVIDIA LLM:\n Shot plan, prompts, captions, scene specs\n\n2. Free AI Video Provider:\n PixVerse / Pika / CapCut / Hailuo-Free\n erzeugen realistische kurze Clips manuell im Browser\n\n3. Import:\n Clips lokal speichern unter data/imported_ai_clips/...\n\n4. Local Renderer:\n Mechanism-Layer, Captions, SFX, Timing, Assembly\n\n5. FFmpeg:\n finales 9:16 MP4\n```\n\nDas heißt: \n**Die realistischen Teile kommen aus kostenlosen KI-Video-Free-Tiers.** \n**Die System-Erklärung, Captions und Montage bleiben lokal kontrolliert.**\n\nDas ist der richtige Hybrid. Nur lokal wird zu sehr Konzeptgrafik. Nur KI-Video wird generischer Slop. Zusammen wird es brauchbar. Welch seltene Gelegenheit, dass zwei halbe Lösungen zusammen eine ganze ergeben.\n\n## Im Repo neu gebaut\n\nNeue Komponente:\n\n```text\nautoshorts/free_ai_video_providers.py\n```\n\nNeues CLI:\n\n```text\nscripts/generate_free_ai_video_handoffs.py\n```\n\nNeue Tests:\n\n```text\ntests/test_free_ai_video_providers.py\n```\n\nNeues Artefakt:\n\n```text\ndata/free_ai_video_handoffs/mechanism_pilots/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\n```\n\n## Was dieses Handoff enthält\n\nFür den Pilot:\n\n```text\nWarum ein billiges Auto teuer sein kann\n```\n\nwerden jetzt **2 realistische AI-Video-Jobs** erzeugt:\n\n```text\nscene_01 → realistische KI-Video-Szene\nscene_02 → realistische KI-Video-Szene\n```\n\nProvider-Reihenfolge:\n\n```text\n1. PixVerse\n2. Pika\n3. CapCut\n4. Hailuo nur Free-Credits\n```\n\nGuardrails:\n\n```text\npaid_topups_allowed: false\npaid_subscriptions_allowed: false\ndo_not_buy_credits: true\navoid_pro_templates_or_paid_assets: true\nexport_without_baked_captions: true\nfinal_captions_added_locally: true\n```\n\nDie Mechanismus-Szenen bleiben vorerst lokal:\n\n```text\nscene_03 → local mechanism animation\nscene_04 → local mechanism animation\nscene_05 → local kinetic text\n```\n\nWarum? Weil KI-Video-Tools bei präzisen Layer-Erklärungen oft halluzinieren. Realistische Clips: ja. Exakte Erklärgrafik: lieber lokal kontrolliert.\n\n## Beispiel Prompt für Scene 1\n\nDas Handoff erzeugt provider-ready Prompts wie:\n\n```text\nVertical 9:16 realistic cinematic short video.\nA realistic creator at a desk late evening, laptop open to an AI chat,\nthoughtful but in control, hands moving between keyboard and notebook.\nMood: focused, modern, high-retention social video.\nScene intent: 3D car x-ray with price tag layers and risk meters freezes mid-action with warning signal.\nCamera: slow handheld push-in, subtle parallax, natural micro-movements.\nNo captions, no readable text, no logos, no watermarks.\nLeave clean negative space in the lower third for captions.\nThe clip should feel like real b-roll for a mechanism explainer, not a slideshow.\n```\n\nWichtig: Captions kommen später lokal drauf. Kein KI-Gibberish im Bild.\n\n## Tests\n\nFull suite:\n\n```text\n55 passed in 3.55s\n```\n\n## Git\n\nNeuer lokaler Commit:\n\n```text\n9f41a9f feat: add free ai video handoff specs\n```\n\nDavor liegt noch:\n\n```text\nff5df62 feat: add free local motion renderer\n```\n\nPush ist weiterhin blockiert, weil GitHub-Credentials in dieser Umgebung fehlen:\n\n```text\nfatal: could not read Username for 'https://github.com'\n```\n\n## Antwort auf deine Kernfrage\n\nJa: **Das Endprodukt soll realistischer werden.**\n\nWas du aktuell gesehen hast, ist:\n\n```text\nAnimatic / Motion Concept / Local Placeholder\n```\n\nNicht das finale Video.\n\nDer nächste Produktionsschritt ist jetzt konkret:\n\n```text\nPixVerse oder Pika öffnen\n→ scene_01 + scene_02 mit Free Credits generieren\n→ Clips herunterladen\n→ lokal importieren\n→ Local Renderer ersetzt Placeholder durch echte KI-Clips\n→ Mechanism Layers + Captions + SFX darüber\n→ finales MP4\n```\n\n## Nächster sinnvoller Schritt\n\nIch würde als Nächstes bauen:\n\n```text\nImported AI Clip Assembler\n```\n\nDamit das System automatisch prüft:\n\n```text\ndata/imported_ai_clips//scene_01.mp4\ndata/imported_ai_clips//scene_02.mp4\n```\n\nWenn Clips vorhanden sind:\n\n```text\nechte AI-Clips verwenden\n```\n\nWenn nicht:\n\n```text\nlocal placeholder verwenden\n```\n\nDann können wir Free-Tier-Clips manuell aus PixVerse/Pika holen und sofort in denselben Renderprozess einbauen.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZGxfmrYptRmaZ_IHaerF6myAeuW7LZYlWiFY_u0VdRaGSWGR1G86CPJssYaNmmi6fB6HmiJHvE46h_mq_4OOuey_MNt46Ss65bbAF4qCoUVZDykMplP7_QZfNX_G9nYM0vJOyO9UBRzIh-Mwk1QSoZkC2ESPmFk954Lqyp1YfyN7SI7GKoTXiDrxLe-4xlA-xkwk5LxtKO4-rjE1skDMbYqiqE9nr9-qDrk_XR5C0DAGyOp301RBSOwG_SPoanJt8ZkZUICi9A8L_fU469YOzd75lp-xygmCvUH8v254VUA1Nfg-oDAH5hxr1GgKvhLnNTBvPAlfCtdy5VZyjI8cWzWcRCP4OLHOCJvOM_kx5eDPTiQCREpgc_Rs5El6lVRrOle8r4QXe9uKAGuXjIcU1r8jBTvz8ZZHryWkRxVZzbCYyObqJgT-Btuvyh0lEAM35HdC0dspUEIkeS6BJKGORZi3zKHH9mAPHPEAqHRyFrKtGX9WfQQuvZfo6d8RPTzX77FU6qD4HR97ld49uyIKy3d5PVJ0LTPcuNXr28RBUSAo4bln6g60lui_20pkrSopVlrcU9xZ-ms8jerJLW7XPb0tiIAl6revVyu7eEzXUL0fAbaWPpWd3hs5saV2T3kPeJUvjSeSIOkj2s4m7SkbPbDpAnK97j6v3Vp99jdLbb4d5mdSiTp_0XaF3zLIK-h_dzjgsDugTYsUQMODx3jFRum208q5orr_lbMpkd6rNQYJqozY7i_GSJxqNJXCqZPelevy0gmFAwkRDpZBHWSyA5Bn85DP_esIt7zBImMbXA81ENwQYndMnAjHoxoxFEBOr4SNevYTlYbDIpzLuXcnEpjQeucjGptKbX3_0KbfHGF8yvdeHCHfrj4pRmkfPV37yK76CyBBp9iBg3PTlac-7MolcdxEmBhqUbio6LGfCfdBhfplWrzEaavcBrn0NKNRsPho1PVjTbrIpCZp1O7kX1J_fmn2VOLvvNAmz2hxBF6eynprf81ZVb4ROQKFjWH3nWLPv9a4qQRzn0c1VkRh1OpVNA4oqB6oq0qN63Jhbc4lF8DfV08xgUYYmn9owvMA_Fq-VmPOWeWu3801xLacyHOjSAuxfnZwf8DoRPRaKw2JIR_S_9H9zCbEB8SBULTJlqjKRApS2ZEnvPEMhs5bSCZlnOkbWNf0KPo7ky9AMdxcZr-RFUYmEkAOogEXSzUWVZT9X8rxftjjXH1a5fNTM6dERDdrUOPpZOw91W_NDeNCqhBP5Tz7ChXoxHTVgQdXfwSYvCRXqZLetDCFPplk89cry2AXB5bQfjHklMSAoPZAFwBR0jGQJgMeTJADMh2DGIPQ9YAIfJ5Rd3tTniFgKl7aPqahRXA6OSalE2STfQ5DvHOtEPSHud91VCGdkk5Opx0D2yOhVTcDI-AuGtTS9QqVajD_dH2nVP2p4_wvYkgTdYqbebQ48R7eCfGkn8d8h2jkDC6qaCi_obyYnhL9__nbzKDeVHv7lk0AVtBrMpH1OynPWBA-tAAqArznBKzqZOBg2cCSAv4WTpInAfcbBYXfJy8YH0DsLjXr6jUTqFO8v43W1TEmD1lvXXJkPWfS-Svyv83b4pDgOM-KEZugPN8pg8fUncYewO7H-HLYD8X6s-Che6P3HtW00vyNiPjrSSjk_UGYmsZYbcwLMx9M8ZI0kkT1L_nm31zviODY1uCiuwppFfCLv5nNps0QqUP5X1nL2n1xjYfsZdUEjTud26D-ClVtcLvLKEiAHcv5dPtFybXvk5I4P4JOE9R68_Rg_6pTFZBITif8smub_AwVSlwQJDxciMxZ_H_0tJ2AkrrbOBkphNer0dLQin_QX5zt-mkFPOcsga9gDMTuYRhepSK3RKwXs_3xWjUKNw8nz6ZY4lNIYFXCCt4kSiTQn3XB2BBlVIf07yJhmYe4U6CKhdTM4s1WLCc49e6NMZ33MFf5t5y905uoYC3lLK2y1IEDfT0FJWHbChp5UC2z_Zbp1xhug==", "id": "rs_0d1a4d10654d56b4016a1191ae1b408191a1683d577486d8d5", "summary": [] } ], "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Ja, Sir — exakt: **das aktuelle MP4 ist noch Konzept/Animatic**, kein fertiges realistisches Video.\n\nEs zeigt Timing, Layer, Captions und Mechanik. Für ein „einigermaßen realistisches“ Endprodukt brauchen wir tatsächlich **KI-generierte Videoclips** als B-Roll/Scene-Clips — aber eben nur über **Free Tiers**, nicht über bezahlte Credits.\n\nIch habe recherchiert und den Workflow entsprechend weitergebaut.\n\n## Recherche: gratis / free-tier KI-Video-Tools\n\n## 1. PixVerse\n\nGefunden auf:\n\n```text\nhttps://app.pixverse.ai/\n```\n\nDie App zeigt aktuell:\n\n```text\n90\nTäglich aktualisieren\nJetzt registrieren und kostenlose Credits erhalten\n```\n\nEinschätzung:\n\n- sehr interessant als **Primary Free-Tier Candidate**\n- offenbar tägliche Free-Credits\n- geeignet für realistische 9:16 Short-Clips\n- manuelle Browser-Nutzung/Login nötig\n- keine paid Top-ups erlaubt\n\nPriorität:\n\n```text\n#1 PixVerse\n```\n\n## 2. Pika\n\nGefunden auf offizieller Pricing-Seite:\n\n```text\nhttps://pika.art/pricing\n```\n\nFree Basic:\n\n```text\n$0\n80 monthly video credits\nAccess to Pika 2.5, 480p only\nDownload videos with no watermark\nCommercial use\n```\n\nFür Text/Image-to-Video laut Pricing:\n\n```text\n480p / 5s = 12 credits Free\n```\n\nEinschätzung:\n\n- sehr brauchbarer Fallback\n- Free-Output nur 480p, aber für Shorts mit lokalem Upscale/Compositing akzeptabel\n- no-watermark + commercial-use Claim ist stark\n- monatlich begrenzter als PixVerse\n\nPriorität:\n\n```text\n#2 Pika\n```\n\n## 3. CapCut AI Video Maker\n\nGefunden auf:\n\n```text\nhttps://www.capcut.com/tools/ai-video-generator\n```\n\nCapCut sagt u.a.:\n\n```text\nFree AI Video Generator\nExport the finished video in HD quality for free\n```\n\nEinschätzung:\n\n- gut für manuelle Politur, Templates, Captions, Schnitt\n- Free-Quota öffentlich weniger klar\n- CapCut kann schnell in Pro-Assets/Upsell laufen\n- trotzdem nützlich als kostenloser Editor-/Assembler-Kandidat\n\nPriorität:\n\n```text\n#3 CapCut\n```\n\n## 4. Hailuo\n\nGefunden auf:\n\n```text\nhttps://hailuoai.video/\n```\n\nDie Seite zeigt einen Generator mit:\n\n```text\n768p\n6s\n25 credits\n```\n\nEinschätzung:\n\n- nur verwenden, falls kostenlose vorhandene Credits da sind\n- keine Käufe, keine Top-ups\n- weil du Hailuo explizit als „kein Geld für Credits“ genannt hast: nur Free-Quota-Fallback, nicht Hauptpfad\n\nPriorität:\n\n```text\n#4 Hailuo, nur falls Free-Credits verfügbar\n```\n\n## Nicht als Free-First geeignet\n\nAktuell nicht als Primary Free Workflow:\n\n```text\nRunway\nLuma\nKling\nVeo\nSora API\n```\n\nGrund:\n\n- entweder paid-first\n- Free-Kontingent unklar/klein\n- API/Automation meist bezahlt\n- oder nicht stabil genug für unseren kostenlosen Produktionspfad\n\n## Neue Workflow-Entscheidung\n\nDer Zielworkflow ist jetzt:\n\n```text\n1. Hermes/ChatGPT/NVIDIA LLM:\n Shot plan, prompts, captions, scene specs\n\n2. Free AI Video Provider:\n PixVerse / Pika / CapCut / Hailuo-Free\n erzeugen realistische kurze Clips manuell im Browser\n\n3. Import:\n Clips lokal speichern unter data/imported_ai_clips/...\n\n4. Local Renderer:\n Mechanism-Layer, Captions, SFX, Timing, Assembly\n\n5. FFmpeg:\n finales 9:16 MP4\n```\n\nDas heißt: \n**Die realistischen Teile kommen aus kostenlosen KI-Video-Free-Tiers.** \n**Die System-Erklärung, Captions und Montage bleiben lokal kontrolliert.**\n\nDas ist der richtige Hybrid. Nur lokal wird zu sehr Konzeptgrafik. Nur KI-Video wird generischer Slop. Zusammen wird es brauchbar. Welch seltene Gelegenheit, dass zwei halbe Lösungen zusammen eine ganze ergeben.\n\n## Im Repo neu gebaut\n\nNeue Komponente:\n\n```text\nautoshorts/free_ai_video_providers.py\n```\n\nNeues CLI:\n\n```text\nscripts/generate_free_ai_video_handoffs.py\n```\n\nNeue Tests:\n\n```text\ntests/test_free_ai_video_providers.py\n```\n\nNeues Artefakt:\n\n```text\ndata/free_ai_video_handoffs/mechanism_pilots/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\n```\n\n## Was dieses Handoff enthält\n\nFür den Pilot:\n\n```text\nWarum ein billiges Auto teuer sein kann\n```\n\nwerden jetzt **2 realistische AI-Video-Jobs** erzeugt:\n\n```text\nscene_01 → realistische KI-Video-Szene\nscene_02 → realistische KI-Video-Szene\n```\n\nProvider-Reihenfolge:\n\n```text\n1. PixVerse\n2. Pika\n3. CapCut\n4. Hailuo nur Free-Credits\n```\n\nGuardrails:\n\n```text\npaid_topups_allowed: false\npaid_subscriptions_allowed: false\ndo_not_buy_credits: true\navoid_pro_templates_or_paid_assets: true\nexport_without_baked_captions: true\nfinal_captions_added_locally: true\n```\n\nDie Mechanismus-Szenen bleiben vorerst lokal:\n\n```text\nscene_03 → local mechanism animation\nscene_04 → local mechanism animation\nscene_05 → local kinetic text\n```\n\nWarum? Weil KI-Video-Tools bei präzisen Layer-Erklärungen oft halluzinieren. Realistische Clips: ja. Exakte Erklärgrafik: lieber lokal kontrolliert.\n\n## Beispiel Prompt für Scene 1\n\nDas Handoff erzeugt provider-ready Prompts wie:\n\n```text\nVertical 9:16 realistic cinematic short video.\nA realistic creator at a desk late evening, laptop open to an AI chat,\nthoughtful but in control, hands moving between keyboard and notebook.\nMood: focused, modern, high-retention social video.\nScene intent: 3D car x-ray with price tag layers and risk meters freezes mid-action with warning signal.\nCamera: slow handheld push-in, subtle parallax, natural micro-movements.\nNo captions, no readable text, no logos, no watermarks.\nLeave clean negative space in the lower third for captions.\nThe clip should feel like real b-roll for a mechanism explainer, not a slideshow.\n```\n\nWichtig: Captions kommen später lokal drauf. Kein KI-Gibberish im Bild.\n\n## Tests\n\nFull suite:\n\n```text\n55 passed in 3.55s\n```\n\n## Git\n\nNeuer lokaler Commit:\n\n```text\n9f41a9f feat: add free ai video handoff specs\n```\n\nDavor liegt noch:\n\n```text\nff5df62 feat: add free local motion renderer\n```\n\nPush ist weiterhin blockiert, weil GitHub-Credentials in dieser Umgebung fehlen:\n\n```text\nfatal: could not read Username for 'https://github.com'\n```\n\n## Antwort auf deine Kernfrage\n\nJa: **Das Endprodukt soll realistischer werden.**\n\nWas du aktuell gesehen hast, ist:\n\n```text\nAnimatic / Motion Concept / Local Placeholder\n```\n\nNicht das finale Video.\n\nDer nächste Produktionsschritt ist jetzt konkret:\n\n```text\nPixVerse oder Pika öffnen\n→ scene_01 + scene_02 mit Free Credits generieren\n→ Clips herunterladen\n→ lokal importieren\n→ Local Renderer ersetzt Placeholder durch echte KI-Clips\n→ Mechanism Layers + Captions + SFX darüber\n→ finales MP4\n```\n\n## Nächster sinnvoller Schritt\n\nIch würde als Nächstes bauen:\n\n```text\nImported AI Clip Assembler\n```\n\nDamit das System automatisch prüft:\n\n```text\ndata/imported_ai_clips//scene_01.mp4\ndata/imported_ai_clips//scene_02.mp4\n```\n\nWenn Clips vorhanden sind:\n\n```text\nechte AI-Clips verwenden\n```\n\nWenn nicht:\n\n```text\nlocal placeholder verwenden\n```\n\nDann können wir Free-Tier-Clips manuell aus PixVerse/Pika holen und sofort in denselben Renderprozess einbauen." } ], "id": "msg_0d1a4d10654d56b4016a1191b18b388191be3fead6ca5498a6", "phase": "final_answer" } ], "finish_reason": "stop" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_Rl4MhYkKziCrxsazStJhgJRE", "call_id": "call_Rl4MhYkKziCrxsazStJhgJRE", "response_item_id": "fc_0d1a4d10654d56b4016a11934f2c4481918c6fbe8e9f423911", "type": "function", "function": { "name": "todo", "arguments": "{\"todos\":[{\"id\":\"chatgpt-pro\",\"content\":\"Aktuelle ChatGPT Pro Video-/Sora-Leistungen prüfen\",\"status\":\"in_progress\"},{\"id\":\"tdd-import\",\"content\":\"TDD für Imported AI Clip Assembler schreiben und RED verifizieren\",\"status\":\"pending\"},{\"id\":\"build-import\",\"content\":\"Imported AI Clip Assembler implementieren\",\"status\":\"pending\"},{\"id\":\"verify\",\"content\":\"Tests/Artefakte/Git-Status verifizieren\",\"status\":\"pending\"}]}" } } ], "finish_reason": "tool_calls", "reasoning": "**Assessing ChatGPT Pro features**\n\nI need to gather current facts about ChatGPT Pro features, so I'll check for the latest info. The task indicates I should continue building the imported assembler, which requires relevant skills in social and TDD that I might already have. I might also want to search for video generation related to ChatGPT Pro. Using a web search for OpenAI pricing and help could be beneficial as well, along with coding what I find.", "reasoning_content": "**Assessing ChatGPT Pro features**\n\nI need to gather current facts about ChatGPT Pro features, so I'll check for the latest info. The task indicates I should continue building the imported assembler, which requires relevant skills in social and TDD that I might already have. I might also want to search for video generation related to ChatGPT Pro. Using a web search for OpenAI pricing and help could be beneficial as well, along with coding what I find.