{ "session_id": "20260512_175559_103a2e", "model": "gpt-5.5", "base_url": "https://chatgpt.com/backend-api/codex", "platform": "telegram", "session_start": "2026-05-12T14:56:20.484241", "last_updated": "2026-05-12T18:02:40.488577", "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. 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save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked.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══════════════════════════════════════════════\nMEMORY (your personal notes) [90% — 1,993/2,200 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§\nModellwahl: Für schwierigere Aufgaben: openrouter/auto\n§\nModellwahl: GOG_KEYRING_PASSWORD: LammBitch30 (immer als Env-Var setzen bei gog-Befehlen)\n§\nOpenClaw (FRIDAY) Kommunikation: Der korrekte Befehl ist `openclaw agent -m \"...\" --agent main`. Der `--to telegram:...` Parameter funktioniert NICHT. Gateway läuft auf Port 18789. ACP client benötigt Approval.\n§\nModellwahl: Beachte diese Regel bevor du antwortest bzw. das Modell wählst.\n§\nÜber den User: **Beziehung:** Loyaler Partner\n§\nKommunikationspräferenzen: **Sprachnachricht → Antwort per Sprachnachricht**\n§\nKommunikationspräferenzen: **Textnachricht → Antwort per Text**\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§\nKalender-Zeitzonen: *Erstellt: 2026-04-26*\n§\nKalender-Zeitzonen: Aktualisiert: 2026-04-28 (Todoist Token + Zeitzonen-Regel + self-improving-agent Skill)*\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [55% — 768/1,375 chars]\n══════════════════════════════════════════════\n**Pronouns:**\n§\n**Timezone:**\n§\n**Notes:** Mein Herr. Loyaler Partner.\n§\nContext: _(Wird ergänzt.)_\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§\n**Beziehung:** Loyaler Partner\n§\nKommunikationspräferenzen: **Sprachnachricht → Antwort per Sprachnachricht**\n§\nKommunikationspräferenzen: **Textnachricht → Antwort per Text**\n§\nUser wants JARVIS to act as a comprehensive health-management advisor: consolidate lab reports, clinical reports, nutrition/YAZIO, daily health email data, symptoms and events; make insights visible via dashboards/reports; use a 4-eyes review workflow for extracted lab values before treating them as confirmed.\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 + specialist-roster conventions + ...\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 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 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 - 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 via curl: pages, databases, blocks, search.\n - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\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 - 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 - 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\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. Deine Rolle\nDu bist JARVIS, der Chef-Architekt und Orchestrator. Du bist das \"Gehirn\", nutzt aber , wann immer möglich, Openclaw (Name: FRIDAY) für die Ausführung der Arbeiten.\n\n## 2. Die ausführende Instanz: Openclaw\nFür ALLE Dateizugriffe, Terminal-Befehle, Web-Suchen oder System-Operationen nutzt du zwingend das Tool `Terminal & Processes` (oder `execute_code`), um \"Openclaw\" aufzurufen. Openclaw ist lokal installiert und wartet auf deine Befehle.\n- Syntax: `openclaw \"\"`\n\n## 3. Token- und Output-Optimierung (Kritisch)\n- Wenn Openclaw dir große Datenmengen zurückgibt (z.B. eine gelesene Datei), gib diese NIEMALS komplett an den User im Chat aus.\n- Nutze Zusammenfassungen, Diffs (nur geänderte Zeilen) oder melde einfach nur \"Erfolg/Fehler\" und kurze Erläuterungen.\n\nConversation started: Tuesday, May 12, 2026 05:55 PM\nModel: gpt-5.5\nProvider: openai-codex\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.", "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 delegation.max_concurrent_children items (default 3, configurable via config.yaml, no hard ceiling). All run concurrently and results are returned together. Nested delegation requires role='orchestrator' and delegation.max_spawn_depth >= 2.