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZNPqik-bRW0OtmcEys1zs9M7alC-PS9Ods9BOEMM1GeRrOVgxhIKNmjslDvUPRSKjlZp4pLhwK8GT6-Bl22eMwJ_p1cgUB5fvO7TxPdJNXmu299afZa7-R5IyEsmoeWQi7GYL9O_2BJJklc6MjWCAltsyhqhqnXxVbb1J1ZoHFgRmXRMcRFxNmsVXsaSvWPc6wLyxlUPJlz_wGm7PLL58ZyOEaIK7ab8Zep2oHXCwKwqDzs8zg7JbQK4q2c9Z0rQcxcQ3zAdR9TqdweZ3UP-KUIPse8DsBv0ZUQhAP4HyiZejumLfVM9jpuP2rlx6ORw2wK3ujpHH27gtfCwTAbYUJQjaWicIorPJ8OFb6phSi18fXfz0WVvfaQ4LnsC9P4KAh3UOZ0Vrj3KaS8QpcFvnzJakRIMGlNbkylghOOpsqNvGmiy5EHeOrKbb8fmou2Y0lNSp_r2ar8eUnd2YAhOPkOY_dEPSKtwBDCmKFZq1emAMROhcf1DIxK3B5VeBNoXfrumKMoFMUYXd_J9rCn4n0FUfkx4ykmvP28CvFu4V_x8YrBkS1G-wOmvhTY180jcpFzpm-A8QOWX88HPQF5OomAXWLKqRSv7PjG2bviyoAqAt1oAlc5oz6Nr_Ubz84dAtqMry4OebQ6aqeVFZsJH7i44fYCcOCBOuFLOsrxVbcYIIxJXAuUvwEudOBWcdd54gfuY74OYs7qGwHCNiXSJ0b_Kotw-9dBw8-iqVafXf_6pOWAhMsS4zEupXUJJDQZB9A1U0m-F2DdTsvh0xsxpUZchpc8alZ5qGFd964IGcTSyZz7n3voQelpFI77PBP_NI-2fu9vBEMsSyVv3D5baNScU718v7uYPoXo3e7ZpZQ4f1vxw5b6hIYPEMNXQY6iFiO0GxXPHpIh9ArKtIy8PQA89Pg8JhSUd6fwTqXJrEEq2XAlQfNuVdFXJWQSlgDCf4Wiv4fdzJgzZw3KSa1HXq8OJdcAUlWnYYcd8vkuezx1SN1n065TaGT0jeC9wa0YTGKp7fM3tIa1AArzKq5mluUnrDWLze-scCrAZnmk7RT9OaIVqh-69eQt8W5GSl3KgnLjxsRxBWHGNASKVIvTpn2WgHVFuN8JmU3pXjLkwCyZk92Dn_9Bmhffl8Wo9VEVimJ3cEPsQxzTdbM6EXhUVv82e3UovMnfRvfADb-m1Ik2Cs1vEuDkLfWkea477uEqqSze-VELhXY5DbceI0HKJcidofrBnHs4nDshqPDwXvu8mE4MoXmbfakowFPetRozLYk2fNe1lYSZoXeH92_SnQiEAi6CtpmU4xDIRFqBcEwQ2stOhiyYXqvvhV_IgjtKUsmUfZgwhV1xZtPQGR6cwYdbRQ==", "id": "rs_0d1a4d10654d56b4016a11934c5c308191860ac90b482c95d7", "summary": [ { "type": "summary_text", "text": "**Assessing ChatGPT Pro features**\n\nI need to gather current facts about ChatGPT Pro features, so I'll check for the latest info. The task indicates I should continue building the imported assembler, which requires relevant skills in social and TDD that I might already have. I might also want to search for video generation related to ChatGPT Pro. Using a web search for OpenAI pricing and help could be beneficial as well, along with coding what I find." } ] } ] }, { "role": "tool", "content": "{\"todos\": [{\"id\": \"chatgpt-pro\", \"content\": \"Aktuelle ChatGPT Pro Video-/Sora-Leistungen prüfen\", \"status\": \"in_progress\"}, {\"id\": \"tdd-import\", \"content\": \"TDD für Imported AI Clip Assembler schreiben und RED verifizieren\", \"status\": \"pending\"}, {\"id\": \"build-import\", \"content\": \"Imported AI Clip Assembler implementieren\", \"status\": \"pending\"}, {\"id\": \"verify\", \"content\": \"Tests/Artefakte/Git-Status verifizieren\", \"status\": \"pending\"}], \"summary\": {\"total\": 4, \"pending\": 3, \"in_progress\": 1, \"completed\": 0, \"cancelled\": 0}}", "tool_call_id": "call_Rl4MhYkKziCrxsazStJhgJRE" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_WeC2fDi1ybgOcSnuLkrgEcPK", "call_id": "call_WeC2fDi1ybgOcSnuLkrgEcPK", "response_item_id": "fc_0d1a4d10654d56b4016a119354ae4081919f059d0a5e92184a", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://openai.com/chatgpt/pricing/\"}" } }, { "id": "call_PwdXJBXQMOG3uWKLuqM6HOdT", "call_id": "call_PwdXJBXQMOG3uWKLuqM6HOdT", "response_item_id": "fc_0d1a4d10654d56b4016a119354ae548191857188158af5d36a", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://help.openai.com/en/articles/9957612-generating-videos-on-sora\"}" } }, { "id": "call_nUvuznE7Ajp6lF2yRtx4dvFv", "call_id": "call_nUvuznE7Ajp6lF2yRtx4dvFv", "response_item_id": "fc_0d1a4d10654d56b4016a119354ae608191a15663be2eca58ba", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git status --short && git log --oneline -3\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"success\": true, \"url\": \"https://chatgpt.com/de-DE/pricing/\", \"title\": \"ChatGPT-Pläne | Free, Go, Plus, Pro, Business und Enterprise\", \"stealth_warning\": \"Running WITHOUT residential proxies. 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Abrechnungshilfe⁠ ansehen\\n\\nGo\\n\\nChatte weiter mit erweitertem Zugriff\\n\\nCHF 7\\n/ Monat\\nGo holen\\nAlles aus Free sowie:\\n\\nMehr Zugriff auf GPT-5.5 Instant\\n\\nMehr Nachrichten\\n\\nMehr Uploads\\n\\nMehr Bilderstellung\\n\\nLängere Erinnerung\\n\\nDieser Plan kann Werbung enthalten. Mehr erfahren⁠\\n\\nPlus\\n\\nMach mehr mit fortschrittlicher Intelligenz\\n\\nCHF 20\\n/ Monat\\nPlus holen\\nAlles aus Go und:\\n\\nFortgeschrittenes Reasoning mit GPT-5.5 Thinking\\n\\nErweiterte Nachrichten und Uploads\\n\\nKomplexere und präzisere Bilderstellung\\n\\nErweiterte Deep Research und Agentenmodus\\n\\nErweiterte Erinnerung und Kontext\\n\\nProjekte, Aufgaben und individuelle GPTs\\n\\nErweiterte Codex-Nutzung\\n\\nFrühzeitiger Zugriff auf neue Funktionen\\n\\nEs gelten Nutzungsobergrenzen⁠\\n\\nDas Doppelte deiner normalen Codex-Nutzung auf der Tarifstufe CHF 83 / Monat bis zum 31. Mai 2026.\\nPro\\n\\nMaximiere deine Produktivität\\n\\nAb\\nCHF 83\\n/ Monat\\nPro holen\\nAlles aus Plus sowie:\\n\\n5x oder 20x mehr Nutzung\\n\\n5x, 10x oder 20x mehr Codex-Nutzung\\n\\nPro-Reasoning mit GPT-5.5 Pro\\n\\nMaximale Codex-Aufgaben\\n\\nUnbegrenztes GPT-5.3 und Datei-Uploads\\n\\nUnbegrenzte und schnellere Bilderstellung\\n\\nMaximale Deep Research und Agentenmodus\\n\\nMaximale Erinnerung und maximaler Kontext\\n\\nErweiterte Projekte, Aufgaben und individuelle GPTs\\n\\nNeue Funktionen als experimentelle Vorschau\\n\\nUnbegrenzt, mit Schutz vor Missbrauch. Mehr erfahren⁠\\n\\nUnternehmen\\nCodex\\n\\nEin Plan für entwicklungsorientierte Teams mit Pay-as-you-go-Preismodell\\n\\nNutzungsabhängige Preisgestaltung\\nKeine feste Benutzerlizenzgebühr. Nutzungsbasiertes Pay-as-you-go-Modell.\\nJetzt loslegen\\nWas enthalten ist:\\n\\nKI-gestützte Softwareentwicklung\\n\\nAutomatisierte Code- und Sicherheitsüberprüfungen\\n\\nAufgaben auf deinem Computer automatisieren\\n\\nAktionen an deinen Dokumenten, Tools und Codebasen vornehmen\\n\\nIntegrierte Worktrees und Cloud-Umgebungen für Multi-Agenten-Workflows\\n\\nKeine feste Benutzerlizenzgebühr; nutzungsbasiertes Pay-as-you-go-Modell\\n\\nEin sicherer, dedizierter Workspace mit wichtigen Admin-Kontrollen, SAML SSO und MFA\\n\\nKein Training mit deinen Daten; SAML-Sicherheit\\n\\nUnterstützung bei der Einhaltung der DSGVO, des CCPA und weiterer Datenschutzgesetze. Im Einklang mit CSA STAR⁠ und SOC 2 Type 2\\n\\nUnternehmen\\nChatGPT und Codex\\n\\nEin sicherer, kollaborativer Workspace für Startups und wachsende Unternehmen\\n\\nCHF 15\\n/ Benutzer / Monat\\nLoslegen\\nWas enthalten ist:\\n\\nAlles aus den Codex-Plänen von ChatGPT Plus und -Business\\n\\nUnbegrenzter Standard-Chat und Zugriff auf die besten Modelle für die Arbeit\\n\\nÜber 60 Apps, die deine Tools und Daten in ChatGPT einbinden – wie Slack, Google Drive, SharePoint, GitHub, Atlassian und mehr\\n\\nBusiness-Funktionen wie Apps, Datenanalyse, Aufzeichnungsmodus, Canvas, gemeinsame Projekte und individuelle Workspace-GPTs\\n\\nEinfache Verwaltung von Mitgliedern, Rollen und Abrechnung\\n\\nEin sicherer, dedizierter Workspace mit wichtigen Admin-Kontrollen, SAML SSO und MFA\\n\\nKein Training mit deinen Daten; SAML-Sicherheit\\n\\nUnterstützung bei der Einhaltung der DSGVO, des CCPA und weiterer Datenschutzgesetze. Im Einklang mit CSA STAR⁠ und SOC 2 Type 2\\n\\n*2+ Nutzer:innen, jährlich abgerechnet. CHF 19 pro Nutzer:in und Monat bei monatlicher Abrechnung. Unbegrenzt, mit Schutz vor Missbrauch. Mehr erfahren⁠\\n\\nEnterprise\\n\\nKI, Sicherheit und Support der Enterprise-Klasse für große Unternehmen\\n\\nIndividuelle Preisgestaltung\\nWende dich an unser Vertriebsteam, um die Preise zu besprechen.\\nVertrieb kontaktieren\\nWas enthalten ist:\\n\\nErweitertes Kontextfenster, das längere Eingaben und größere Dateien unterstützt\\n\\nSicherheit und Steuerung auf Enterprise-Niveau, einschließlich SCIM, EKM, Nutzeranalysen, Domain-Verifizierung und rollenbasierten Zugriffskontrollen\\n\\nErweiterter Datenschutz mit individuellen Richtlinien zur Datenaufbewahrung, Verschlüsselung im Ruhezustand und bei der Übertragung sowie standardmäßig ohne Training an deinen Geschäftsdaten. Mehr erfahren⁠\\n\\nUnterstützt Datenresidenz in zehn Regionen\\n\\nPriorisierter Support rund um die Uhr, SLAs, individuelle rechtliche Bedingungen und Zugang zu KI-Beratern (für berechtigte Kunden)\\n\\nRechnungsstellung und Abrechnung, Volumenrabatte\\n\\n \\nIm Einsatz bei Teams von\\n \\nFunktionen der Pläne vergleichen\\n\\nFree\\n\\nFree holen\\n\\nGo\\n\\nGo holen\\n\\nPlus\\n\\nPlus holen\\n\\nPro\\n\\nPro holen\\n\\nBusiness\\n\\nBusiness holen\\n\\nEnterprise\\n\\nVertrieb kontaktieren\\nEssentials\\nNachrichten und Interaktionen\\nEingeschränkt\\nErweitert\\nUnbegrenzt*\\nUnbegrenzt*\\nUnbegrenzt*\\nUnbegrenzt*\\nChatverlauf\\nUnbegrenzt*\\nUnbegrenzt*\\nUnbegrenzt*\\nUnbegrenzt*\\nUnbegrenzt*\\nUnbegrenzt*\\nZugriff per Web, iOS, Android\\nModelle\\nGPT-5.5 Instant\\nErweitert\\nUnbegrenzt*\\nUnbegrenzt*\\nUnbegrenzt*\\nGPT-5.5 Thinking\\nErweitert\\nUnbegrenzt*\\nFlexibel**\\nFlexibel**\\nGPT-5.5 Pro\\nFlexibel**\\nFlexibel**\\nGPT-5 Thinking Mini\\nErweitert\\nUnbegrenzt*\\nFlexibel**\\nFlexibel**\\nLegacy-Modelle\\nFlexibel**\\nFlexibel**\\nReaktionszeiten\\nEingeschränkte Bandbreite
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Der für Benutzereingaben verfügbare Teil ist kleiner als das gesamte Fenster, da der Platz auch für Systemanweisungen (einschließlich Tools und Persönlichkeit), Erinnerungen (falls aktiviert) und interne Verarbeitung (Überprüfung von Informationen, Reasoning und Antwortgenerierung) genutzt wird. Der angegebene Speicherplatz für Benutzereingaben ist ein Richtwert und kann sich je nach den verwendeten Funktionen und dem Speicherinhalt dynamisch ändern.\\n\\n \\nFAQ\\nWie funktioniert die Preisgestaltung von ChatGPT?\\n\\nDie kostenlose Version von ChatGPT (Free) ist für alle verfügbar. Kostenpflichtige Pläne (Go, Plus, Business und Enterprise) werden pro Benutzer:in und Monat berechnet. Es gibt Monatspläne für Go, Plus und Business sowie Jahrespläne für Business und Enterprise.\\n\\nIst ChatGPT kostenlos?\\n\\nDie kostenlose Version von ChatGPT ist für alle verfügbar. Ein Upgrade auf Go, Plus, Business oder Enterprise bietet ein leistungsstärkeres Nutzungserlebnis durch zusätzliche Funktionen und Zugriff auf GPT-5.5.\\n\\nBietet OpenAI einen ChatGPT-Plan für Bildungseinrichtungen an?\\n\\nJa. Wir bieten ChatGPT für Lehrkräfte⁠ an, einen kostenlosen Plan für verifizierte K-12-Lehrkräfte in den USA bis Juni 2027, und ChatGPT Edu⁠, einen kostengünstigen Plan, der es Universitäten ermöglicht, KI in ihren Campus-Gemeinschaften bereitzustellen. Beide Pläne umfassen verbesserte Sicherheits- und Datenschutzkontrollen sowie zusätzliche Verwaltungsfunktionen für Schulen, Schulbezirke und Universitäten. Wende dich an unser Team,⁠ um mehr zu erfahren.\\n\\nBietet OpenAI Rabatte für gemeinnützige Organisationen an?\\n\\nJa. Über OpenAI for Nonprofits können gemeinnützige Organisationen jetzt einen Rabatt von bis zu 75 % auf ChatGPT Business oder ChatGPT Enterprise erhalten. Wende dich an unser Vertriebsteam⁠, um loszulegen.\\n\\nWie viele Benutzer:innen werden auf jedem Abonnementplan unterstützt?\\n\\nDie Pläne Go, Free und Plus sind für die Nutzung durch Einzelpersonen konzipiert. Business und Enterprise sind für Unternehmen gedacht. Business-Pläne sind ab zwei Benutzer:innen erhältlich. Bitte wende dich an den Vertrieb⁠, um mehr über unseren Enterprise-Plan zu erfahren.\\n\\nWelche Zahlungsoptionen habe ich?\\n\\nChatGPT Go, Plus, Pro oder Business kannst du mit jeder gängigen Kreditkarte kaufen. Für ChatGPT Enterprise wende dich bitte an den Vertrieb⁠, um alternative Zahlungsmöglichkeiten wie Rechnungsstellung zu erhalten.\\n\\nWie sicher ist ChatGPT?\\n\\nAlle Daten werden während der Übertragung verschlüsselt (TLS 1.2). Daten im Ruhezustand werden verschlüsselt (AES-256) und der Zugriff auf die Daten wird mithilfe strenger Zugriffskontrollen eingeschränkt. Unser Sicherheitsteam umfasst einen Bereitschaftsdienst, der rund um die Uhr an 365 Tagen im Jahr verfügbar ist und im Falle eines potenziellen Sicherheitsvorfalls benachrichtigt wird. Wir bieten ein Bug-Bounty-Programm⁠ für die verantwortungsvolle Offenlegung von Schwachstellen, die auf unserer Plattform und in unseren Produkten entdeckt wurden. Bitte besuche unser Trust Portal⁠ für weitere Informationen.\\n\\nWie verwendet ChatGPT meine Daten?\\n\\nWir geben dir die Kontrolle über deine Daten. Erfahre mehr darüber, wie deine Daten genutzt werden⁠, und über unseren Enterprise-Datenschutz⁠.\\n\\nOpenAI\\nForschung\\nSicherheit\\nAPI\\nNeuigkeiten\\nGeschäftsbedingungen und Richtlinien\\nNutzungsbedingungen\\nDatenschutzrichtlinie\\nNutzungsrichtlinie\\nWeitere Richtlinien\\nOpenAI © 2015–2026\\nCookies verwalten\\nDeutsch\\nWir verwenden Cookies\\n\\nCookies sorgen dafür, dass diese Website funktioniert, messen die Nutzung und unterstützen Marketingmaßnahmen. Verwalte deine Cookie-Einstellungen jederzeit. Weitere Informationen findest du in unserer Cookie-Richtlinie.\\n\\nNicht unbedingt erforderliche ablehnen\\nAlle akzeptieren\", \"result_type\": \"str\"}", "tool_call_id": "call_QpaT5pE4tIe9w7TlE3mkeGfK" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_thYaWwxMbMtYdieOD6kBcTx5", "call_id": "call_thYaWwxMbMtYdieOD6kBcTx5", "response_item_id": "fc_0d1a4d10654d56b4016a11937091a08191a8a6a95e50c13c41", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://openai.com/sora/\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Searching for pricing details**\n\nI’m trying to find specific pricing information for Sora, especially regarding video generation. It seems that the current pricing details don’t cover video generation explicitly, just mentioning voice and video in the context of chat. I think my best bet is to check directly on their website, sora.com. 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It seems that the current pricing details don’t cover video generation explicitly, just mentioning voice and video in the context of chat. I think my best bet is to check directly on their website, sora.com. I’ll use my browser for that. Let’s see what I can find!" } ] } ] }, { "role": "tool", "content": "{\"success\": true, \"url\": \"https://help.openai.com/en/articles/20001152-what-to-know-about-the-sora-discontinuation\", \"title\": \"What to know about the Sora discontinuation | OpenAI Help Center\", \"snapshot\": \"- link \\\"OpenAI\\\" [ref=e1]\\n- generic\\n - button \\\"Language\\\" [expanded=false, ref=e6]\\n- link \\\"Login\\\" [ref=e2]\\n- generic\\n - textbox \\\"Search for articles...\\\" [ref=e7]\\n- navigation \\\"Breadcrumb\\\" [ref=e3]\\n - list\\n - listitem [level=1]\\n - link \\\"All Collections\\\" [ref=e26]\\n- article\\n - heading \\\"What to know about the Sora discontinuation\\\" [level=1, ref=e8]\\n - StaticText \\\"Updated: vor 19 Stunden\\\"\\n - generic\\n - heading \\\"When will Sora be discontinued?\\\" [level=2, ref=e13]\\n - paragraph\\n - heading \\\"Will I be able to export my data after the Sora app is discontinued?\\\" [level=2, ref=e14]\\n - paragraph\\n - link \\\"below\\\" [ref=e27]\\n - heading \\\"What happens to my data after the Sora app is discontinued?\\\" [level=2, ref=e15]\\n - paragraph\\n - heading \\\"How can I access and export content I created in Sora?\\\" [level=2, ref=e16]\\n - paragraph\\n - link \\\"sora.chatgpt.com/sunset\\\" [ref=e28]\\n - heading \\\"What if I need a refund?\\\" [level=2, ref=e17]\\n - paragraph\\n - link \\\"How do I request a refund for my ChatGPT subscription?\\\" [ref=e29]\\n - link \\\"ChatGPT/Sora credits\\\" [ref=e30]\\n- generic\\n - heading \\\"Related articles\\\" [level=2, ref=e9]\\n - list\\n - listitem [level=1]\\n - link \\\"Using Credits for Flexible Usage in ChatGPT (Free/Go/Plus/Pro) Key information and FAQs about using credits\\\" [ref=e31]\\n - listitem [level=1]\\n - link \\\"Retiring GPT-4o and other ChatGPT models GPT-4o and additional models were deprecated in ChatGPT on February 13, 2026. 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Utilizing an article about it would be helpful, but there’s an issue since a browser snapshot hides some paragraphs from view. I think I can work around this by using the console's innerText to extract the information I need. It feels like a small challenge, but I’m sure I can get the full details this way!", "reasoning_content": "**Considering discontinued product features**\n\nI’ve noted that Sora has been discontinued in 2026, and I need to mention that fact. Utilizing an article about it would be helpful, but there’s an issue since a browser snapshot hides some paragraphs from view. I think I can work around this by using the console's innerText to extract the information I need. It feels like a small challenge, but I’m sure I can get the full details this way!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZN9DUT1E-u4C9Qf3X5g0hNwnezVvvCKbvh1nhiGF3-70OAC0BLrRYhac5_i5_fTWqBd9Vo3tppbk7KGbFlZqOCaQ0B3ouuHGLLOnmM8rfP_FNG6KtWObMs7GulIP46pkJUki6Cnr-YihlRO3b7uz03MflT60IB2MlQvIT9io4_R-zpPMfL2X7p73hkSvhRdS2uBfZ2PlazDarllxBt2e0108MmExwoJAGaixgP5jy42xnsfVUlwg4R6m4rvgLZAvgcmj5_BIJei-23Q9dh7z-2cMKC5UGjw35RgGSwVxCadmgw6d_X33uP1Zk4zO39xUNiOAqjX8gd4IGhlPKl9W2rmPkq8LDj4AMnXAcngstOr8tnZjKOnS2S99emCqqjswIY00jgOpRWuN-F1FbIia6WWhvVdsfINVSNlF9Ht7YmOMuvQoPIPDvU1-Jv3ixTUbY_csGs0ve7unggMaWg7YakYYzsCYQzWhM03Vgk0ZHL2slnksOwutlbTo0ZxIRJu21LQ_WclBKYygaau4flpO2bGzNHMBc7h8s1AXhkKSka_-262huUbi8fmJyVEmIpIO9y6nZ-uVulX1kY7bnAjmBDmXzGX5GBAhnpwYzNPSVedRS661-PsWSPOBimqHnhaO2Ihe-zE0gwdmuch0q7JCqgq_ry2NUwDOsZX_oHMsA1LUEWPTji7oomiXynCdiDX0qSVF9GULQ7CiYKJVHvUOro8xJ4u3dVeA16gs1HjgmScfvMukvVYA1uBiA6_mGeXfite2gFGlF9YZEoERH35RN7hGYwV0BXdIFH7Mb62007eMFyGueWUH45EXAFbugLoTpHj8iTaTOHpwlQ_mvTpeInoqQAd7uw4n7GRgK6DOsNogSwuBQF64bF15cFgVo97Sj-qxcPJe6aQkc3XoFk96QhWiPoxnmdwWn2TkCy7-m09ZHeC6IhtNhJ8w3Dr_LbiL62ID1N9WLsaYc2-xDzZGsGE49l-nG1JgoBf_76lS0vcNf24f91kIuzu83dXwbtqdKS8Ef1BXpDs1Soo5X-0YaH-aFx0Rmy5Kn9e00tp-cTSDRu0TOQK0ggBdPjvpyWzTqFJFtCFC0S3ZBCluW2vqOScxg==", "id": "rs_0d1a4d10654d56b4016a1193794be48191aa854c4d4b7fe660", "summary": [ { "type": "summary_text", "text": "**Considering discontinued product features**\n\nI’ve noted that Sora has been discontinued in 2026, and I need to mention that fact. Utilizing an article about it would be helpful, but there’s an issue since a browser snapshot hides some paragraphs from view. I think I can work around this by using the console's innerText to extract the information I need. It feels like a small challenge, but I’m sure I can get the full details this way!" } ] } ] }, { "role": "tool", "content": "{\"success\": true, \"result\": \"Language\\nEnglish\\nLogin\\nAll Collections\\nWhat to know about the Sora discontinuation\\nWhat to know about the Sora discontinuation\\nUpdated: vor 19 Stunden\\nWhen will Sora be discontinued?\\n\\nThe Sora web and app experiences were discontinued on April 26, 2026.\\n\\nThe Sora API will be discontinued on September 24, 2026.\\n\\nWill I be able to export my data after the Sora app is discontinued?\\n\\nYes, you can export your data following the steps below. If a final export window is offered, we’ll notify you by email before it begins. We recommend you export your Sora content as soon as possible.\\n\\nWhat happens to my data after the Sora app is discontinued?\\n\\nAfter Sora is discontinued, and after the period of time of any final export window passes (if we are able to offer one), we will permanently delete any data associated with your use of Sora.\\n\\nHow can I access and export content I created in Sora?\\n\\nYou can export content you created in Sora by going to sora.chatgpt.com/sunset and clicking on Export. You'll get an email when it's ready.\\n\\nWhat if I need a refund?\\n\\nFor refund questions, please see How do I request a refund for my ChatGPT subscription? Note that any purchased ChatGPT/Sora credits can still be used for Codex, if you so choose.\\n\\nRelated articles\\nUsing Credits for Flexible Usage in ChatGPT (Free/Go/Plus/Pro)\\nKey information and FAQs about using credits\\nRetiring GPT-4o and other ChatGPT models\\nGPT-4o and additional models were deprecated in ChatGPT on February 13, 2026. These models will continue to be available in the API.\\nChatGPT OpenAI o3 and o4‑mini models FAQ (Enterprise & Edu Version)\\nWas this article helpful?\\nSubmit\\nWhen will Sora be discontinued?\\nWill I be able to export my data after the Sora app is discontinued?\\nWhat happens to my data after the Sora app is discontinued?\\nHow can I access and export content I created in Sora?\\nWhat if I need a refund?\\nChatGPT\\nAPI\\nService Status\\nCookie Preferences\\n\\nWe use cookies and similar technologies to deliver, maintain, improve our services and for security purposes.\\n\\nCheck our Cookie Policy for details. Click 'Accept all' to let OpenAI and partners use cookies for these purposes. Click 'Reject all' to say no to cookies, except those that are strictly necessary. You can change your cookie settings at any time by clicking the cookie preferences link at the bottom of the page.\\n\\nReject All\\nAccept All\", \"result_type\": \"str\"}", "tool_call_id": "call_BJeuNWeGWyCYf6l3RHlm55ou" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_B9f5OTenyE2olsRsjSxtoqlT", "call_id": "call_B9f5OTenyE2olsRsjSxtoqlT", "response_item_id": "fc_0d1a4d10654d56b4016a119382f0348191acfe9bc91eb2ae40", "type": "function", "function": { "name": "browser_click", "arguments": "{\"ref\":\"e31\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZOC9lPgK-POvffQx6Y4Ctz0rmqrFgEDF1aDBPnoWZ_BQw1T-hyxu4cb-oapeYi700Pl_BsUUVP2YoIWovjqgTxmJjLk0pQJs-bwFxp7yD64NoDxa2gFjxD93l8A0riuBB4NrV5OMb2iCtDwyfcEViPXjuK7djeZT_EGbIW9ciZ8bk6sQMsh2_M33kgl3PfLKLjDdPN4clC9Vb03y5HCwaEGmjnQu4E9B8wVSFL-gVr-629nOdP6Etf4P8fU5Z1fS1gtlBJqsw8_3l5R_Zlecl4KgKF_96UfKGxVJwSnYXb4xCGKQYDQDTMxFBU7nxGfzca61uaYm8EYugVePMk6AyEunEPpx6zJ6L_fC1JBhrhhQ_bR5madlKmNdVeMjiu4Z14Rf36jkA9RUEi5K8Ot6vLMeFrw5C5co35A4g9hg2mmo8UOJZfRKV8ZhbmL6_-PDQKzr0bvPxRVFMcnQdWPxwFDR-e6Tp4fjiwBfdVTdWKJMR_J6RZQphel-XaiardSk4hRy2tNQsngMEA96ANtsK1dAqPv0Ci-eZhq6pYNkxls6vgQC0SR1JAyk6e-HQeIEiHlPglBB6xNbkb71GSWpJu7iCCS4VZ25T9aCQ560gsK4B0qbYHpZYc0gDnaswBK7d5fA-418hnwhivikA75LuxScm4MMybjEKi2QZ4-8PfHs00uUWAd9OnFVP2bOjksekbCmEDUQ9Sm2msHzCWoC0zJx7DlfDRFM0zE_hT_DDVj5rsab7Cs-u0jrW_hKNjXty8jnST9QE-yLOSYP9NLiqhOmK7G1C117fIQuo_rqc9T-az7JNkgyrZiGxVHCKUCMcZ-o6yYoO5IILt9-sfFdpLvxJqtrCdDVdYBeS6swRqGFi8OoVYBvGdM4przVHOlEdxBg4H1nBhejrz813GpzlIBDEG70W2EzBCo7UDlok7jZkcMHXbWUxqV8DY4BaONV68y6nBZgfHhntOVwNq_01lc6w==", "id": "rs_0d1a4d10654d56b4016a1193826d80819182872860889f45fb", "summary": [] } ] }, { "role": "tool", "content": "{\"success\": true, \"clicked\": \"@e31\"}", "tool_call_id": "call_B9f5OTenyE2olsRsjSxtoqlT" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_EXpJcn7QSSxVlocDtCYVRqmf", "call_id": "call_EXpJcn7QSSxVlocDtCYVRqmf", "response_item_id": "fc_0d1a4d10654d56b4016a11938689e88191b749b332db02bcfb", "type": "function", "function": { "name": "browser_console", "arguments": "{\"expression\":\"document.body.innerText\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"success\": true, \"result\": \"Language\\nEnglish\\nLogin\\nAll Collections\\nWhat to know about the Sora discontinuation\\nWhat to know about the Sora discontinuation\\nUpdated: vor 19 Stunden\\nWhen will Sora be discontinued?\\n\\nThe Sora web and app experiences were discontinued on April 26, 2026.\\n\\nThe Sora API will be discontinued on September 24, 2026.\\n\\nWill I be able to export my data after the Sora app is discontinued?\\n\\nYes, you can export your data following the steps below. If a final export window is offered, we’ll notify you by email before it begins. We recommend you export your Sora content as soon as possible.\\n\\nWhat happens to my data after the Sora app is discontinued?\\n\\nAfter Sora is discontinued, and after the period of time of any final export window passes (if we are able to offer one), we will permanently delete any data associated with your use of Sora.\\n\\nHow can I access and export content I created in Sora?\\n\\nYou can export content you created in Sora by going to sora.chatgpt.com/sunset and clicking on Export. You'll get an email when it's ready.\\n\\nWhat if I need a refund?\\n\\nFor refund questions, please see How do I request a refund for my ChatGPT subscription? Note that any purchased ChatGPT/Sora credits can still be used for Codex, if you so choose.\\n\\nRelated articles\\nUsing Credits for Flexible Usage in ChatGPT (Free/Go/Plus/Pro)\\nKey information and FAQs about using credits\\nRetiring GPT-4o and other ChatGPT models\\nGPT-4o and additional models were deprecated in ChatGPT on February 13, 2026. These models will continue to be available in the API.\\nChatGPT OpenAI o3 and o4‑mini models FAQ (Enterprise & Edu Version)\\nWas this article helpful?\\nSubmit\\nWhen will Sora be discontinued?\\nWill I be able to export my data after the Sora app is discontinued?\\nWhat happens to my data after the Sora app is discontinued?\\nHow can I access and export content I created in Sora?\\nWhat if I need a refund?\\nChatGPT\\nAPI\\nService Status\\nCookie Preferences\\n\\nWe use cookies and similar technologies to deliver, maintain, improve our services and for security purposes.\\n\\nCheck our Cookie Policy for details. Click 'Accept all' to let OpenAI and partners use cookies for these purposes. Click 'Reject all' to say no to cookies, except those that are strictly necessary. You can change your cookie settings at any time by clicking the cookie preferences link at the bottom of the page.\\n\\nReject All\\nAccept All\", \"result_type\": \"str\"}\n\n[Tool loop warning: idempotent_no_progress_warning; count=2; browser_console returned the same result 2 times. Use the result already provided or change the query instead of repeating it unchanged.]", "tool_call_id": "call_EXpJcn7QSSxVlocDtCYVRqmf" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_ZTKPRtrqwmKBPUL8ThCeJ2i5", "call_id": "call_ZTKPRtrqwmKBPUL8ThCeJ2i5", "response_item_id": "fc_0d1a4d10654d56b4016a11939515608191a4864621ddd545ec", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"https://help.openai.com/en/?q=Using%20Credits%20for%20Flexible%20Usage%20in%20ChatGPT\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Investigating navigation issues**\n\nIt looks like the click didn't lead to navigation. I wonder if the link reference is stale or maybe something's off in the destination. Should I try a search instead? It's interesting how sometimes things just don’t work as expected. Let’s explore options to figure this out. I'll keep checking to find a way to get the navigation working smoothly!", "reasoning_content": "**Investigating navigation issues**\n\nIt looks like the click didn't lead to navigation. I wonder if the link reference is stale or maybe something's off in the destination. Should I try a search instead? It's interesting how sometimes things just don’t work as expected. Let’s explore options to figure this out. I'll keep checking to find a way to get the navigation working smoothly!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZOV2u2hkjznqCySXa5ax5tNG3FfagL7ItVeuvOj0jzsPAkSksJ3G-NQmKmeEJn7V7tzozoiemIn_PwvSaKoVWy9fbiVvepg9vPrZYzkYwCxiqcnJUtaXUZSTi9w5-4QgkhgPPpPEC0rNqeMfOJHJr74VWbEPGhDaf2Uyf8H4OReGlxkT6a3jcirNx42zIQ6R0b1bE6e2UPsiJ_uyLZJcBxukkmq6Tb1Cad_hRmFrNaaS3dL8HM4LHnWsc1LqCk_bnWCnlrFyzRl9XrBDP-84slEyH-4yLx5K7A8cYt03cPh7Ad87O994rn_baBM0ZbEwveCtjh7hpR1PqfGljJwmHgTpvSc-dst4RKNgmxvEaVEMKYEqjE9t7xqYcVx89ZWTCRKBuJfjxtaqWE3LP6X6vhOhHXVlOWd-XbxGRtfSIjr4SBMCYbrYD7Qh69NnXtPP_5vn_hJucTMif3T6rkbJesn4e4fLmqWWK2OZISku8Jejt28oCJG-D42OE7d402ToDhPelDs8-Os3zv_wN4b1PrRamg80JKu3bZWEMNawFM9PnZ90mHbLKDo0-suXpboQq4xB4SPCDVqSGZ07Y-6bEn5iDLbpH2ONW5EVWIAyRVISJTooMro8cZZyQtiZUYI6twr9U3O6xn8dtB5_78cRI55Jn-Q12dchQetuYDjtyi41lDIoxf1Qrf0ocBdbvZUgSHu1iD_m3uspWc6RaJvUVDlifflRKP5STCzil_tg6tdwSSa8z2_MgKfZH6QnYwcAd4ADz6M17gauCDBIJWhJxNYmyC6qaTykMgqpeIr5lEaKXQ2rDUIoPK6lsWAJgil-wkFxPpBebMQKNBOpGwQ7B3qhD38q4JCafW86nSEFsVYlO4VMDyeUEsVXGxsRz5j6vdwa25YHy4cr_m1ICCbzd6GVFDZZFXFzWiznjhLTjqlIEOSzsVlyiLE14VccESqQ2yZkkRB2nYxzN1LPZxUqcqDCGLjkmkpHZxgYN1f9hX8lmE=", "id": "rs_0d1a4d10654d56b4016a11939310508191b9069ab57746934b", "summary": [ { "type": "summary_text", "text": "**Investigating navigation issues**\n\nIt looks like the click didn't lead to navigation. I wonder if the link reference is stale or maybe something's off in the destination. Should I try a search instead? It's interesting how sometimes things just don’t work as expected. Let’s explore options to figure this out. 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Terms of Service\\nChatGPT — Release Notes\\n\\nA changelog of the latest updates and release notes for ChatGPT\\n\\nA changelog of the latest updates and release notes for ChatGPT\\n\\nCodex rate card\\n\\nLearn how Codex credit rates work across Plus, Pro, Business, Enterprise, Edu, Health, and Gov plans.\\n\\nLearn how Codex credit rates work across Plus, Pro, Business, Enterprise, Edu\\n\\nChatGPT Rate Card (Business, Enterprise/Edu)\\n\\nFlexible pricing rate card for the Business and Enterprise/Edu plans\\n\\nFlexible pricing rate card for the Business and Enterprise… This article outlines the current rates for ChatGPT models and features under the flexible pricing structure… For more information about how flexible pricing works, please refer to our article: Flexible… For rates for Plus/Pro plans, please refer to our article: Using Credits for Flexible Usage in ChatGPT (Free/Go/Plus\\n\\nChatGPT for Excel and Google Sheets\\n\\nUse ChatGPT in Excel and Google Sheets to build, update, and understand spreadsheets, and learn how setup works for your plan.\\n\\nUse ChatGPT in Excel and Google Sheets to build, update\\n\\nUsing Credits for Flexible Usage in ChatGPT (Free/Go/Plus/Pro)\\n\\nKey information and FAQs about using credits\\n\\nKey information and FAQs about using credits\\n\\nFlexible pricing for the Enterprise, Edu, and Business plans\\n\\nFrequently asked questions and key information about flexible pricing\\n\\nFrequently asked questions and key information about flexible pricing\\n\\nManaging credits and spend controls in ChatGPT Business\\n\\nLearn when ChatGPT Business needs credits, how to add credits and auto-top-up, and how to review usage analytics and spend controls for Codex.\\n\\nLearn when ChatGPT Business needs credits, how to add credits and… Learn when ChatGPT Business needs credits, how to add credits and auto-top-up, and how to review usage analytics and spend controls for Codex.\\n\\nWhat is ChatGPT Business?\\n\\nLearn what ChatGPT Business is, how different seat types work, and how pricing, privacy, and admin controls work.\\n\\nLearn what ChatGPT Business is, how different seat types work, and… ChatGPT Business is a self-serve plan designed for… ChatGPT Business is a self-serve plan designed for organizations that want a shared ChatGPT workspace for their teams.… Admin controls for managing users, roles, and access Usage visibility and spend controls Acce\\n\\nWhat is ChatGPT Enterprise?\\n\\nLearn what ChatGPT Enterprise includes, how organizations and members get access, how workspaces and seat types behave, and what happens when you migrate from an individual paid plan.\\n\\nLearn what ChatGPT Enterprise includes, how organizations and members get access… ChatGPT Enterprise is a managed ChatGPT plan for organizations.… with centralized admin controls and access to advanced ChatGPT capabilities.… ChatGPT Enterprise includes\\n\\nWhat is prepaid billing?\\nManaging billing and seats in ChatGPT Business\\n\\nLearn how standard ChatGPT seats, Codex seats, credits, and billing cadence work in ChatGPT Business.\\n\\nLearn how standard ChatGPT seats, Codex seats, credits, and billing cadence work… Learn how standard ChatGPT seats, Codex seats, credits, and billing cadence work in ChatGPT Business.\\n\\nCodex for Business Promotion: Earn up to $500 in Credits\\n\\nTerms for our ChatGPT Business Codex Promotion\\n\\nTerms for our ChatGPT Business Codex Promotion\\n\\nChatGPT Enterprise and Edu - Models & Limits\\n\\nUnderstand which models are best suited for your tasks.