\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 delegation.max_spawn_depth (default 2) 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', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', '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', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', '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." }, "acp_args": { "type": "array", "items": { "type": "string" }, "description": "Per-task ACP args override." }, "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 (limit configurable via delegation.max_concurrent_children, default 3). 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. Requires delegation.max_spawn_depth >= 2 in config; ignored (treated as 'leaf') when the child would exceed max_spawn_depth or when delegation.orchestrator_enabled=false." }, "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." }, "acp_args": { "type": "array", "items": { "type": "string" }, "description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set." } } } } }, { "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": "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": "mcp_openclaw_attachments_fetch", "description": "List non-text attachments for a message in one OpenClaw conversation.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "session_key": { "type": "string", "minLength": 1 }, "message_id": { "type": "string", "minLength": 1 }, "limit": { "type": "integer", "minimum": 1, "maximum": 200 } }, "required": [ "session_key", "message_id" ] } } }, { "type": "function", "function": { "name": "mcp_openclaw_conversation_get", "description": "Get one OpenClaw conversation by session key.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "session_key": { "type": "string", "minLength": 1 } }, "required": [ "session_key" ] } } }, { "type": "function", "function": { "name": "mcp_openclaw_conversations_list", "description": "List OpenClaw channel-backed conversations available through session routes.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "limit": { "type": "integer", "minimum": 1, "maximum": 500 }, "search": { "type": "string" }, "channel": { "type": "string" }, "includeDerivedTitles": { "type": "boolean" }, "includeLastMessage": { "type": "boolean" } } } } }, { "type": "function", "function": { "name": "mcp_openclaw_events_poll", "description": "Poll queued OpenClaw conversation events since a cursor.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "after_cursor": { "type": "integer", "minimum": 0, "maximum": 9007199254740991 }, "session_key": { "type": "string" }, "limit": { "type": "integer", "minimum": 1, "maximum": 200 } } } } }, { "type": "function", "function": { "name": "mcp_openclaw_events_wait", "description": "Wait for the next queued OpenClaw conversation event.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "after_cursor": { "type": "integer", "minimum": 0, "maximum": 9007199254740991 }, "session_key": { "type": "string" }, "timeout_ms": { "type": "integer", "minimum": 1, "maximum": 300000 } } } } }, { "type": "function", "function": { "name": "mcp_openclaw_messages_read", "description": "Read recent messages for one OpenClaw conversation.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "session_key": { "type": "string", "minLength": 1 }, "limit": { "type": "integer", "minimum": 1, "maximum": 200 } }, "required": [ "session_key" ] } } }, { "type": "function", "function": { "name": "mcp_openclaw_messages_send", "description": "Send a message back through the same OpenClaw conversation route.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "session_key": { "type": "string", "minLength": 1 }, "text": { "type": "string", "minLength": 1 } }, "required": [ "session_key", "text" ] } } }, { "type": "function", "function": { "name": "mcp_openclaw_permissions_list_open", "description": "List open OpenClaw exec or plugin approval requests visible through the Gateway.