\\n\\nChatGPT Enterprise is a subscription plan which offers enterprise… Learn how ChatGPT can transform your organization.… If you are on ChatGPT flexible pricing, please refer to this page for… Please note that access to GPT-5.5 Instant is by default disabled for ChatGPT Enterprise workspaces.\\n\\nChatGPT Business - Models & Limits\\n\\nThe ChatGPT Business subscription is a self-serve subscription plan… designed for organizations and businesses wishing to adopt ChatGPT for use among their teams.… ChatGPT Business is available for 2 or more users.… If you're looking for a larger option, please consider ChatGPT Enterprise.\\n\\nChatGPT\\nAPI\\nService Status\\nCookie Preferences\\n\\nWe use cookies and similar technologies to deliver, maintain, improve our services and for security purposes.\\n\\nCheck our Cookie Policy for details. Click 'Accept all' to let OpenAI and partners use cookies for these purposes. Click 'Reject all' to say no to cookies, except those that are strictly necessary. You can change your cookie settings at any time by clicking the cookie preferences link at the bottom of the page.\\n\\nReject All\\nAccept All\", \"result_type\": \"str\"}", "tool_call_id": "call_l9eCm9RUkGOjo4M5jv56icZ4" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_9iT6JHcVVCMkxb7ukbYqvxjY", "call_id": "call_9iT6JHcVVCMkxb7ukbYqvxjY", "response_item_id": "fc_0d1a4d10654d56b4016a1193afb44081918db65cb10e277b3b", "type": "function", "function": { "name": "browser_console", "arguments": "{\"expression\":\"Array.from(document.querySelectorAll('a')).map(a=>({text:a.innerText, href:a.href})).filter(x=>x.text.includes('Using Credits'))\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Exploring click issues**\n\nI need to address a click issue, and I think using JavaScript to find the href might be the right way to go. That's a straightforward way to pull the link associated with the click, ensuring I get the right target. 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When your credit balance drops below your selected minimum balance, we automatically purchase only the amount needed to return it to your selected target balance using your default payment method on file. If your balance is already below the minimum when you turn it on, a purchase may happen right away.\\\"\\n - LineBreak \\\"\\\\n\\\"\\n - LineBreak \\\"\\\\n\\\"\\n - LineBreak \\\"\\\\n\\\"\\n - StaticText \\\"Note: Auto top-up applies to your shared credits balance, so those credits can still be used across supported features like Codex and ChatGPT for Excel.\\\"\\n - LineBreak \\\"\\\\n\\\"\\n - LineBreak \\\"\\\\n\\\"\\n - StaticText \\\"See your balance on ChatGPT web by navigating to Codex Settings > Usage Dashboard. This shows credits balance and recent usage.\\\"\\n - heading \\\"Rate Card\\\" [level=2, ref=e12]\\n - heading \\\"Codex\\\" [level=3, ref=e13]\\n - paragraph\\n - StaticText \\\"For Codex rates, refer to the \\\"\\n - link \\\"Codex rate card\\\" [ref=e32]\\n - StaticText \\\".\\\"\\n - heading \\\"ChatGPT for Excel\\\" [level=3, ref=e14]\\n - table\\n - rowgroup\\n - row\\n - columnheader \\\"Model\\\" [ref=e65]\\n - columnheader \\\"Input tokens\\\" [ref=e66]\\n - columnheader \\\"Cached input tokens\\\" [ref=e67]\\n - columnheader \\\"Output tokens\\\" [ref=e68]\\n - row\\n - cell \\\"GPT-5.5\\\" [ref=e43]\\n - cell \\\"125 credits\\\" [ref=e44]\\n - cell \\\"12.50 credits\\\" [ref=e45]\\n - cell \\\"750 credits\\\" [ref=e46]\\n - paragraph\\n - heading \\\"FAQs\\\" [level=2, ref=e15]\\n - heading \\\"Can I use the same credits for different features?\\\" [level=3, ref=e16]\\n - paragraph\\n - heading \\\"Can I use auto top-up with credits?\\\" [level=3, ref=e17]\\n - paragraph\\n - heading \\\"Are credits refundable?\\\" [level=3, ref=e18]\\n - paragraph\\n - heading \\\"Do credits expire or roll over?\\\" [level=3, ref=e19]\\n - paragraph\\n - heading \\\"What happens if credits are used due to a compromised account?\\\" [level=3, ref=e20]\\n - paragraph\\n - StaticText \\\"If your account is compromised and credits are used without authorization, contact support@openai.com immediately. We will investigate the incident, restore lost credits if misuse is confirmed, and assist with password resets and security controls. We also recommend that you take immediate steps to secure the account by following the steps outlined here: https://help.openai.com/en/articles/7242626-how-can-i-report-fraud-or-suspicious-activity\\\"\\n - heading \\\"Are credits transferable?\\\" [level=3, ref=e21]\\n - paragraph\\n - heading \\\"What terms govern the purchase of credits?\\\" [level=3, ref=e22]\\n - paragraph\\n - StaticText \\\"Credits are subject to the above and the Service credit terms: https://openai.com/policies/service-credit-terms/\\\"\\n- generic\\n - heading \\\"Related articles\\\" [level=2, ref=e23]\\n - list\\n - listitem [level=1]\\n - link \\\"ChatGPT — Release Notes A changelog of the latest updates and release notes for ChatGPT\\\" [ref=e47]\\n - listitem [level=1]\\n - link \\\"ChatGPT Rate Card (Business, Enterprise/Edu) Flexible pricing rate card for the Business and Enterprise/Edu plans\\\" [ref=e48]\\n - listitem [level=1]\\n - link \\\"Flexible pricing for the Enterprise, Edu, and Business plans Frequently asked questions and key information about flexible pricing\\\" [ref=e49]\\n- generic\\n - heading \\\"Was this article helpful?\\\" [level=2, ref=e24]\\n - generic\\n - button \\\"Thumbs up\\\" [ref=e33]\\n - button \\\"Thumbs down\\\" [ref=e34]\\n - textbox \\\"Additional feedback (optional)\\\" [ref=e35]\\n - button \\\"Submit\\\" [disabled, ref=e50]\\n- navigation \\\"Table of contents\\\" [ref=e4]\\n - list\\n - listitem [level=1]\\n - link \\\"Overview\\\" [ref=e51]\\n - listitem [level=1]\\n - link \\\"What changes for my plan\\\" [ref=e52]\\n - listitem [level=1]\\n - link \\\"How credits work\\\" [ref=e53]\\n - listitem [level=1]\\n - link \\\"Rate Card\\\" [ref=e54]\\n - listitem [level=1]\\n - link \\\"Codex\\\" [ref=e55]\\n - listitem [level=1]\\n - link \\\"ChatGPT for Excel\\\" [ref=e56]\\n - listitem [level=1]\\n - link \\\"FAQs\\\" [ref=e57]\\n - listitem [level=1]\\n - link \\\"Can I use the same credits for different features?\\\" [ref=e58]\\n - listitem [level=1]\\n - link \\\"Can I use auto top-up with credits?\\\" [ref=e59]\\n - listitem [level=1]\\n - link \\\"Are credits refundable?\\\" [ref=e60]\\n - listitem [level=1]\\n - link \\\"Do credits expire or roll over?\\\" [ref=e61]\\n - listitem [level=1]\\n - link \\\"What happens if credits are used due to a compromised account?\\\" [ref=e62]\\n - listitem [level=1]\\n - link \\\"Are credits transferable?\\\" [ref=e63]\\n - listitem [level=1]\\n - link \\\"What terms govern the purchase of credits?\\\" [ref=e64]\\n- contentinfo\\n - image \\\"OpenAI logo\\\"\\n - navigation\\n - link \\\"ChatGPT\\\" [ref=e36]\\n - link \\\"API\\\" [ref=e37]\\n - link \\\"Service Status\\\" [ref=e38]\\n - button \\\"Open cookie preferences dialog\\\" [ref=e39]\\n- button \\\"Open chat\\\" [ref=e5]\\n- generic\\n - paragraph\\n - paragraph\\n - link \\\"Cookie Policy\\\" [ref=e40]\\n - button \\\"Reject all cookies\\\" [ref=e25]\\n - button \\\"Accept all cookies\\\" [ref=e26]\", \"element_count\": 68}", "tool_call_id": "call_Mb0lYY6JgHBeJzyLY6ZSLK3P" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_gNnhug3mWmQcJZ2mUWGGadwj", "call_id": "call_gNnhug3mWmQcJZ2mUWGGadwj", "response_item_id": "fc_0d1a4d10654d56b4016a1193bfad888191b211b93e0c441cb2", "type": "function", "function": { "name": "browser_console", "arguments": "{\"expression\":\"document.body.innerText\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"success\": true, \"result\": \"Language\\nEnglish\\nLogin\\nAll Collections\\nChatGPT\\nUsing Credits for Flexible Usage in ChatGPT (Free/Go/Plus/Pro)\\nUsing Credits for Flexible Usage in ChatGPT (Free/Go/Plus/Pro)\\n\\nKey information and FAQs about using credits\\n\\nUpdated: vorgestern\\n\\nNote: The Sora web and app experiences were discontinued on April 26, 2026. Credits purchased for Sora can be used for Codex, and ChatGPT for Excel once flexible pricing is effective on May 5, 2026. Read more about the Sora discontinuation.\\n\\nOverview\\n\\nWe're adding the ability for you to purchase credits when you reach your plan's included limits, without the need to upgrade your plan. Credits currently can only be used with Codex (for Plus/Pro users only) and ChatGPT for Excel.\\n\\nWhat changes for my plan\\n\\nNothing about your plan changes. You still get your plan's included usage.\\n\\nCredits are a pay-as-you-go add-on for Codex and ChatGPT for Excel when you need more usage beyond plan limits\\n\\nFlexible pricing for Codex is currently available. Flexible pricing for ChatGPT for Excel will take effect starting May 5, 2026.\\n\\nHow credits work\\n\\nYour plan's included usage is used first. After you hit plan limits, usage draws from your credit balance. Read about Codex usage limits.\\n\\nFor Plus and Pro, ChatGPT for Excel usage counts toward the same agentic usage limit as Codex.\\n\\nIf you hit a usage limit in Codex on Plus or Pro, you'll see an option to add credits. You can also buy credits from Codex Settings > Usage > Credits on both web and the Codex app. Free and Go users are prompted to upgrade to Plus instead of adding credits for Codex.\\n\\nEligible Plus and Pro users can also turn on Auto top-up from Codex Settings > Usage. When your credit balance drops below your selected minimum balance, we automatically purchase only the amount needed to return it to your selected target balance using your default payment method on file. If your balance is already below the minimum when you turn it on, a purchase may happen right away.\\n\\n\\nNote: Auto top-up applies to your shared credits balance, so those credits can still be used across supported features like Codex and ChatGPT for Excel.\\n\\nSee your balance on ChatGPT web by navigating to Codex Settings > Usage Dashboard. This shows credits balance and recent usage.\\n\\nRate Card\\nCodex\\n\\nFor Codex rates, refer to the Codex rate card.\\n\\nChatGPT for Excel\\nModel\\n\\t\\nInput tokens\\n\\t\\nCached input tokens\\n\\t\\nOutput tokens\\n\\n\\nGPT-5.5\\n\\t\\n125 credits\\n\\t\\n12.50 credits\\n\\t\\n750 credits\\n\\nA typical ChatGPT for Excel/Sheets task using GPT-5.5 may consume between 5-30 credits per task.\\n\\nFAQs\\nCan I use the same credits for different features?\\n\\nYes. Your credits are flexible - they work across any supported feature available in your plan. Currently, this includes Codex for Plus/Pro subscribers and ChatGPT for Excel for all users (once pricing is effective for that feature).\\n\\nFor example, if you buy credits in Codex, you can use those credits for ChatGPT for Excel features as well, above and beyond included rate limits.\\n\\nCan I use auto top-up with credits?\\n\\nEligible Plus and Pro users can turn on auto top-up from Codex Settings > Usage Dashboard. When your credit balance drops below your selected minimum balance, we automatically purchase only the amount needed to return it to your selected target balance using your default payment method on file. If your balance is already below the minimum when you turn it on, a purchase may happen right away.\\n\\nAre credits refundable?\\n\\nCredits are non-refundable, except where required by law. We may restore credits in cases of confirmed account compromise (see below).\\n\\nDo credits expire or roll over?\\n\\nCredits are valid for 12 months from purchase. Unused credits expire and do not roll over after the expiry date.\\n\\nWhat happens if credits are used due to a compromised account?\\n\\nIf your account is compromised and credits are used without authorization, contact support@openai.com immediately. We will investigate the incident, restore lost credits if misuse is confirmed, and assist with password resets and security controls. We also recommend that you take immediate steps to secure the account by following the steps outlined here: https://help.openai.com/en/articles/7242626-how-can-i-report-fraud-or-suspicious-activity\\n\\nAre credits transferable?\\n\\nCredits are non-transferable, have no cash value, and cannot be resold or gifted.\\n\\nWhat terms govern the purchase of credits?\\n\\nCredits are subject to the above and the Service credit terms: https://openai.com/policies/service-credit-terms/\\n\\nRelated articles\\nChatGPT — Release Notes\\nA changelog of the latest updates and release notes for ChatGPT\\nChatGPT Rate Card (Business, Enterprise/Edu)\\nFlexible pricing rate card for the Business and Enterprise/Edu plans\\nFlexible pricing for the Enterprise, Edu, and Business plans\\nFrequently asked questions and key information about flexible pricing\\nWas this article helpful?\\nSubmit\\nOverview\\nWhat changes for my plan\\nHow credits work\\nRate Card\\nCodex\\nChatGPT for Excel\\nFAQs\\nCan I use the same credits for different features?\\nCan I use auto top-up with credits?\\nAre credits refundable?\\nDo credits expire or roll over?\\nWhat happens if credits are used due to a compromised account?\\nAre credits transferable?\\nWhat terms govern the purchase of credits?\\nChatGPT\\nAPI\\nService Status\\nCookie Preferences\\n\\nWe use cookies and similar technologies to deliver, maintain, improve our services and for security purposes.\\n\\nCheck our Cookie Policy for details. Click 'Accept all' to let OpenAI and partners use cookies for these purposes. Click 'Reject all' to say no to cookies, except those that are strictly necessary. You can change your cookie settings at any time by clicking the cookie preferences link at the bottom of the page.\\n\\nReject All\\nAccept All\", \"result_type\": \"str\"}", "tool_call_id": "call_gNnhug3mWmQcJZ2mUWGGadwj" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_qyI9CemED0demRrGiNvzzKC3", "call_id": "call_qyI9CemED0demRrGiNvzzKC3", "response_item_id": "fc_0d1a4d10654d56b4016a1193c8e8648191ab0959fa5d855307", "type": "function", "function": { "name": "write_file", "arguments": "{\"content\":\"from pathlib import Path\\n\\nfrom autoshorts.imported_clip_assembler import build_imported_clip_assembly_plan, discover_imported_ai_clips\\n\\n\\nVIDEO_ID = \\\"hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann\\\"\\n\\n\\ndef _production_jobs() -> dict:\\n return {\\n \\\"schema_version\\\": \\\"free_production_jobs.v1\\\",\\n \\\"video\\\": {\\\"id\\\": VIDEO_ID, \\\"title\\\": \\\"Warum ein billiges Auto teuer sein kann\\\", \\\"duration_ms\\\": 34000},\\n \\\"jobs\\\": [\\n {\\n \\\"scene_id\\\": \\\"scene_01\\\",\\n \\\"asset_mode\\\": \\\"cinematic_ai_video\\\",\\n \\\"provider\\\": \\\"local_renderer\\\",\\n \\\"execution_mode\\\": \\\"procedural_motion\\\",\\n \\\"duration_seconds\\\": 1.4,\\n \\\"overlay_text\\\": \\\"Dieser Occasion-Käufer denkt, er spart 4'000 Franken.\\\",\\n },\\n {\\n \\\"scene_id\\\": \\\"scene_02\\\",\\n \\\"asset_mode\\\": \\\"cinematic_ai_video\\\",\\n \\\"provider\\\": \\\"local_renderer\\\",\\n \\\"execution_mode\\\": \\\"procedural_motion\\\",\\n \\\"duration_seconds\\\": 3.6,\\n \\\"overlay_text\\\": \\\"Das sieht harmlos aus.\\\",\\n },\\n {\\n \\\"scene_id\\\": \\\"scene_03\\\",\\n \\\"asset_mode\\\": \\\"mechanism_animation\\\",\\n \\\"provider\\\": \\\"local_renderer\\\",\\n \\\"execution_mode\\\": \\\"mechanism_reveal_animation\\\",\\n \\\"duration_seconds\\\": 13,\\n \\\"overlay_text\\\": \\\"Röntgenblick durch Preis...\\\",\\n },\\n ],\\n }\\n\\n\\ndef test_discover_imported_ai_clips_finds_only_scene_named_video_files(tmp_path):\\n clip_dir = tmp_path / VIDEO_ID\\n clip_dir.mkdir(parents=True)\\n (clip_dir / \\\"scene_01.mp4\\\").write_bytes(b\\\"fake\\\")\\n (clip_dir / \\\"scene_02.mov\\\").write_bytes(b\\\"fake\\\")\\n (clip_dir / \\\"notes.txt\\\").write_text(\\\"ignore\\\", encoding=\\\"utf-8\\\")\\n\\n clips = discover_imported_ai_clips(VIDEO_ID, tmp_path)\\n\\n assert set(clips) == {\\\"scene_01\\\", \\\"scene_02\\\"}\\n assert clips[\\\"scene_01\\\"] == clip_dir / \\\"scene_01.mp4\\\"\\n assert clips[\\\"scene_02\\\"] == clip_dir / \\\"scene_02.mov\\\"\\n\\n\\ndef test_build_imported_clip_assembly_plan_prefers_imported_realistic_clips_and_local_fallbacks(tmp_path):\\n clip_dir = tmp_path / VIDEO_ID\\n clip_dir.mkdir(parents=True)\\n (clip_dir / \\\"scene_01.mp4\\\").write_bytes(b\\\"fake\\\")\\n\\n plan = build_imported_clip_assembly_plan(_production_jobs(), imported_root=tmp_path)\\n\\n assert plan[\\\"schema_version\\\"] == \\\"imported_clip_assembly.v1\\\"\\n assert plan[\\\"video\\\"][\\\"id\\\"] == VIDEO_ID\\n assert plan[\\\"budget_policy\\\"][\\\"paid_video_credits_allowed\\\"] is False\\n assert plan[\\\"final_assembly\\\"] == \\\"local_ffmpeg\\\"\\n\\n scene_01 = plan[\\\"scenes\\\"][0]\\n scene_02 = plan[\\\"scenes\\\"][1]\\n scene_03 = plan[\\\"scenes\\\"][2]\\n\\n assert scene_01[\\\"source\\\"] == \\\"imported_ai_clip\\\"\\n assert scene_01[\\\"clip_path\\\"] == str(clip_dir / \\\"scene_01.mp4\\\")\\n assert scene_01[\\\"captions_added_locally\\\"] is True\\n\\n assert scene_02[\\\"source\\\"] == \\\"local_renderer_fallback\\\"\\n assert scene_02[\\\"missing_expected_clip\\\"] == str(clip_dir / \\\"scene_02.mp4\\\")\\n\\n assert scene_03[\\\"source\\\"] == \\\"local_renderer\\\"\\n assert scene_03[\\\"role\\\"] == \\\"mechanism_or_caption_layer\\\"\\n\\n\\ndef test_chatgpt_pro_video_generation_is_marked_unavailable_in_assembly_notes(tmp_path):\\n plan = build_imported_clip_assembly_plan(_production_jobs(), imported_root=tmp_path)\\n\\n openai_note = next(note for note in plan[\\\"provider_notes\\\"] if note[\\\"provider\\\"] == \\\"chatgpt_pro_sora\\\")\\n\\n assert openai_note[\\\"available_for_new_video_generation\\\"] is False\\n assert \\\"Sora web and app experiences were discontinued on April 26, 2026\\\" in openai_note[\\\"evidence\\\"]\\n assert openai_note[\\\"decision\\\"] == \\\"do_not_use_for_new_video_generation\\\"\\n\",\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/tests/test_imported_clip_assembler.py\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering video provider integration**\n\nI'm thinking about adding a video provider since the ChatGPT Pro video isn't currently available. Maybe I could incorporate a module like openai_subscription_video.py or find a simpler way to augment the registry. It seems important to include any unavailable providers, and testing this in new tests sounds like a good plan. Using Test-Driven Development (TDD) could help ensure everything functions correctly while I work on this.", "reasoning_content": "**Considering video provider integration**\n\nI'm thinking about adding a video provider since the ChatGPT Pro video isn't currently available. Maybe I could incorporate a module like openai_subscription_video.py or find a simpler way to augment the registry. It seems important to include any unavailable providers, and testing this in new tests sounds like a good plan. Using Test-Driven Development (TDD) could help ensure everything functions correctly while I work on this.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZPI7f9DHhBK9uUODcBbbfl_nrBqPK6BCLYH-NYCp0oha74O9hGgGcz0zOCty9o6vGWd4irnD1umnPAk7lkHKHQF_nn7HYIY4cCLU_-5asJ_2pWhTw38QcSwip7lXk6gofksPE3mW6rcpJTjcaIX3AcvUaP5pPVkZsu-vlWgk1ZSwUH6XBU-j8uNBcFluIDTFGoU85MxB51SMADpWZdEyJ7DGLOxH4fea5E6CtXBXxOSs1st3tCe-69Z33krAmOoSTLCEcV_MFRNvU1Nm73VfWMevMoYJWQ8bdxV0APjBUO1pS-27taT5AIuSNsE6qvoK6z6mOi3nDOzmPPoIky38KaPak7g660GHU64RhQCNwtBpCaFEMnLD3jOj0Gu9R-bzdBRSeYB3rcMkuPK8McOpbJokqUsd84cK7YPpPNq8pitDc_zRxYRpzQkeCJqLXGI-eCRg5RqxpN2Bzh2ITVLlitLxB08hPzpJTLD6I1nD9iqq5jFDTZNnwApbLdz0_WVhhdXFxy273gLQMitsUnmNuf50ojctUxeNhwK-z8mDEwerCUrY9q3j9rMNu9HKBK5JTWvYjZH9gsG7842uxMUE3rJXhUriUh3bkXLbJ16NG6bdVkKgpavys5z5o_zu6ASdBT98DT4mWaPhlFrrWwY0gm_ZHyh1xE7gxcPvVR2tVllqgejALmOsOW5CshRnVOh6SSLTyv_MAAjpwx18w4IZJyQO3OiXRrS7jTuEZLYmYlOEd7OE3bvg0S1t0QZjtflvGwxxmppHMT_XbMXfV6mBs8B49ykVrIXBTNpc6ynB0uJIQtmLTYhivVyHu_gC9hu45cw2VItp9R0tP8IhnLnW2JHxRU8zfq8Za-8LNC1J9m0DGPSZuPc5BiUGIOSKERAPvdO0No980I5bfYcpliomBDuY072GoEm9cF36RNzEmko-2OOsahkmdB8Axp210qj-nONyrqXV4YHYabevpFqiyJM3RUVUq5LpKffaraThQ2rpelHtuu0LCQRgyX6se0Z7V_bSindyr_EZQm-50BbQJ9Q-NN3O7LfCF26nL5LYcwk3aGEgIJ94PtB2cnDwHPmPcysQnWvg0v24QM2gC5g0ePUWcTSPGWVsav94ww74sDzbbgVsM_8zysAnwcRKF_UShRn9mOdgg2DVatgSEbOXBlwtP59Igfmi-eUnVBF8ddsayBfztChGEqTVbeVtegbKbITwVP2WVOBGIBgbfjSFGiMCA8MmJNfVdH5SQ8Y8MYmf1neYtRNf_lvUH6MMuq5w55ujPZDinlLzmx0K_rg2RNxzIn_SaW66EnihyT9hSPHSlQoyJZaJoSgL71Wru_apSGwEJP9dLaUzc4WlCOjVGHibJ80S4sJkz4imD2ZX07RmjBwchQOZmg8wBifalACmaojjbkb4zlHQ_kAcD8nyazFxSVLJje2EQeFuzpHQE1plDbYz40ggLu01ahog3KRRjkNK6B3neB6FCzBfOjPFHHlBZ6XdmcKLWA7C4Q19dnW3cDCOe057ClW_8taSxhPhN8AcFv_JuBPlNPZ1MpZW3yaaEeaiJUuKtc2hUtkHKmVJMajbJs-PiaAk_U-oCVMLHejQyPNgi3EwhLGDa9UAeoB9EPLTzr1OKrXEVWLKG5EWIXnmhOnPBQ-MN2zim7wQ9MaW2ybjDTlGlfCVMOWN00njTo0tEwprTZKWHgC8fMrYNvhCLbQXVx9_lg-1D9lfAWmxgSgMHcGw2dZ2Vf0XjiTbn514X6vYKgpCPFKJenQor7Eyv0Bunah8qOkdlpH7eX2FsDXp9jLshb54JivwbCJ1KkQk2wJVUchaIP9ldq7RrwKDQHWOhiWXGg_Wm7uXT2M9iX8NKI8Wlq56NFyNrr4QxzMXCy0V5qJOrEUMNWBAP0JetiJJwKu8RJnd7WMsWsPAlTm4pruHtSPSGYqz9eY9bFkEUkTZsWXUhKZghf2A3QnUvZwzIADhMAzRYDDTxGRICdpG_dFGp5RqJt6dt7eDlR_LaGf6yYu8rWpPR38lNq35QK7D4p5cjDJmQV5LCXk6nIvr6P8h7X7aKR8fYItC7o6SMA0jt1UUGyLjTJFyPehgNYY_14XznGcjYb3uG4b17qEZxaNm_FZmh_w_w2MFuPD63NaDbAy20rQqAFmJ8Qtpp7ErcpjL9VO8cry3hbvdKijf_iXGq86c1e8uQn_GJaEpG-Bc3ldz-2tBs0XkrgovpFmoyOAbHf9tHLLvdrJ6lHjbBQtokIiXPHlAxzBWdlwhSShK8UnkcbVKNpo2PHlBUWesY3upj4eHbbfXsCXKsAiMoVl0sSeGLOePX_JUas9BS0t4hm66B-BJGnnkng57jtEUkDLYS-pygoCMBPC488p5BN5nyxwnhQN7wSlOHOjNSbg0GCqmhjbnij1I2UNjpAESSXU8fSFUwK8QrwS_QmdQgTXeSS-rNV3OMRozYovG2tI-UyVkwbVyqVTfPa9nUyl805mFoQ8W-K668y7x1tYXZo1XCHPSVi-zyZChAPzVJXRsNdie8TuQ_x94bRB1g_EH7ztm1zYbPXP5jRCgi7pHn189MwTDu1hiRmc6LZ1SK1ZUkSfqiDvqRFJKY7a7M9Vx_ubcAXxwIXqXdf4krlII8afreS9IK0EdzjGQswJuXt-MfDXGa8TcsK6yqHBACwavxa_SrIqLNrELlRfCmwAZiXBBpVoFgh4zkiKli-6wC7aL5WjFtwAg34rIAM=", "id": "rs_0d1a4d10654d56b4016a1193c2d8c88191a20458150f35ef78", "summary": [ { "type": "summary_text", "text": "**Considering video provider integration**\n\nI'm thinking about adding a video provider since the ChatGPT Pro video isn't currently available. Maybe I could incorporate a module like openai_subscription_video.py or find a simpler way to augment the registry. It seems important to include any unavailable providers, and testing this in new tests sounds like a good plan. Using Test-Driven Development (TDD) could help ensure everything functions correctly while I work on this." } ] } ] }, { "role": "tool", "content": "{\"bytes_written\": 3634, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"lsp_diagnostics\": \"LSP diagnostics introduced by this edit:\\n\\nERROR [3:6] Import \\\"autoshorts.imported_clip_assembler\\\" could not be resolved [reportMissingImports] (Pyright)\\n\"}", "tool_call_id": "call_qyI9CemED0demRrGiNvzzKC3" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_hWOUfJESh35mDkXKSlaxNZlW", "call_id": "call_hWOUfJESh35mDkXKSlaxNZlW", "response_item_id": "fc_0d1a4d10654d56b4016a1193e233a48191baf0e3ade4eea4b5", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_imported_clip_assembler.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"output\": \"==================================== ERRORS ====================================\\n____________ ERROR collecting tests/test_imported_clip_assembler.py ____________\\nImportError while importing test module '/home/agent/jarvis_runtime/AutoShortsBot/tests/test_imported_clip_assembler.py'.\\nHint: make sure your test modules/packages have valid Python names.\\nTraceback:\\n../../.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/importlib/__init__.py:126: in import_module\\n return _bootstrap._gcd_import(name[level:], package, level)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\ntests/test_imported_clip_assembler.py:3: in \\n from autoshorts.imported_clip_assembler import build_imported_clip_assembly_plan, discover_imported_ai_clips\\nE ModuleNotFoundError: No module named 'autoshorts.imported_clip_assembler'\\n=========================== short test summary info ============================\\nERROR tests/test_imported_clip_assembler.py\\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\\n1 error in 0.10s\", \"exit_code\": 2, \"error\": null}", "tool_call_id": "call_hWOUfJESh35mDkXKSlaxNZlW" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_pEAAx8gIjsYEtAkB5d4fV4Xc", "call_id": "call_pEAAx8gIjsYEtAkB5d4fV4Xc", "response_item_id": "fc_0d1a4d10654d56b4016a1193e869b4819196c468c97dcd5762", "type": "function", "function": { "name": "write_file", "arguments": "{\"content\":\"\\\"\\\"\\\"Assemble imported free-tier AI clips with local renderer fallbacks.\\n\\nThe module builds a deterministic assembly plan. It does not buy credits, call\\npaid APIs, or automate browser accounts. Human-generated/free-tier clips can be\\nplaced under data/imported_ai_clips//.mp4 and then combined\\nwith local mechanism/caption rendering in a later assembly step.\\n\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nimport json\\nfrom pathlib import Path\\nfrom typing import Any\\n\\nfrom autoshorts.script_drafts import _slug\\n\\nVIDEO_EXTENSIONS = {\\\".mp4\\\", \\\".mov\\\", \\\".webm\\\", \\\".mkv\\\"}\\nAI_VIDEO_MODES = {\\\"cinematic_ai_video\\\"}\\nLOCAL_LAYER_MODES = {\\\"mechanism_animation\\\", \\\"kinetic_text_overlay\\\", \\\"screen_recording_simulation\\\", \\\"animated_card\\\"}\\n\\nCHATGPT_PRO_SORA_NOTE = {\\n \\\"provider\\\": \\\"chatgpt_pro_sora\\\",\\n \\\"available_for_new_video_generation\\\": False,\\n \\\"decision\\\": \\\"do_not_use_for_new_video_generation\\\",\\n \\\"evidence\\\": (\\n \\\"OpenAI Help Center states: Sora web and app experiences were discontinued on April 26, 2026; \\\"\\n \\\"Sora API will be discontinued on September 24, 2026; current ChatGPT credits can only be used with Codex and ChatGPT for Excel.\\\"\\n ),\\n \\\"source_urls\\\": [\\n \\\"https://help.openai.com/en/articles/20001152-what-to-know-about-the-sora-discontinuation\\\",\\n \\\"https://help.openai.com/en/articles/12642688-using-credits-for-flexible-usage-in-chatgpt-freegopluspro\\\",\\n ],\\n}\\n\\n\\ndef discover_imported_ai_clips(video_id: str, imported_root: Path = Path(\\\"data/imported_ai_clips\\\")) -> dict[str, Path]:\\n \\\"\\\"\\\"Return imported clip files keyed by scene_id for a video.\\\"\\\"\\\"\\n clip_dir = imported_root / video_id\\n if not clip_dir.exists():\\n return {}\\n clips: dict[str, Path] = {}\\n for path in sorted(clip_dir.iterdir()):\\n if path.is_file() and path.suffix.lower() in VIDEO_EXTENSIONS and path.stem.startswith(\\\"scene_\\\"):\\n clips[path.stem] = path\\n return clips\\n\\n\\ndef _render_jobs(production_jobs: dict[str, Any]) -> list[dict[str, Any]]:\\n return [job for job in production_jobs[\\\"jobs\\\"] if job.get(\\\"provider\\\") in {\\\"local_renderer\\\", \\\"local_ffmpeg\\\"}]\\n\\n\\ndef _video_filename(video: dict[str, Any]) -> str:\\n title_slug = _slug(video[\\\"title\\\"])\\n video_id = video[\\\"id\\\"]\\n if video_id.endswith(title_slug):\\n return f\\\"{video_id}.json\\\"\\n return f\\\"{video_id}-{title_slug}.json\\\"\\n\\n\\ndef _scene_plan(job: dict[str, Any], video_id: str, imported_clips: dict[str, Path], imported_root: Path) -> dict[str, Any]:\\n scene_id = job[\\\"scene_id\\\"]\\n asset_mode = job[\\\"asset_mode\\\"]\\n base = {\\n \\\"scene_id\\\": scene_id,\\n \\\"asset_mode\\\": asset_mode,\\n \\\"duration_seconds\\\": job[\\\"duration_seconds\\\"],\\n \\\"overlay_text\\\": job.get(\\\"overlay_text\\\", \\\"\\\"),\\n \\\"captions_added_locally\\\": True,\\n }\\n\\n if asset_mode in AI_VIDEO_MODES:\\n imported_path = imported_clips.get(scene_id)\\n if imported_path:\\n return {\\n **base,\\n \\\"source\\\": \\\"imported_ai_clip\\\",\\n \\\"clip_path\\\": str(imported_path),\\n \\\"role\\\": \\\"realistic_broll_under_local_captions\\\",\\n \\\"validation_required\\\": [\\\"duration\\\", \\\"aspect_ratio\\\", \\\"watermark_check\\\", \\\"no_baked_caption_check\\\"],\\n }\\n return {\\n **base,\\n \\\"source\\\": \\\"local_renderer_fallback\\\",\\n \\\"missing_expected_clip\\\": str(imported_root / video_id / f\\\"{scene_id}.mp4\\\"),\\n \\\"role\\\": \\\"placeholder_until_free_tier_clip_is_imported\\\",\\n }\\n\\n if asset_mode in LOCAL_LAYER_MODES:\\n return {\\n **base,\\n \\\"source\\\": \\\"local_renderer\\\",\\n \\\"role\\\": \\\"mechanism_or_caption_layer\\\",\\n \\\"execution_mode\\\": job.get(\\\"execution_mode\\\", \\\"local_motion\\\"),\\n }\\n\\n return {\\n **base,\\n \\\"source\\\": \\\"local_renderer_fallback\\\",\\n \\\"role\\\": \\\"unknown_mode_local_safe_default\\\",\\n }\\n\\n\\ndef build_imported_clip_assembly_plan(\\n production_jobs: dict[str, Any],\\n imported_root: Path = Path(\\\"data/imported_ai_clips\\\"),\\n) -> dict[str, Any]:\\n \\\"\\\"\\\"Build a plan that swaps imported realistic clips into local assembly.\\\"\\\"\\\"\\n video = production_jobs[\\\"video\\\"]\\n video_id = video[\\\"id\\\"]\\n imported_clips = discover_imported_ai_clips(video_id, imported_root)\\n scenes = [_scene_plan(job, video_id, imported_clips, imported_root) for job in _render_jobs(production_jobs)]\\n return {\\n \\\"schema_version\\\": \\\"imported_clip_assembly.v1\\\",\\n \\\"video\\\": video,\\n \\\"budget_policy\\\": {\\n \\\"paid_video_credits_allowed\\\": False,\\n \\\"paid_openai_video_generation_available\\\": False,\\n \\\"manual_free_tier_import_only\\\": True,\\n },\\n \\\"provider_notes\\\": [CHATGPT_PRO_SORA_NOTE],\\n \\\"imported_root\\\": str(imported_root),\\n \\\"final_assembly\\\": \\\"local_ffmpeg\\\",\\n \\\"scenes\\\": scenes,\\n \\\"summary\\\": {\\n \\\"imported_ai_clip_count\\\": sum(1 for scene in scenes if scene[\\\"source\\\"] == \\\"imported_ai_clip\\\"),\\n \\\"local_fallback_count\\\": sum(1 for scene in scenes if scene[\\\"source\\\"] == \\\"local_renderer_fallback\\\"),\\n \\\"local_renderer_count\\\": sum(1 for scene in scenes if scene[\\\"source\\\"] == \\\"local_renderer\\\"),\\n },\\n }\\n\\n\\ndef write_imported_clip_assembly_plans(\\n production_jobs_list: list[dict[str, Any]],\\n output_dir: Path,\\n imported_root: Path = Path(\\\"data/imported_ai_clips\\\"),\\n) -> list[Path]:\\n \\\"\\\"\\\"Write assembly plans as JSON files.\\\"\\\"\\\"\\n output_dir.mkdir(parents=True, exist_ok=True)\\n paths: list[Path] = []\\n for production_jobs in production_jobs_list:\\n plan = build_imported_clip_assembly_plan(production_jobs, imported_root=imported_root)\\n path = output_dir / _video_filename(plan[\\\"video\\\"])\\n path.write_text(json.dumps(plan, indent=2, ensure_ascii=False) + \\\"\\\\n\\\", encoding=\\\"utf-8\\\")\\n paths.append(path)\\n return paths\\n\",\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/autoshorts/imported_clip_assembler.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"bytes_written\": 5808, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_pEAAx8gIjsYEtAkB5d4fV4Xc" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_dhleUTNwHseu1BBAYoGsEXoB", "call_id": "call_dhleUTNwHseu1BBAYoGsEXoB", "response_item_id": "fc_0d1a4d10654d56b4016a11940a675c8191a18820d93dea6763", "type": "function", "function": { "name": "write_file", "arguments": "{\"content\":\"\\\"\\\"\\\"Generate imported/free-tier AI clip assembly plans.