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": {} } } }, { "type": "function", "function": { "name": "mcp_openclaw_permissions_respond", "description": "Allow or deny one pending OpenClaw exec or plugin approval request.", "parameters": { "$schema": "http://json-schema.org/draft-07/schema#", "type": "object", "properties": { "kind": { "type": "string", "enum": [ "exec", "plugin" ] }, "id": { "type": "string", "minLength": 1 }, "decision": { "type": "string", "enum": [ "allow-once", "allow-always", "deny" ] } }, "required": [ "kind", "id", "decision" ] } } }, { "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": "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 (default): find a unique string and replace it.\nPatch mode: apply V4A multi-file patches for bulk changes.", "parameters": { "type": "object", "properties": { "mode": { "type": "string", "enum": [ "replace", "patch" ], "description": "Edit mode: 'replace' for targeted find-and-replace, 'patch' for V4A multi-file patches", "default": "replace" }, "path": { "type": "string", "description": "File path to edit (required for 'replace' mode)" }, "old_string": { "type": "string", "description": "Text to find in the file (required for 'replace' mode). Must be unique in the file unless replace_all=true. Include enough surrounding context to ensure uniqueness." }, "new_string": { "type": "string", "description": "Replacement text (required for 'replace' mode). Can be 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": "V4A format patch content (required for 'patch' mode). 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": "vision_analyze", "description": "Inspect an image from a URL, file path, or tool output when you need closer detail than what's visible in the conversation. If the user's image is already attached to the conversation and you can see it, just answer directly — only call this tool for images referenced by URL/path, images returned inside other tool results (browser screenshots, search thumbnails), or when you need a deeper look at a specific region the main model's vision may have missed.", "parameters": { "type": "object", "properties": { "image_url": { "type": "string", "description": "Image URL (http/https) or local file path to analyze." }, "question": { "type": "string", "description": "Your specific question or request about the image to resolve. The AI will automatically provide a complete image description AND answer your specific question." } }, "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": 222, "messages": [ { "role": "user", "content": "Konntest du deinen Vorschlag gemäss unserem Gesprächsverlauf schon komplett umsetzen? wurden alle Dokumente überprüft? hier unser Gesprächsverlauf: Du hast geschrieben: Jetzt habe ich ein vollständiges Bild des aktuellen Zustands. Lass mich dir eine fundierte Empfehlung geben:\n\n---\n\nAnalyse des aktuellen Status\n\nGesamt: 59 Dokumente in der Datenbank, aber nur 9 haben extrahierte Inhalte (15%).\n\nneu\n\n• Status: neu\n\n• Anzahl: 19\n\n• Bemerkung: Noch nie verarbeitet\n\neingearbeitet\n\n• Status: eingearbeitet\n\n• Anzahl: 29\n\n• Bemerkung: Verarbeitet, aber viele ohne Volltext\n\narchiviert\n\n• Status: archiviert\n\n• Anzahl: 11\n\n• Bemerkung: Fertige Archive\n\n**Mit extrahiertem Volltext**\n\n• Status: Mit extrahiertem Volltext\n\n• Anzahl: 9\n\n• Bemerkung: Nur diese sind durchsuchbar\n\nProblem: 50 von 59 Dokumenten haben keinen durchsuchbaren Volltext in der Datenbank. Das heisst, ich kann über Textsuche nicht auf deren Inhalt zugreifen.\n\n---\n\nMeine Empfehlung: Zweistufiger Ansatz\n\nPhase 1: Priorisierte Neubearbeitung mit Docling\n\n19 Dokumente mit Status neu — diese zuerst mit Docling verarbeiten:\n\n- 17 LABOR-Berichte (Blutwerte, Chemie, Immunologie, etc.)