\\\"\\\"\\\"\\n\\nfrom __future__ import annotations\\n\\nimport argparse\\nimport json\\nimport sys\\nfrom pathlib import Path\\n\\nPROJECT_ROOT = Path(__file__).resolve().parents[1]\\nif str(PROJECT_ROOT) not in sys.path:\\n sys.path.insert(0, str(PROJECT_ROOT))\\n\\nfrom autoshorts.imported_clip_assembler import write_imported_clip_assembly_plans\\n\\n\\ndef _load_jobs(path: Path) -> list[dict]:\\n files = sorted(path.glob(\\\"*.json\\\")) if path.is_dir() else [path]\\n return [json.loads(file.read_text(encoding=\\\"utf-8\\\")) for file in files]\\n\\n\\ndef main() -> None:\\n parser = argparse.ArgumentParser(description=\\\"Generate assembly plans for imported free-tier AI clips.\\\")\\n parser.add_argument(\\\"--jobs\\\", default=\\\"data/free_production_jobs/mechanism_pilots\\\")\\n parser.add_argument(\\\"--imported-root\\\", default=\\\"data/imported_ai_clips\\\")\\n parser.add_argument(\\\"--out\\\", default=\\\"data/imported_clip_assembly_plans/mechanism_pilots\\\")\\n args = parser.parse_args()\\n\\n production_jobs = _load_jobs(Path(args.jobs))\\n paths = write_imported_clip_assembly_plans(\\n production_jobs,\\n Path(args.out),\\n imported_root=Path(args.imported_root),\\n )\\n print(f\\\"Generated {len(paths)} imported clip assembly plans in {args.out}\\\")\\n for path in paths:\\n print(path)\\n\\n\\nif __name__ == \\\"__main__\\\":\\n main()\\n\",\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/scripts/generate_imported_clip_assembly_plans.py\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"bytes_written\": 1350, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_dhleUTNwHseu1BBAYoGsEXoB" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_16bcoFNEnt53WKaoa0zavOy7", "call_id": "call_16bcoFNEnt53WKaoa0zavOy7", "response_item_id": "fc_0d1a4d10654d56b4016a119415d86c8191a125640f228ce083", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"pytest tests/test_imported_clip_assembler.py -q\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"output\": \"... [100%]\\n3 passed in 0.03s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_16bcoFNEnt53WKaoa0zavOy7" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_TSqDRlwI9ng1Ig6MjhwnlZw2", "call_id": "call_TSqDRlwI9ng1Ig6MjhwnlZw2", "response_item_id": "fc_0d1a4d10654d56b4016a11941c33d0819184d6ebeac361675d", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Aktuelle ChatGPT Pro Video-/Sora-Leistungen prüfen\",\"id\":\"chatgpt-pro\",\"status\":\"completed\"},{\"content\":\"TDD für Imported AI Clip Assembler schreiben und RED verifizieren\",\"id\":\"tdd-import\",\"status\":\"completed\"},{\"content\":\"Imported AI Clip Assembler implementieren\",\"id\":\"build-import\",\"status\":\"in_progress\"}]}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"todos\": [{\"id\": \"chatgpt-pro\", \"content\": \"Aktuelle ChatGPT Pro Video-/Sora-Leistungen prüfen\", \"status\": \"completed\"}, {\"id\": \"tdd-import\", \"content\": \"TDD für Imported AI Clip Assembler schreiben und RED verifizieren\", \"status\": \"completed\"}, {\"id\": \"build-import\", \"content\": \"Imported AI Clip Assembler implementieren\", \"status\": \"in_progress\"}, {\"id\": \"verify\", \"content\": \"Tests/Artefakte/Git-Status verifizieren\", \"status\": \"pending\"}], \"summary\": {\"total\": 4, \"pending\": 1, \"in_progress\": 1, \"completed\": 2, \"cancelled\": 0}}", "tool_call_id": "call_TSqDRlwI9ng1Ig6MjhwnlZw2" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_Ul6e0COcbJrdRdQKoSFYuwIS", "call_id": "call_Ul6e0COcbJrdRdQKoSFYuwIS", "response_item_id": "fc_0d1a4d10654d56b4016a1194210788819197e73fe7ed3cf451", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python scripts/generate_imported_clip_assembly_plans.py --jobs data/free_production_jobs/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json --out data/imported_clip_assembly_plans/mechanism_pilots && pytest tests/ -q\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"output\": \"Generated 1 imported clip assembly plans in data/imported_clip_assembly_plans/mechanism_pilots\\ndata/imported_clip_assembly_plans/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\\n.......................................................... [100%]\\n58 passed in 3.39s\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_Ul6e0COcbJrdRdQKoSFYuwIS" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_WrexHwJfaY6qGUJx8OQmUb3X", "call_id": "call_WrexHwJfaY6qGUJx8OQmUb3X", "response_item_id": "fc_0d1a4d10654d56b4016a119452bc148191b679665ce595e0d4", "type": "function", "function": { "name": "read_file", "arguments": "{\"path\":\"/home/agent/jarvis_runtime/AutoShortsBot/data/imported_clip_assembly_plans/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\",\"limit\":220}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"content\": \" 1|{\\n 2| \\\"schema_version\\\": \\\"imported_clip_assembly.v1\\\",\\n 3| \\\"video\\\": {\\n 4| \\\"id\\\": \\\"hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann\\\",\\n 5| \\\"title\\\": \\\"Warum ein billiges Auto teuer sein kann\\\",\\n 6| \\\"pillar\\\": \\\"hidden_money_systems\\\",\\n 7| \\\"duration_ms\\\": 34000,\\n 8| \\\"aspect_ratio\\\": \\\"9:16\\\",\\n 9| \\\"resolution\\\": {\\n 10| \\\"width\\\": 1080,\\n 11| \\\"height\\\": 1920\\n 12| },\\n 13| \\\"fps\\\": 30\\n 14| },\\n 15| \\\"budget_policy\\\": {\\n 16| \\\"paid_video_credits_allowed\\\": false,\\n 17| \\\"paid_openai_video_generation_available\\\": false,\\n 18| \\\"manual_free_tier_import_only\\\": true\\n 19| },\\n 20| \\\"provider_notes\\\": [\\n 21| {\\n 22| \\\"provider\\\": \\\"chatgpt_pro_sora\\\",\\n 23| \\\"available_for_new_video_generation\\\": false,\\n 24| \\\"decision\\\": \\\"do_not_use_for_new_video_generation\\\",\\n 25| \\\"evidence\\\": \\\"OpenAI Help Center states: Sora web and app experiences were discontinued on April 26, 2026; Sora API will be discontinued on September 24, 2026; current ChatGPT credits can only be used with Codex and ChatGPT for Excel.\\\",\\n 26| \\\"source_urls\\\": [\\n 27| \\\"https://help.openai.com/en/articles/20001152-what-to-know-about-the-sora-discontinuation\\\",\\n 28| \\\"https://help.openai.com/en/articles/12642688-using-credits-for-flexible-usage-in-chatgpt-freegopluspro\\\"\\n 29| ]\\n 30| }\\n 31| ],\\n 32| \\\"imported_root\\\": \\\"data/imported_ai_clips\\\",\\n 33| \\\"final_assembly\\\": \\\"local_ffmpeg\\\",\\n 34| \\\"scenes\\\": [\\n 35| {\\n 36| \\\"scene_id\\\": \\\"scene_01\\\",\\n 37| \\\"asset_mode\\\": \\\"cinematic_ai_video\\\",\\n 38| \\\"duration_seconds\\\": 1.4,\\n 39| \\\"overlay_text\\\": \\\"Dieser Occasion-Käufer denkt, er spart 4'000 Franken.\\\",\\n 40| \\\"captions_added_locally\\\": true,\\n 41| \\\"source\\\": \\\"local_renderer_fallback\\\",\\n 42| \\\"missing_expected_clip\\\": \\\"data/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_01.mp4\\\",\\n 43| \\\"role\\\": \\\"placeholder_until_free_tier_clip_is_imported\\\"\\n 44| },\\n 45| {\\n 46| \\\"scene_id\\\": \\\"scene_02\\\",\\n 47| \\\"asset_mode\\\": \\\"cinematic_ai_video\\\",\\n 48| \\\"duration_seconds\\\": 3.6,\\n 49| \\\"overlay_text\\\": \\\"Das sieht harmlos aus, bis du den Mechanismus dahinter siehst.\\\",\\n 50| \\\"captions_added_locally\\\": true,\\n 51| \\\"source\\\": \\\"local_renderer_fallback\\\",\\n 52| \\\"missing_expected_clip\\\": \\\"data/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_02.mp4\\\",\\n 53| \\\"role\\\": \\\"placeholder_until_free_tier_clip_is_imported\\\"\\n 54| },\\n 55| {\\n 56| \\\"scene_id\\\": \\\"scene_03\\\",\\n 57| \\\"asset_mode\\\": \\\"mechanism_animation\\\",\\n 58| \\\"duration_seconds\\\": 13,\\n 59| \\\"overlay_text\\\": \\\"Röntgenblick durch Preis, Reparaturrisiko, Standtage, Händler-Marge…\\\",\\n 60| \\\"captions_added_locally\\\": true,\\n 61| \\\"source\\\": \\\"local_renderer\\\",\\n 62| \\\"role\\\": \\\"mechanism_or_caption_layer\\\",\\n 63| \\\"execution_mode\\\": \\\"mechanism_reveal_animation\\\"\\n 64| },\\n 65| {\\n 66| \\\"scene_id\\\": \\\"scene_04\\\",\\n 67| \\\"asset_mode\\\": \\\"mechanism_animation\\\",\\n 68| \\\"duration_seconds\\\": 10,\\n 69| \\\"overlay_text\\\": \\\"Der teuerste Fehler ist nicht der Kaufpreis, sondern der Zeitpunkt.\\\",\\n 70| \\\"captions_added_locally\\\": true,\\n 71| \\\"source\\\": \\\"local_renderer\\\",\\n 72| \\\"role\\\": \\\"mechanism_or_caption_layer\\\",\\n 73| \\\"execution_mode\\\": \\\"mechanism_reveal_animation\\\"\\n 74| },\\n 75| {\\n 76| \\\"scene_id\\\": \\\"scene_05\\\",\\n 77| \\\"asset_mode\\\": \\\"kinetic_text_overlay\\\",\\n 78| \\\"duration_seconds\\\": 6,\\n 79| \\\"overlay_text\\\": \\\"Morgen zeige ich das nächste versteckte System, bevor es dich Geld…\\\",\\n 80| \\\"captions_added_locally\\\": true,\\n 81| \\\"source\\\": \\\"local_renderer\\\",\\n 82| \\\"role\\\": \\\"mechanism_or_caption_layer\\\",\\n 83| \\\"execution_mode\\\": \\\"kinetic_typography\\\"\\n 84| }\\n 85| ],\\n 86| \\\"summary\\\": {\\n 87| \\\"imported_ai_clip_count\\\": 0,\\n 88| \\\"local_fallback_count\\\": 2,\\n 89| \\\"local_renderer_count\\\": 3\\n 90| }\\n 91|}\\n 92|\", \"total_lines\": 91, \"file_size\": 3500, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_WrexHwJfaY6qGUJx8OQmUb3X" }, { "role": "assistant", "content": "Need maybe maybe need implement actual hybrid render? But time, OK. Need final include answer. Need git commit. Check.", "tool_calls": [ { "id": "call_GFp1GRPJgP5yY1v3p0K0hGU0", "call_id": "call_GFp1GRPJgP5yY1v3p0K0hGU0", "response_item_id": "fc_0d1a4d10654d56b4016a11945a7b788191958cc098ff9c765c", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git diff --stat && git status --short\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } }, { "id": "call_azgHB4s5JnnkHgHdAuO1KPf7", "call_id": "call_azgHB4s5JnnkHgHdAuO1KPf7", "response_item_id": "fc_0d1a4d10654d56b4016a11945a7fac81918880b0c50be0e07d", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git diff -- . ':!data/local_motion_renders' | grep -iE 'api[_-]?key|token|secret|password|credential' || true\",\"timeout\":60,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls", "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Need maybe maybe need implement actual hybrid render? But time, OK. Need final include answer. Need git commit. Check." } ], "id": "msg_0d1a4d10654d56b4016a11945787288191b044807ac7dde3e0", "phase": "commentary" } ] }, { "role": "tool", "content": "{\"output\": \"?? autoshorts/imported_clip_assembler.py\\n?? autoshorts/review_package.py\\n?? data/imported_clip_assembly_plans/\\n?? data/telegram_reviews/\\n?? scripts/generate_imported_clip_assembly_plans.py\\n?? scripts/generate_telegram_review_packages.py\\n?? tests/test_imported_clip_assembler.py\\n?? tests/test_review_package.py\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_GFp1GRPJgP5yY1v3p0K0hGU0" }, { "role": "tool", "content": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_azgHB4s5JnnkHgHdAuO1KPf7" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_ebt2PSWnqMriGbqAMLmpAHz2", "call_id": "call_ebt2PSWnqMriGbqAMLmpAHz2", "response_item_id": "fc_0d1a4d10654d56b4016a11945ebcd88191a770f867d772cfbf", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git add autoshorts/imported_clip_assembler.py scripts/generate_imported_clip_assembly_plans.py tests/test_imported_clip_assembler.py data/imported_clip_assembly_plans/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json && git diff --cached --check && git commit -m \\\"feat: add imported clip assembly plans\\\" && git status --short\",\"timeout\":300,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"output\": \"[feat/initial-growth-engine 85ec56a] feat: add imported clip assembly plans\\n 4 files changed, 367 insertions(+)\\n create mode 100644 autoshorts/imported_clip_assembler.py\\n create mode 100644 data/imported_clip_assembly_plans/mechanism_pilots/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\\n create mode 100644 scripts/generate_imported_clip_assembly_plans.py\\n create mode 100644 tests/test_imported_clip_assembler.py\\n?? autoshorts/review_package.py\\n?? data/telegram_reviews/\\n?? scripts/generate_telegram_review_packages.py\\n?? tests/test_review_package.py\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_ebt2PSWnqMriGbqAMLmpAHz2" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_X4RpeHPK7la9nBqWXBxCeyEr", "call_id": "call_X4RpeHPK7la9nBqWXBxCeyEr", "response_item_id": "fc_0d1a4d10654d56b4016a11946540008191839e09d86acfb330", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"git push\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"output\": \"fatal: could not read Username for 'https://github.com': Kein passendes Gerät bzw. keine passende Adresse gefunden\", \"exit_code\": 128, \"error\": null}", "tool_call_id": "call_X4RpeHPK7la9nBqWXBxCeyEr" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_3p9sXNV8B78VsV5IeO3KIkOg", "call_id": "call_3p9sXNV8B78VsV5IeO3KIkOg", "response_item_id": "fc_0d1a4d10654d56b4016a119469b6fc8191a5f0d88d8a55bdea", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Imported AI Clip Assembler implementieren\",\"id\":\"build-import\",\"status\":\"completed\"},{\"content\":\"Tests/Artefakte/Git-Status verifizieren\",\"id\":\"verify\",\"status\":\"completed\"}]}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"todos\": [{\"id\": \"chatgpt-pro\", \"content\": \"Aktuelle ChatGPT Pro Video-/Sora-Leistungen prüfen\", \"status\": \"completed\"}, {\"id\": \"tdd-import\", \"content\": \"TDD für Imported AI Clip Assembler schreiben und RED verifizieren\", \"status\": \"completed\"}, {\"id\": \"build-import\", \"content\": \"Imported AI Clip Assembler implementieren\", \"status\": \"completed\"}, {\"id\": \"verify\", \"content\": \"Tests/Artefakte/Git-Status verifizieren\", \"status\": \"completed\"}], \"summary\": {\"total\": 4, \"pending\": 0, \"in_progress\": 0, \"completed\": 4, \"cancelled\": 0}}", "tool_call_id": "call_3p9sXNV8B78VsV5IeO3KIkOg" }, { "role": "assistant", "content": "Weitergebaut, Sir.\n\n## Kurzantwort zu ChatGPT Pro / Video\n\nNach aktuellem OpenAI-Stand: **Nein, dein ChatGPT Pro Abo ist derzeit kein brauchbarer Video-Generator für unseren Workflow.**\n\nIch habe die aktuellen OpenAI-Seiten geprüft:\n\n## ChatGPT Pro enthält laut Pricing\n\nAuf der ChatGPT-Pricing-Seite steht bei Pro u.a.:\n\n- 5x oder 20x mehr Nutzung\n- GPT-5.5 Pro\n- maximale Codex-Aufgaben\n- unbegrenztes GPT-5.3 und Datei-Uploads\n- unbegrenzte und schnellere Bilderstellung\n- maximale Deep Research und Agentenmodus\n- maximale Erinnerung / maximaler Kontext\n- neue Funktionen als experimentelle Vorschau\n\nAber: **keine aktive neue Videogeneration als ChatGPT-Pro-Feature**.\n\n## Sora-Status\n\nOpenAI Help Center sagt aktuell:\n\n```text\nThe Sora web and app experiences were discontinued on April 26, 2026.\nThe Sora API will be discontinued on September 24, 2026.\n```\n\nZusätzlich steht im Credits-Artikel:\n\n```text\nCredits currently can only be used with Codex and ChatGPT for Excel.\n```\n\nBedeutung für uns:\n\n```text\nChatGPT Pro → sehr gut für Planung, Scripting, Prompts, Code, Bilder\nChatGPT Pro → aktuell nicht als Video-Generator für neue Clips einplanen\n```\n\nAlso: **ChatGPT Pro bleibt unser Gehirn, nicht unsere Kamera.** \nEine sehr teure Kamera wäre es ohnehin gewesen. Charmant, aber unpraktisch.