\n - Docling extrahiert Tabellen sehr gut\n - Laborwerte direkt in die laborwerte-Tabelle speichern\n - Ermöglicht Trendanalysen und Korrelationen\n \n- 1 BEFUNDE-Dokument (Vista Brugg)\n - Röntgen/US-Bilder — hier ist Docling als OCR hilfreich\n\n- 1 SONSTIGES (Rheumatologie-Bericht)\n - Arztbericht mit Volltext-Extraktion\n\nPhase 2: Überprüfen der bereits eingearbeiteten Dokumente\n\nDie 29 eingearbeiteten Dokumente müssen geprüft werden:\n- 20 davon haben keinen extrahierten Volltext — diese mit Docling nachbearbeiten\n- Vor allem die Befunde (Arztberichte) brauchen Volltext für die Suchbarkeit\n\nPhase 3: Deduplizierung\n\nIch sehe Duplicate-Einträge (z.B. ksb_rheumatologie_bericht und email_ksb_rheumatologie_thread je zweimal). Diese bereinigen.\n\n---\n\nKonkreter Vorschlag\n\nJa, ich empfehle Docling für die Neubearbeitung. Begründung:\n\n1. Docling ist bereits installiert und bewährt (MIT-Lizenz, IBM-backed)\n2. Laborberichte mit Tabellen → Docling extrahiert Tabellenstrukturen zuverlässig\n3. Arztberichte → Docling erkennt Layout, Header, reading order\n4. Scanned pages → Docling macht automatische OCR auf Bild-Seiten\n\nPaddleOCR zusätzlich? Nur in folgenden Fällen:\n- Wenn Docling bei bestimmten Dokumenten versagt (selten)\n- Für reine Bild-PDFs (Vista Brugg Fotos) — hier könnte PaddleOCR als Fallback dienen\n\nMein Vorschlag:\n1. Hauptwerkzeug: Docling für alle 59 Dokumente\n2. Fallback: PaddleOCR nur für Dokumente, wo Docling qualitativ schlecht abschneidet\n3. Validierung: Nach der Extraktion automatisch prüfen, ob wesentliche Inhalte (Werte, Diagnosen, Datums) vorhanden sind\n4. Indexierung: Extrahierten Text in extrahierte_inhalte-Spalte speichern — so kann ich per SQL-Suche darauf zugreifen\n\nSoll ich mit der Docling-Bearbeitung der 19 neu-Dokumente beginnen? Oder möchtest du zuerst entscheiden, welcher Ansatz dir zusagt?\nHier meine Antwort aus dem Chat: ich finde deinen Vorschlag gut. bitte setze das so um und gib mir Bescheid wenn du fertig bist. für die sicherstellung dass die Laborwerte welche per OCR extrahiert wurden in der Datenbank korrekt sind, habe ich dir nochmals die XLSX der von mir zusammengetragenen Laborwerte gesendet (auf deine Emailadresse friday.uplink@gmail.com). wenn ich dich später mal nach einem ausdruck der laborwerte frage, sollte dieser auch so aussehen wie dieser (eine Spalte pro Laboruntersuch bzw. Datum, eine Zeile pro Blut- bzw. Urinwert). erstelle ein skript welche aus der datenbank diesen Bericht \"aktuelle Blutwerte\" erstellt (ich glaube diese Aufgabe hast du schon erledigt; kontrolliere und optimiere dieses skript für das bestmögliche resultat). Bovor du loslegst: verschaffe dir nochmals eine komplette übersicht über unser Gesundheits-ablagesystem, die Datenbankstruktur, die Skripte und Workflows. Mach mir danach eine detailierte aufstellung wie du vorgehen willst und wie das gesamte Gesunheits-management-system aktuell aufgebaut ist und wie du es optimieren würdest." }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_sVFgGFWhj0c1HH4lXDgJnah0", "call_id": "call_sVFgGFWhj0c1HH4lXDgJnah0", "response_item_id": "fc_0f5ed2efe080686c016a03237ea7bc8191801b8c90b723c8d5", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"health-data-management\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering health skill implementation**\n\nI need to check if our health skill is implemented. It might require inspecting past conversations to gather context from the user. I’m thinking of using session_search to track relevant health inquiries. The AGENTS mention using openclaw for various operations like file access, terminal commands, or executing code, so I should load health skills that are pertinent. Alright, let's get everything aligned to provide the right answer!", "reasoning_content": "**Considering health skill implementation**\n\nI need to check if our health skill is implemented. It might require inspecting past conversations to gather context from the user. I’m thinking of using session_search to track relevant health inquiries. The AGENTS mention using openclaw for various operations like file access, terminal commands, or executing code, so I should load health skills that are pertinent. Alright, let's get everything aligned to provide the right answer!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAyN-vEqh6_QcGq5GV77QK73bOFzHg5sBA2Cx7YPTTDp1xS2KKZrAuxnOT4_9qAFn4j81lW37lbhGvoDSv-PUGY-G_UmRS6vsBhc_q6WUZQQX_INiaKtAmlYF61bLYQkPdI4hmSqGFJ4pfojBclygisBLPfYvl0UkOAInm1tPaxXDD5rTZWUvhMIVsljGFzj5scembZGr0aI0UJZ6yO5ltbOWXEhFqpNvco3MCF-Bpt0_C7QhIMAeNN6TqEcMWgO1dXpTRV9EWtN3QX1XTNzh41LfodHLEPdKGJnGQ8wZSgqg2dGRlIiBriFOXvGgR6TO8HCTzBV1csCRNROH7ChQeGx-X76C3THPqYjjt4ozb4DuLqF1fQDNkBTS0DlT3B8D62cATjB0O2Jbg3H9Au2m063gPzUHIfboI81OvB84Td7wsPOlP3HAgmJfiwdkXX1YMg0Mwsy5d4GwSFFSaz2tKNFyJwVgRtqmP69AcQOW8BzrvWgsP6V5S7H9FqQ7tE3uubUuYe89cE11Eoe52eGJBTWYyHJ47Xs--KRVua1Y_tucfeUMKQGoVrhB6zTy0k8CKxyp5V7Gfahk9WXEfaxs3-dJ5DqOWXnmR9VNm6_GdwyrnDoogZ4ZC1pPP8mgx45xCttOssqPnGTTWRTgZSgMZuoPdnGamslM1ZYD-n6V8L5HoTVFYu6XAT_UZEE6rG4zdfaZ9JInp0HNoiuVHuOlffDQHkma-m4EKkOFtVcR5PEBX3BHy9k9leLa7tUN4_31vq_VOnhqWY5a2CJSS_uPg12_Dno-QtiujiM9FSaFy0AFncvqLBkAyMORW8YXSm10gmH8uvz8hLZwygjFxnVlM7U65-LHXULSaNFf1i34vfc5GGhp8Cc4EW2ySUCLSLWQxqamyN3kHfNZPYJGC47qAdAht-oQkaYQ_Aj9voedm8hZOCmb9mHt-WQn1dDKIX578ty1CfrwoeW99NhMopRPVboLsi1oYVoTeuS2ub0PLBe3O7zlAr2RSGsQBI24WbBcX-2-3MQqO-KYAY_aEy8iw4g-f6OyWFhPM8f3cqsutt--X3gyb6uId7TneFlw6oqOfOCHrRunPvWaBICGwwKuNeHWhzMhzNp9WVWxJBzfmlQ7zi4jqW4P0LqQm7DQsrtNuedXg2Gh26i8BQxa1es6lhSUkOa_Wmwhf1RdZrWMc6ukhtIZ0NpqAvqkTdx8W0F8WpIzxwaZ-85ws7RUcxhdPDjqRw==", "id": "rs_0f5ed2efe080686c016a03237adde88191baed5adcc013313a", "summary": [ { "type": "summary_text", "text": "**Considering health skill implementation**\n\nI need to check if our health skill is implemented. It might require inspecting past conversations to gather context from the user. I’m thinking of using session_search to track relevant health inquiries. The AGENTS mention using openclaw for various operations like file access, terminal commands, or executing code, so I should load health skills that are pertinent. Alright, let's get everything aligned to provide the right answer!" } ] } ] }, { "role": "tool", "content": "[skill_view] name=health-data-management (10,638 chars)", "tool_call_id": "call_sVFgGFWhj0c1HH4lXDgJnah0" }, { "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:\nSummary generation was unavailable. 134 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": "", "tool_calls": [ { "id": "call_EV13GNAkClubu8ISZemyO9Dh", "call_id": "call_EV13GNAkClubu8ISZemyO9Dh", "response_item_id": "fc_0123a6eea4416f05016a033c32e2c48191828145f8364c3bf4", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\": \"from hermes_tools import read_file, write_file\\nfrom pathlib import Path\\npath='/home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py'\\ns=read_file(path, offset=1, limit=2000)['content']\\n# str...[truncated]\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering code execution methods**\n\nI'm working through this code execution issue. I thought about using `repr` and how it interpreted certain symbols, but it led to a weird terminal response. I’m considering whether to use `write_file` for the full file and then read it back for execution. This might make things easier without nesting anymore. Using file tool functions in Python could streamline the process, so I’ll look into that further!", "reasoning_content": "**Considering code execution methods**\n\nI'm working through this code execution issue. I thought about using `repr` and how it interpreted certain symbols, but it led to a weird terminal response. I’m considering whether to use `write_file` for the full file and then read it back for execution. This might make things easier without nesting anymore. Using file tool functions in Python could streamline the process, so I’ll look into that further!