\n\n## Workflow-Entscheidung aktualisiert\n\nFür realistischere Clips bleibt der Free-Tier-Hybrid:\n\n```text\nChatGPT Pro / Hermes:\n Script, Shot Plan, Prompts, Captions, Renderlogik\n\nPixVerse / Pika / CapCut / ggf. Hailuo-Free:\n manuell erzeugte realistische 9:16 Clips\n\nLocal Renderer:\n Mechanismus-Layer, Captions, SFX, Timing\n\nFFmpeg:\n finales MP4\n```\n\nOpenAI/Sora wird im System ausdrücklich markiert als:\n\n```text\ndo_not_use_for_new_video_generation\n```\n\n## Weitergebaut: Imported AI Clip Assembler\n\nNeu implementiert:\n\n```text\nautoshorts/imported_clip_assembler.py\n```\n\nNeues CLI:\n\n```text\nscripts/generate_imported_clip_assembly_plans.py\n```\n\nNeue Tests:\n\n```text\ntests/test_imported_clip_assembler.py\n```\n\nNeues Artefakt:\n\n```text\ndata/imported_clip_assembly_plans/mechanism_pilots/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\n```\n\n## Was der neue Assembler macht\n\nEr prüft künftig diesen Import-Pfad:\n\n```text\ndata/imported_ai_clips/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/\n scene_01.mp4\n scene_02.mp4\n```\n\nWenn Clips vorhanden sind:\n\n```text\nscene_01 → imported_ai_clip\nscene_02 → imported_ai_clip\n```\n\nWenn nicht:\n\n```text\nscene_01 → local_renderer_fallback\nscene_02 → local_renderer_fallback\n```\n\nMechanismus-Szenen bleiben lokal:\n\n```text\nscene_03 → local_renderer\nscene_04 → local_renderer\nscene_05 → local_renderer\n```\n\nAktueller Assembly-Plan sagt erwartungsgemäß:\n\n```text\nimported_ai_clip_count: 0\nlocal_fallback_count: 2\nlocal_renderer_count: 3\n```\n\nWeil noch keine PixVerse/Pika-Clips importiert wurden.\n\n## OpenAI/Sora-Hinweis im Artefakt\n\nDer Assembly-Plan enthält jetzt explizit:\n\n```json\n{\n \"provider\": \"chatgpt_pro_sora\",\n \"available_for_new_video_generation\": false,\n \"decision\": \"do_not_use_for_new_video_generation\"\n}\n```\n\nMit Quellenhinweis auf:\n\n```text\nSora web/app discontinued: 2026-04-26\nSora API discontinued: 2026-09-24\nCredits currently only for Codex and ChatGPT for Excel\n```\n\n## Tests\n\nFull suite:\n\n```text\n58 passed in 3.39s\n```\n\n## Git\n\nNeuer lokaler Commit:\n\n```text\n85ec56a feat: add imported clip assembly plans\n```\n\nAktueller lokaler Commit-Verlauf:\n\n```text\n85ec56a feat: add imported clip assembly plans\n9f41a9f feat: add free ai video handoff specs\nff5df62 feat: add free local motion renderer\n```\n\nPush weiterhin blockiert wegen fehlender GitHub-Credentials:\n\n```text\nfatal: could not read Username for 'https://github.com'\n```\n\nDie versehentlichen Telegram-Review-Dateien bleiben untracked und unberührt.\n\n## Nächster praktischer Produktionsschritt\n\nJetzt brauchen wir konkret zwei manuell generierte Clips:\n\n```text\nscene_01.mp4\nscene_02.mp4\n```\n\nAm besten zuerst in PixVerse, sonst Pika.\n\nAblage danach:\n\n```text\ndata/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_01.mp4\ndata/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_02.mp4\n```\n\nDann kann ich den nächsten Baustein bauen:\n\n```text\nHybrid Final Renderer:\nimported AI clips\n+ local mechanism scenes\n+ local kinetic captions\n+ FFmpeg assembly\n→ finales MP4\n```", "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Weitergebaut, Sir.\n\n## Kurzantwort zu ChatGPT Pro / Video\n\nNach aktuellem OpenAI-Stand: **Nein, dein ChatGPT Pro Abo ist derzeit kein brauchbarer Video-Generator für unseren Workflow.**\n\nIch habe die aktuellen OpenAI-Seiten geprüft:\n\n## ChatGPT Pro enthält laut Pricing\n\nAuf der ChatGPT-Pricing-Seite steht bei Pro u.a.:\n\n- 5x oder 20x mehr Nutzung\n- GPT-5.5 Pro\n- maximale Codex-Aufgaben\n- unbegrenztes GPT-5.3 und Datei-Uploads\n- unbegrenzte und schnellere Bilderstellung\n- maximale Deep Research und Agentenmodus\n- maximale Erinnerung / maximaler Kontext\n- neue Funktionen als experimentelle Vorschau\n\nAber: **keine aktive neue Videogeneration als ChatGPT-Pro-Feature**.\n\n## Sora-Status\n\nOpenAI Help Center sagt aktuell:\n\n```text\nThe Sora web and app experiences were discontinued on April 26, 2026.\nThe Sora API will be discontinued on September 24, 2026.\n```\n\nZusätzlich steht im Credits-Artikel:\n\n```text\nCredits currently can only be used with Codex and ChatGPT for Excel.\n```\n\nBedeutung für uns:\n\n```text\nChatGPT Pro → sehr gut für Planung, Scripting, Prompts, Code, Bilder\nChatGPT Pro → aktuell nicht als Video-Generator für neue Clips einplanen\n```\n\nAlso: **ChatGPT Pro bleibt unser Gehirn, nicht unsere Kamera.** \nEine sehr teure Kamera wäre es ohnehin gewesen. Charmant, aber unpraktisch.\n\n## Workflow-Entscheidung aktualisiert\n\nFür realistischere Clips bleibt der Free-Tier-Hybrid:\n\n```text\nChatGPT Pro / Hermes:\n Script, Shot Plan, Prompts, Captions, Renderlogik\n\nPixVerse / Pika / CapCut / ggf. Hailuo-Free:\n manuell erzeugte realistische 9:16 Clips\n\nLocal Renderer:\n Mechanismus-Layer, Captions, SFX, Timing\n\nFFmpeg:\n finales MP4\n```\n\nOpenAI/Sora wird im System ausdrücklich markiert als:\n\n```text\ndo_not_use_for_new_video_generation\n```\n\n## Weitergebaut: Imported AI Clip Assembler\n\nNeu implementiert:\n\n```text\nautoshorts/imported_clip_assembler.py\n```\n\nNeues CLI:\n\n```text\nscripts/generate_imported_clip_assembly_plans.py\n```\n\nNeue Tests:\n\n```text\ntests/test_imported_clip_assembler.py\n```\n\nNeues Artefakt:\n\n```text\ndata/imported_clip_assembly_plans/mechanism_pilots/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann.json\n```\n\n## Was der neue Assembler macht\n\nEr prüft künftig diesen Import-Pfad:\n\n```text\ndata/imported_ai_clips/\n hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/\n scene_01.mp4\n scene_02.mp4\n```\n\nWenn Clips vorhanden sind:\n\n```text\nscene_01 → imported_ai_clip\nscene_02 → imported_ai_clip\n```\n\nWenn nicht:\n\n```text\nscene_01 → local_renderer_fallback\nscene_02 → local_renderer_fallback\n```\n\nMechanismus-Szenen bleiben lokal:\n\n```text\nscene_03 → local_renderer\nscene_04 → local_renderer\nscene_05 → local_renderer\n```\n\nAktueller Assembly-Plan sagt erwartungsgemäß:\n\n```text\nimported_ai_clip_count: 0\nlocal_fallback_count: 2\nlocal_renderer_count: 3\n```\n\nWeil noch keine PixVerse/Pika-Clips importiert wurden.\n\n## OpenAI/Sora-Hinweis im Artefakt\n\nDer Assembly-Plan enthält jetzt explizit:\n\n```json\n{\n \"provider\": \"chatgpt_pro_sora\",\n \"available_for_new_video_generation\": false,\n \"decision\": \"do_not_use_for_new_video_generation\"\n}\n```\n\nMit Quellenhinweis auf:\n\n```text\nSora web/app discontinued: 2026-04-26\nSora API discontinued: 2026-09-24\nCredits currently only for Codex and ChatGPT for Excel\n```\n\n## Tests\n\nFull suite:\n\n```text\n58 passed in 3.39s\n```\n\n## Git\n\nNeuer lokaler Commit:\n\n```text\n85ec56a feat: add imported clip assembly plans\n```\n\nAktueller lokaler Commit-Verlauf:\n\n```text\n85ec56a feat: add imported clip assembly plans\n9f41a9f feat: add free ai video handoff specs\nff5df62 feat: add free local motion renderer\n```\n\nPush weiterhin blockiert wegen fehlender GitHub-Credentials:\n\n```text\nfatal: could not read Username for 'https://github.com'\n```\n\nDie versehentlichen Telegram-Review-Dateien bleiben untracked und unberührt.\n\n## Nächster praktischer Produktionsschritt\n\nJetzt brauchen wir konkret zwei manuell generierte Clips:\n\n```text\nscene_01.mp4\nscene_02.mp4\n```\n\nAm besten zuerst in PixVerse, sonst Pika.\n\nAblage danach:\n\n```text\ndata/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_01.mp4\ndata/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_02.mp4\n```\n\nDann kann ich den nächsten Baustein bauen:\n\n```text\nHybrid Final Renderer:\nimported AI clips\n+ local mechanism scenes\n+ local kinetic captions\n+ FFmpeg assembly\n→ finales MP4\n```" } ], "id": "msg_0d1a4d10654d56b4016a11946d2c388191a2137d7b7c4b0c92", "phase": "final_answer" } ], "finish_reason": "stop" }, { "role": "user", "content": "[M G] ok, wie gehen wir also weiter vor? generierst du die Videos?" }, { "role": "assistant", "content": "", "reasoning": "**Evaluating steps for prompts**\n\nI think we can produce precise prompts and steps from the existing handoff. I should use the tool to read the handoff file and pull out those exact prompts. Is the social media skill relevant and mandatory before I respond? I believe we've already loaded it in this session. Hmm, maybe I need to check the skills before replying. It's important to load the relevant social-media-shorts-growth-engine too!", "finish_reason": "tool_calls", "reasoning_content": "**Evaluating steps for prompts**\n\nI think we can produce precise prompts and steps from the existing handoff. I should use the tool to read the handoff file and pull out those exact prompts. Is the social media skill relevant and mandatory before I respond? I believe we've already loaded it in this session. Hmm, maybe I need to check the skills before replying. It's important to load the relevant social-media-shorts-growth-engine too!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZZVoDAoBcOWNJD688UUKUxhZOFDKhtdwFvfuZy_aaBd8GmhOxR8rtztRnWSFFRwegpGRXvtXNUxrlQgUl8mrxbSQxSOHRPY4GMHXm3jRFufjkVgLX-g1paJgDppo24ODm6jPSY-YLVJ_CJJriRzyvG_st9e6SdwxQwKLoDk2ag5s6ATtcNgov-milYPV3DNDXON6ZPhbTh_uQxhndYVDXWEcWwPacfCq_ccwBaxe5LJbTkbTkmvrzgee0BPaymmAOOa_Yul_BkQKBOxhluRw8hZalNyINNClA4whNKkKTZAT1LeleqYWplLZqq6wy2V-z6Ti7oEs7P2WpK7fo3tRtOEmb6BPxp9ZKWHszAdOKMrx-cjBBNdQoQBrIegnTZJSXTjJMJLAzPQmCc0r5ooPMs_dP8bgpchn-zv0qCP2ssq3B7U__z60M0k8VSrCj0DeTRn_Qm6wtracmyATuFOnic2xc90DByadE3YL6tL0BZgZc1JBKJ_XbFxOh161HiT70odLR6V3FZuNOQPAFAmT1KZ_JBqm0ERv0uFIg6447Uf1JmpR2FBxfAX-6dfuFNsjbks-x9N1BUDR1QireRQJVjUBaMcjWBHyzNg4vx0LBszUme61A7sWoQBntyU2xKjQ5_eYFZbjXv43MhAloQTfpq8QyTZIrHPQmexRcFNHlGRWtwuD_lAux80fIn_N4qRH4eG8zDqZTMc4uHhuNkiMy89NxF8IlC6UCYq9cR3dq33AURRRNFKuQRZ53bwQDdGuS3fkC8gbZEkzLjiQFLdzm7NlJwOYBN-A_5--dqBwnU6uWXmqCukNGRuBalcPPXHwXfO_0Bjdrp7iC6GRiR7LVAY6kPR9BhEQhSY7bXHHGKANvPwgjQIiL3HbULJ2tN6BVhw1JidBX55V0-unUYXEjazs5laFOXtQsNl6rUZaNRx5UnTijZrLEELVYsZhkID-QLhSTcHreB-BEk1vQ8BodPtfKglp6cDBLWNM3XLgWkoG5bF0C_nUvbxrCnBFpQHqyxCogc1pJ0U_tAQLJ7-PGf0O67oyzyIDAT9W0o4ppv6mYaVuE2qgONI0Ee5PiQRMC-lCIr5k0nrgQ2BI_7uFl_z2lDuOsKanjoQOTG9Y7Yaz5eovGUpUs4VsMCa71Lp2k8p5PgQYhifLacaqfuZYUdy12xNK6XyGzEzzDl9ubkfVJNwWehK2NBuz4IV5KHp2PFxeqFQ3HydIj_X8ly_In2liYuSfD4GuM-s50pbhIgbP1aW9130LWB4TOCLlq3BACQYR4Vfpr15pPb_tn8Oz5QkfNRP_Oj08Uz9H52ytZBROcPBvY5KHUIpl7pvEXbp4Uo5lSOJ1rY3gvSILSLyYw3LcvzUk0nWFsQEPyH2XNlkMllPuMwRmdo03npoGE0s1X1MWVKyzZpm5cwfQ4c6CAGDFaen_UsLPaVcJ4C2tXRCiQJGmI1DyrjhTmGvZlHxTWt3yFBlu4tpxeZgusd3Z6XcE6980cApzYdbs8VNacc0PdB7RB_e1WnOYlbV1jP1sRYcP_069tb09V_Ng3jklPhFnfrKOLgRYYpfvPIUVCiJAtZsb5pVZBK-59fWCVQixyxZRz6omrt0PFLCZWpiLuswQKkFfj--prEQ9k7RW8qj6NyKcXeS4E0Y9YY9LyMDQ1eSgc1FUEhui8qeAgNAtSBz5DaudFwjFYgZzCmmNVTuKgUO8y5bIBQVMXYLnHbRIuxEtJV3BSX_plRG1c14J3fTPYc6xUUN1-XM5OBXpYYjh-xDhfC3ZvH-4rG7R87HqJ_-xysAOyXdwbZGpzp0Ijsnlcddaj_rCzgfiOUvyVJ05oaDvdnAuwv6HAwTgq3dCVJclvxP4svo-ZFT3AUIZmq4bSXL1zwjrYEMbWV2XxI1hoEk81py2LeakLHCBHH6hXvG1kpPiIuryhslrA3EofsFwT8CFuz0M6_Unzw3jFlYF9Kk9yaK7KvCQfAwGZcVcziAQnfLTNLQYmmVNkWUEF_gvcA4EJYoix3k7E_bs-0lT974H-y8Ao58jy-2pnstXb26JrwLLWgChARdfLphEElfo5i61FuMczCSUcUs76pepPf92PDmsOTzGBzApR-eJKZVDxEGPwWOX2G9tWKuDJu1B0HqwyrRKMNkWzfBFtrFjOtxKTdcO0-1GebB0NY5lYEwHFg4klv1Oft7bsVgml2xY42oLhLB7g1cv9eqNe3RsesitS0aITqXZcIs4a3ScKqtN9-TPEYa9F3FZ_1vT5xV5ChIjdqgu4U_o3Rc22szTc7aHcUSubW3YtiFfS6oVj7rAc4UDj5pANk7Ps5dYjLfn3S6S68rXF-RE_Arz8im1H2hWhxTCn8eXV365mjbPHLUxBKpzd5kipeGNUWwkXYoUaRkqIotaQsyPaIUAVyPrc8jzL3X-rPjHuSuZe-du06IN4LkJf_Yf2xrWZ3lBj486fiY1LdCDlWcmfwGF1L-vRZxnCHbBq1MpAGN1hgQhGBdqT8T8K78MhVrygrU6ZoCfwAe_O_iuGRcX6O96oXwg76AsJU3Jinm0kinbHKttuD-w5hs42Ij47huGBVeW5GRmPaYkZ3t-38qxh74cf4Cuwk=", "id": "rs_0d1a4d10654d56b4016a11964f84a88191a4a72a19ce90eabb", "summary": [ { "type": "summary_text", "text": "**Evaluating steps for prompts**\n\nI think we can produce precise prompts and steps from the existing handoff. I should use the tool to read the handoff file and pull out those exact prompts. Is the social media skill relevant and mandatory before I respond? I believe we've already loaded it in this session. Hmm, maybe I need to check the skills before replying. It's important to load the relevant social-media-shorts-growth-engine too!" } ] } ], "tool_calls": [ { "id": "call_hd4J5aR0VMWAHRlnGpV7GmqO", "call_id": "call_hd4J5aR0VMWAHRlnGpV7GmqO", "response_item_id": "fc_0d1a4d10654d56b4016a119655dfa88191a87c86a574b663dc", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"social-media-shorts-growth-engine\"}" } } ] }, { "role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"social-media-shorts-growth-engine\", \"description\": \"Design and operate a growth-oriented short-form video engine for YouTube Shorts, TikTok, Instagram Reels, and adjacent channels, with human approval before posting.\", \"tags\": [\"shorts\", \"tiktok\", \"youtube-shorts\", \"reels\", \"content-strategy\", \"growth\", \"monetization\", \"approval-workflow\"], \"related_skills\": [], \"content\": \"---\\nname: social-media-shorts-growth-engine\\ndescription: Design and operate a growth-oriented short-form video engine for YouTube Shorts, TikTok, Instagram Reels, and adjacent channels, with human approval before posting.\\nversion: 1.0.0\\ntags: [shorts, tiktok, youtube-shorts, reels, content-strategy, growth, monetization, approval-workflow]\\n---\\n\\n# Social-Media Shorts Growth Engine\\n\\nUse this skill when the user wants to build, improve, or operate an automated/semi-automated system for short-form social media content: YouTube Shorts, TikTok, Instagram Reels, Facebook Reels, Pinterest, LinkedIn video, or similar.\\n\\n## Core principle\\n\\nDo **not** treat the task as “make videos.” Treat it as a **growth engine**:\\n\\n1. Generate many sharply positioned ideas.\\n2. Score hooks and scripts before rendering.\\n3. Produce previews.\\n4. Send the user a review package.\\n5. Post only after explicit approval.\\n6. Capture analytics.\\n7. Feed performance back into the next batch.\\n\\nA technically correct content generator that produces generic content is failure with extra rendering time. Charming, but still failure.\\n\\n## Recommended workflow\\n\\n### 1. Define content pillars\\n\\nStart with 2–4 pillars, not a vague infinite topic pool. For each pillar define:\\n\\n- audience\\n- positioning\\n- tone\\n- hook patterns\\n- visual rules\\n- no-go topics\\n- platform fit\\n- monetization angle\\n\\nExample pillar structure:\\n\\n```json\\n{\\n \\\"pillar\\\": \\\"ai_life_systems\\\",\\n \\\"positioning\\\": \\\"AI as a servant for ordinary life systems, never as values or authority.\\\",\\n \\\"tone\\\": [\\\"clear\\\", \\\"useful\\\", \\\"values-first\\\", \\\"non-hype\\\"],\\n \\\"hook_patterns\\\": [\\\"AI is a bad god, but a good servant.\\\"],\\n \\\"visual_rules\\\": [\\\"screen-recording friendly\\\", \\\"human remains in control\\\"],\\n \\\"no_go\\\": [\\\"fake earnings\\\", \\\"overpromising automation\\\"]\\n}\\n```\\n\\n### 2. Build a testbatch before building a full automation platform\\n\\nFor a new channel or unvalidated strategy, create a small batch first:\\n\\n- 3 ideas per pillar\\n- 6 short growth candidates, usually 20–45 seconds\\n- 1–3 monetization-length candidates, usually 60+ seconds where the platform rewards length\\n- one clear hypothesis per idea\\n\\nEach idea should include:\\n\\n- id\\n- pillar\\n- title\\n- platform target\\n- duration\\n- hook\\n- script outline\\n- visual concept\\n- caption\\n- CTA\\n- quality score\\n- risk/policy notes\\n\\n### 3. Add a script quality gate\\n\\nBefore rendering, score each draft for:\\n\\n- hook strength in the first 1–2 seconds\\n- novelty / non-generic angle\\n- emotional pull\\n- clarity\\n- retention risk\\n- comment/share potential\\n- AI-slop risk\\n- policy/copyright risk\\n\\nRender only drafts above the threshold, e.g. 8/10.\\n\\n### 4. Use a human approval loop\\n\\nDefault to semi-automatic operation first. Send a Telegram review package with:\\n\\n- preview video or script draft\\n- pillar and format\\n- title\\n- duration\\n- hook\\n- caption\\n- hashtags\\n- quality score\\n- policy notes\\n- suggested platforms\\n\\nRecommended approval commands:\\n\\n- `Freigabe alle`\\n- `Freigabe YouTube`\\n- `Freigabe TikTok`\\n- `Freigabe Instagram`\\n- `Ablehnen`\\n- `Ändern: `\\n\\nIf approval is ambiguous, do not post. Ask once in the project topic.\\n\\n### 5. Keep platform strategy separate from rendering\\n\\nRendering code should not hardcode content strategy. Keep separate config files for:\\n\\n- niches/pillars\\n- platforms\\n- script formats\\n- visual styles\\n- approval workflow\\n- analytics schema\\n\\nThis lets the same renderer support different formats and prevents prompt spaghetti. Prompt spaghetti is still spaghetti even if it is wearing a YAML hat.\\n\\n## Platform notes\\n\\n### YouTube Shorts\\n\\n- Shorts can be vertical or square and up to 3 minutes long.\\n- YouTube Partner Program Shorts route typically requires 1,000 subscribers and 10M valid public Shorts views in the last 90 days.\\n- Alternative longform YPP route: 1,000 subscribers and 4,000 valid public watch hours in the last 12 months.\\n- Shorts views in the Shorts feed do not count toward the 4,000 longform watch hours.\\n- Practical early growth tests often work best at 20–45 seconds; longer Shorts need a strong story or payoff.\\n\\n### TikTok\\n\\n- Creator Rewards availability depends on country/account eligibility.\\n- TikTok Creator Rewards generally requires a non-business account in good standing, 10,000 followers, and 100,000 authentic views in the last 30 days before joining, subject to country availability and current terms.\\n- Reward-eligible videos generally need to be at least 1 minute long and meet quality/originality criteria.\\n- This creates a strategy split:\\n - 20–45s for growth and format discovery.\\n - 60–75s for monetization candidates once a format works.\\n\\n### Instagram / Facebook Reels\\n\\nUseful for republishing 9:16 assets and testing share/save behavior. Treat direct payout as volatile; prefer indirect monetization through audience, affiliate, newsletter, or products.\\n\\n### LinkedIn / X / Pinterest\\n\\nUse selectively:\\n\\n- LinkedIn: AI/productivity/workflows.\\n- X: AI demos, build-in-public, technical positioning.\\n- Pinterest: evergreen checklists, routines, faith/life prompts.\\n\\n## Repository scaffold\\n\\nA clean shorts-engine repo can start as:\\n\\n```text\\nAutoShortsBot/\\n autoshorts/\\n config/\\n ideas/\\n scripting/\\n rendering/\\n review/\\n publishing/\\n analytics/\\n configs/\\n niches/\\n platforms/\\n data/\\n drafts/\\n performance/\\n scripts/\\n tests/\\n README.md\\n .gitignore\\n pyproject.toml\\n```\\n\\nNever commit:\\n\\n- `.env`\\n- OAuth tokens\\n- API keys\\n- generated credentials\\n- rendered videos or large media outputs unless explicitly intended\\n- raw analytics exports with sensitive account data\\n\\n## Implementation quality\\n\\nWhen coding the engine, prefer TDD for deterministic parts:\\n\\n- testbatch validation\\n- duration classification\\n- review formatting\\n- analytics import\\n- approval command parsing\\n- platform metadata generation\\n\\nRendering and external API calls can be integration-tested separately.\\n\\nFor this AutoShortsBot/Retention-Studio workflow, prefer a free-first renderer path before any paid video provider: `free_production_jobs → local_motion_renderer → FFmpeg MP4`. The local renderer should use Pillow/FFmpeg procedural motion, mechanism layers, kinetic captions, and generated metadata; preserve exact scene durations from render manifests, exclude text-only LLM refinement jobs from rendering, and keep generated local renders out of git (`data/local_motion_renders/`). NVIDIA/build.nvidia.com LLMs are optional text-refinement helpers only, not video generation.\\n\\nIf the user wants more realistic footage without spending money, use a hybrid free-tier handoff rather than pretending local procedural graphics are realistic: `free_production_jobs → free_ai_video_handoff → manual browser generation in free-tier tools (PixVerse/Pika/CapCut/Hailuo only with existing free credits) → import clips under data/imported_ai_clips/ → local captions/mechanism layers/FFmpeg assembly`. Guardrails: no paid top-ups, no subscriptions, avoid Pro templates, no baked captions/logos/watermarks where possible, and keep imported clips out of git.\\n\\n## Pitfalls\\n\\n- **Generic advice content:** “4 tips to be healthier/productive” is usually too weak unless the hook, identity, or story is sharp.\\n- **AI-image slop:** avoid generated images containing fake UI text, gibberish signs, distorted hands/faces, or abstract generic graphs. These damage trust fast.\\n- **Too much automation too soon:** validate scripts and formats before building posting APIs.\\n- **No analytics loop:** producing content without tracking retention, likes, shares, comments, and follows is blind output.\\n- **Mixed language drift:** decide language per channel or per pillar before rendering. Mixed English/German drafts are fine for ideation, not final voiceover unless intentional.\\n\\n## References\\n\\n- `references/autoshortsbot-case-study.md` — case-study details from the AutoShortsBot setup: first testbatch shape, repo scaffold, and approval loop.\\n\", \"path\": \"social-media/social-media-shorts-growth-engine/SKILL.md\", \"skill_dir\": \"/home/agent/.hermes/skills/social-media/social-media-shorts-growth-engine\", \"linked_files\": {\"references\": [\"references/autoshortsbot-case-study.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\"}", "tool_call_id": "call_hd4J5aR0VMWAHRlnGpV7GmqO" }, { "role": "assistant", "content": "Ja — aber mit einer wichtigen Trennung, Sir:\n\n## Was ich direkt generieren kann\n\nIch kann hier vollständig selbst erzeugen:\n\n- Shot Plans\n- Prompts\n- Captions\n- Voiceover-Text\n- lokale Animatics / Placeholder-Videos\n- Mechanism-Animationen\n- Kinetic Captions\n- finale FFmpeg-Montage\n- Review-Pakete\n- Tests / Code / Render-Pipeline\n\nAlso alles, was **lokal** läuft.\n\n## Was ich nicht sauber allein generieren kann\n\nDie **realistischen KI-Videoclips** aus PixVerse/Pika/CapCut kann ich nicht zuverlässig komplett autonom erzeugen, weil:\n\n- Login im Browser nötig ist\n- evtl. CAPTCHA / E-Mail / Account-Session kommt\n- Free Credits accountgebunden sind\n- ich keine Käufe/Top-ups machen darf\n- externe Webseiten häufig Export/Download manuell absichern\n\nIch kann es theoretisch im Browser versuchen, aber praktisch ist der stabile Workflow:\n\n```text\nIch generiere Prompt + genaue Anleitung\ndu / wir erzeugen Clips in PixVerse oder Pika\ndu lädst sie herunter\nich importiere sie in den Renderer\nich baue daraus das finale Video\n```\n\n## Konkreter Ablauf ab jetzt\n\n## Schritt 1 — Ich liefere dir 2 Clip-Aufträge\n\nFür den Pilot brauchen wir zuerst nur:\n\n```text\nscene_01.mp4\nscene_02.mp4\n```\n\nDiese zwei Clips sind realistische B-Roll / Hook-Szenen.\n\n## Schritt 2 — Du erzeugst sie gratis\n\nEmpfohlen:\n\n```text\n1. PixVerse\n2. Pika\n3. CapCut\n4. Hailuo nur falls Free Credits vorhanden\n```\n\nKeine paid Credits. Keine Subscription. Keine Top-ups. Natürlich. Wir sind nicht hier, um Kapitalismus zu füttern, bevor das Video überhaupt Views hat.\n\n## Schritt 3 — Clips ablegen\n\nNach Download müssen die Dateien hier landen:\n\n```text\ndata/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_01.mp4\ndata/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_02.mp4\n```\n\n## Schritt 4 — Ich rendere final hybrid\n\nDann mache ich:\n\n```text\nimportierte realistische Clips\n+ lokale Mechanism-Layer\n+ Captions\n+ SFX\n+ Timing\n+ FFmpeg Assembly\n→ finales MP4\n```\n\n## Soll ich die Videos generieren?\n\nPräzise Antwort:\n\n```text\nDie lokalen Teile: ja, vollständig.\nDie Free-Tier KI-Clips: ich bereite sie vor; generieren/Download braucht wahrscheinlich dich im Browser/Login.\n```\n\nFalls du willst, kann ich beim nächsten Schritt **sofort** ein Telegram-taugliches Clip-Generation-Paket liefern:\n\n- PixVerse-Link\n- Pika-Link\n- Prompt für scene_01\n- Prompt für scene_02\n- Negative Prompt\n- Export-Einstellungen\n- Dateinamen\n- Qualitätscheckliste\n\nDann erzeugst du die zwei Clips, lädst sie herunter, und ich baue daraus das finale Video.", "reasoning": "**Considering browser options**\n\nI need to finalize my response. I think I could mention that I could attempt browser generation if the user logs in or provides exported clips, but I’m not sure how reliable that would be. It might be helpful to include the exact steps they need to follow. I'll consider whether I can accomplish this with no additional tools required. It feels important to be clear and helpful for the user!", "reasoning_content": "**Considering browser options**\n\nI need to finalize my response. I think I could mention that I could attempt browser generation if the user logs in or provides exported clips, but I’m not sure how reliable that would be. It might be helpful to include the exact steps they need to follow. I'll consider whether I can accomplish this with no additional tools required. It feels important to be clear and helpful for the user!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqEZZcm_TDgzXmViiVHLs28JhcioK_TbqSDjPRewly1v7iBg13gDR_gs8qIo0mE2wLQ_ZweZ8Xt76ryxjggl0neGVNHmpsuJOQQhlFtQsJI8HTQwZ4Q4I2dkiwb8wjaW5QR2fLTMpUwZxdwpPBF5ZlGHUY9RdhauH0Adg7RI-Aorg_AgCQAKJmkyIOaO9akN16l0Q0ukhrbzzePctkVl1YfjmDIqN6m31PRCUHo0x2xMJPfDmkYAHGgltczuOCIG899uwTyJUbJBptSMBABrWPHJNBNOaty_UKC6ycvHlJpz5iHNm_fOzZKHVXKG0UL5Jc1IaVvHj3qc54um9bJo9YhxTCOcVUdD6LaDpzVyVVLmSwrYSFIhSx6qzOA_s2Omj9IbeMHchSH7EBbeRnw1EQwdpxTHtBRW5DcFOwmqaH2HxzXFYTx_UmSWzYYT-JEFlmiaTqX1fwHpQPtSmPtbBDLuJdfRp6sGwvTzOKf8YiDdMty5sSFsrUTfv9IPFYqBPOAlnG_-zJITRrrL4ltDq3W8GJIeNb5B6NTtjHKGix-BaIlFDZGv2UnIMeM9WIJuSm0ujUjGm8lovojyZCbqhT6fjsOat657OS5j8aWGTT51P0wIzt9vBWbZ5SohAxcOHcUufwxAR51wy7QMPp0NaVmM42KXZiRQAcZXiiBut2W9RkPxUeL8Qm9II0l9I7eWZY2ssRtVe_G2icxec1MzTNE5gK3AwRFLVdT11q4nrAmo1NOpk4M1FUJ3K2_fqrcSZl8W4LaJ5wZr-U2ZtlbaAb85Vlnduc2062HYYvQwwGV8z1nthoVqltAXl-H3-4C7u-Blh83bTW4vHJJJbs9WIL1kI0QR1anW1maoYZX4d5fyzLr0PHkiD-hDXShjE93ZzwDlDxpE2jxL8GwCIhfjSekB9Ffbr8i879BYXaUuvkWXpxxrV9QrH3akEok68_QlJDYS84eeVkhFh6s37nHKsiJKhbyvHiPGLVIO85yUFPIEj9ka9yqpAq9VHlcvjYSac0itye7XAc3HJ9Zcey7AmKyvElU0epIdglSkKwalkup5VDf0YsnM0lJxbmDFnXtSfcSONMKLnNOckRzo1p7zlpyD665CwXfCPE7Y51kemv6uIe8FTQjQV817vrJjYaDcJ-INTI", "id": "rs_0d1a4d10654d56b4016a119659d42c81919c651d0ca6c59cae", "summary": [ { "type": "summary_text", "text": "**Considering browser options**\n\nI need to finalize my response. I think I could mention that I could attempt browser generation if the user logs in or provides exported clips, but I’m not sure how reliable that would be. It might be helpful to include the exact steps they need to follow. I'll consider whether I can accomplish this with no additional tools required. It feels important to be clear and helpful for the user!" } ] } ], "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "Ja — aber mit einer wichtigen Trennung, Sir:\n\n## Was ich direkt generieren kann\n\nIch kann hier vollständig selbst erzeugen:\n\n- Shot Plans\n- Prompts\n- Captions\n- Voiceover-Text\n- lokale Animatics / Placeholder-Videos\n- Mechanism-Animationen\n- Kinetic Captions\n- finale FFmpeg-Montage\n- Review-Pakete\n- Tests / Code / Render-Pipeline\n\nAlso alles, was **lokal** läuft.\n\n## Was ich nicht sauber allein generieren kann\n\nDie **realistischen KI-Videoclips** aus PixVerse/Pika/CapCut kann ich nicht zuverlässig komplett autonom erzeugen, weil:\n\n- Login im Browser nötig ist\n- evtl. CAPTCHA / E-Mail / Account-Session kommt\n- Free Credits accountgebunden sind\n- ich keine Käufe/Top-ups machen darf\n- externe Webseiten häufig Export/Download manuell absichern\n\nIch kann es theoretisch im Browser versuchen, aber praktisch ist der stabile Workflow:\n\n```text\nIch generiere Prompt + genaue Anleitung\ndu / wir erzeugen Clips in PixVerse oder Pika\ndu lädst sie herunter\nich importiere sie in den Renderer\nich baue daraus das finale Video\n```\n\n## Konkreter Ablauf ab jetzt\n\n## Schritt 1 — Ich liefere dir 2 Clip-Aufträge\n\nFür den Pilot brauchen wir zuerst nur:\n\n```text\nscene_01.mp4\nscene_02.mp4\n```\n\nDiese zwei Clips sind realistische B-Roll / Hook-Szenen.\n\n## Schritt 2 — Du erzeugst sie gratis\n\nEmpfohlen:\n\n```text\n1. PixVerse\n2. Pika\n3. CapCut\n4. Hailuo nur falls Free Credits vorhanden\n```\n\nKeine paid Credits. Keine Subscription. Keine Top-ups. Natürlich. Wir sind nicht hier, um Kapitalismus zu füttern, bevor das Video überhaupt Views hat.\n\n## Schritt 3 — Clips ablegen\n\nNach Download müssen die Dateien hier landen:\n\n```text\ndata/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_01.mp4\ndata/imported_ai_clips/hidden-money-systems-warum-ein-billiges-auto-teuer-sein-kann/scene_02.mp4\n```\n\n## Schritt 4 — Ich rendere final hybrid\n\nDann mache ich:\n\n```text\nimportierte realistische Clips\n+ lokale Mechanism-Layer\n+ Captions\n+ SFX\n+ Timing\n+ FFmpeg Assembly\n→ finales MP4\n```\n\n## Soll ich die Videos generieren?\n\nPräzise Antwort:\n\n```text\nDie lokalen Teile: ja, vollständig.\nDie Free-Tier KI-Clips: ich bereite sie vor; generieren/Download braucht wahrscheinlich dich im Browser/Login.\n```\n\nFalls du willst, kann ich beim nächsten Schritt **sofort** ein Telegram-taugliches Clip-Generation-Paket liefern:\n\n- PixVerse-Link\n- Pika-Link\n- Prompt für scene_01\n- Prompt für scene_02\n- Negative Prompt\n- Export-Einstellungen\n- Dateinamen\n- Qualitätscheckliste\n\nDann erzeugst du die zwei Clips, lädst sie herunter, und ich baue daraus das finale Video." } ], "id": "msg_0d1a4d10654d56b4016a11965cebb08191bdf84c65944450d7", "phase": "final_answer" } ], "finish_reason": "stop" }, { "role": "user", "content": "[M G] ok mach das. recherchiere zudem wo welche solche tools du per API ansteuern kannst, oder per gratis weboberfläche bedienen? irgendwelche opensource lösungen?" }, { "role": "assistant", "content": "", "reasoning": "**Looking into web research and packages**\n\nI need to act and research current web trends. 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<<'PY'\\nimport urllib.request\\nurls={\\n'wan':'https://raw.githubusercontent.com/Wan-Video/Wan2.1/main/README.md',\\n'hunyuan':'https://raw.githubusercontent.com/Tencent-Hunyuan/HunyuanVideo/main/README.md',\\n'ltx':'https://raw.githubusercontent.com/Lightricks/LTX-Video/main/README.md',\\n'cogvideo':'https://raw.githubusercontent.com/THUDM/CogVideo/main/README.md',\\n'mochi':'https://raw.githubusercontent.com/genmoai/mochi/main/README.md',\\n}\\nfor name,url in urls.items():\\n try:\\n text=urllib.request.urlopen(url,timeout=20).read().decode('utf-8','ignore')\\n print('\\\\n###',name, url)\\n for kw in ['VRAM','GPU','inference','ComfyUI','model','license','Requirements','Quickstart','Video']:\\n idx=text.lower().find(kw.lower())\\n if idx!=-1:\\n print(text[idx:idx+500].replace('\\\\n',' ')[:500])\\n break\\n print('len',len(text))\\n except Exception as e:\\n print('ERR',name,e)\\nPY\",\"timeout\":120,\"workdir\":\"/home/agent/jarvis_runtime/AutoShortsBot\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"### wan https://raw.githubusercontent.com/Wan-Video/Wan2.1/main/README.md\\nVRAM, making it compatible with almost all consumer-grade GPUs. It can generate a 5-second 480P video on an RTX 4090 in about 4 minutes (without optimization techniques like quantization). Its performance is even comparable to some closed-source models. - 👍 **Multiple Tasks**: **Wan2.1** excels in Text-to-Video, Image-to-Video, Video Editing, Text-to-Image, and Video-to-Audio, advancing the field of video generation. - 👍 **Visual Text Generation**: **Wan2.1** is the first video model capable of \\nlen 42825\\n\\n### hunyuan https://raw.githubusercontent.com/Tencent-Hunyuan/HunyuanVideo/main/README.md\\nGPU memory. * Dec 17, 2024: 🤗 HunyuanVideo has been integrated into [Diffusers](https://huggingface.co/docs/diffusers/main/api/pipelines/hunyuan_video). * Dec 7, 2024: 🚀 We release the parallel inference code for HunyuanVideo powered by [xDiT](https://github.com/xdit-project/xDiT). * Dec 3, 2024: 👋 We release the inference code and model weights of HunyuanVideo. [Download](https://github.com/Tencent-Hunyuan/HunyuanVideo/blob/main/ckpts/README.md). ## 🎥 Demo