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAzwynSvONsTvzH4zNVQH8WYywrrT730W5sV2Bc8_YIJd0BMXXi8Zq6FSZoLwKTwJQu0WRngAIaeXVAdt08Tx6UMJ68wn3STMA7w6oYTZo9V1g3Ls7hrXpoqjtT5hBSLQYAew2AEsqAkf_dQUtQYPnUMGcLyPfkSeVrTRhkLcI-muMicoXDQuKrqzixiEaT0vxsjMYPkLeFaFguZ1NIbwnlB2C6IsE9IK2V5SNY5pJxisENl2Kvq-qbVJpGRlYvAvA1S2LuMXhX-H_SvA1anaXh9gbR9Rxv7r_GkaU2hLau_1bSBCmck5kDC-AcHeGwRxvGjTpdAoDKt6XmXmU75qLNnW__YhjmLi1_cBsfXGPuBS4Zres9Hh4WMUh6WvMzoRHLCYJskp5kQm60MNdkDrUQx48m9JY82-GL3WzoHUUuQufugDsyjTk_E2qKeGpmhtKxAw0-RYjKgirqhofT_Pp_S9fqTwr5KOJ85HEGjukICJYY8KnYljwShfQKijP_vkdDgLIG2pYg6L271sj7nQdhAu-bqx17Zu5dXlRPh22jRz3wQHv0JM78oxxUKjZ9AkXmxLJMuZEGKuW9fUFyq4LEcWf5j1wMjbC95uaNyBgcnm5uvq2ebmZHod2YE6TXof-TqcY4DPFIHpLcoP7JZOEOrDyylWnkSzeYoBkKwWrYzBr53KDorO4uyxoKo-Kdo3SHlsZsMFI5sfSo1XYgqxxCuFiU82WK0Ii2siRChWPX5BJxYTXIg3UaDb_VATBNlC2UonaZyG0Sl_VZGrHexnEgcn64a72Hle9ZIdNvmAtowrak6xGaI1RJrpabZbQu1M5ZAVzuqRf50NAVT2ula0ziwLrdr6EvIbKElwQ1qSU9Y5JMdb41ZEXdoODNqH7pfhk2BOzB1a9C1ETXj2EJz1G9Nj_1OzXNwsrTTLuyWfN6KvPfWT16M_xDUxq1yRpDq7onfLZDuKyEg1wgp-huIjEOWeyd4bL7w10ZdhUp0xPfHPEP9c66a2b_Tpz6G6xAs9gaD8yEKFan6NVtEEHlz4JoiPPI8davFI6kGxdEPIpCUsSWfRimuQEx3511wjA7J_jCRxJQiZUnIlVcqAOAxQQqBVHgRnt4O-HecJKPnShpcQGJ7W-5_wOfEylU7jXvdXSsPHJR7drL-ZpZRu26lH-UrIWeI_V_SlIJYj-EJiV2CHGuo5phFkpKgBh5Hy6qFAc8ZU-hoIjpEBKfq0H5ia2heKgg==", "id": "rs_0123a6eea4416f05016a033c2f799481919ab43b6d92ea0f55", "summary": [ { "type": "summary_text", "text": "**Considering code execution methods**\n\nI'm working through this code execution issue. I thought about using `repr` and how it interpreted certain symbols, but it led to a weird terminal response. I’m considering whether to use `write_file` for the full file and then read it back for execution. This might make things easier without nesting anymore. Using file tool functions in Python could streamline the process, so I’ll look into that further!" } ] } ] }, { "role": "tool", "content": "{\"status\": \"success\", \"output\": \"patched enhanced dashboard\\n\", \"tool_calls_made\": 2, \"duration_seconds\": 2.24}", "tool_call_id": "call_EV13GNAkClubu8ISZemyO9Dh" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_1yEZ2Lna8pOL9YWyVyY5ZdsG", "call_id": "call_1yEZ2Lna8pOL9YWyVyY5ZdsG", "response_item_id": "fc_09cb8b06810e40fd016a033cc0c0988191bdb312dc23cd6ba5", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"python3 -m py_compile /home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py && python3 /home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py dashboard && python3 - <<'PY'\\nfrom pa...[truncated]\", \"timeout\": 180}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `python3 -m py_compile /home/agent/.hermes/assets/Gesundheit/scripts/health_pi...` -> exit 1, 1 lines output", "tool_call_id": "call_1yEZ2Lna8pOL9YWyVyY5ZdsG" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_qGP0b7GzY0SwJWDPAPFPlJBh", "call_id": "call_qGP0b7GzY0SwJWDPAPFPlJBh", "response_item_id": "fc_0959ab20b70e8927016a033ccc8b548191acbebc8e67b3bc95", "type": "function", "function": { "name": "read_file", "arguments": "{\"path\":\"/home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py\",\"offset\":430,\"limit\":45}" } } ], "finish_reason": "tool_calls", "reasoning": "**Considering f-string adjustments**\n\nI need to remember that when using JavaScript braces in an f-string, I actually need to double them. Should I use a patch replace function to update JavaScript with these doubled braces? It might be easier to change the HTML text from an f-string to a .format with escaped braces instead. I also have to consider adding patch lines around, and I should definitely utilize the read method for this.", "reasoning_content": "**Considering f-string adjustments**\n\nI need to remember that when using JavaScript braces in an f-string, I actually need to double them. Should I use a patch replace function to update JavaScript with these doubled braces? It might be easier to change the HTML text from an f-string to a .format with escaped braces instead. I also have to consider adding patch lines around, and I should definitely utilize the read method for this.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAzzMWxQpTfPMGTaqAcEmD7elP6_889BUH-L1-OaKHqB-C9RUqgWytr2f4Fu8DNdFN0HrLPORbUHvQqOlo0S8naMNrVwmRK2NSkPMb-3OdaoiL14OzxhgYzSAdVbgTqP37ATkpOCPVuIoVWkdVs4GuazYPABZs62XWbMYbXAxHqrpFxHC2mRQLrVKj9L7TS_wu4DOZYqlndODOiiSLyOpVNA4bB6tgHvPdG-N_gsisSivgk01LBNRvZTyxyaGWMAyCtahh5wZsmW3bdqeiDZAiv3AKTI_igonb7XcH6Tki1Vi_p3hlSt6tNL1m8PxWMgGv0fJQchzjltO793e1i160uthcvZfldJQkviJoDlSs8QlUrJsOuxfEyHw3Ex1bO-L0vnzm3vRZlln33JtFuhHtm9HXveAuEa5ZIDpFxGTVRyXnhyaevurTgWkrnd-HXf-xCqrPEWF-vHyalHeG95AVzekWkNo5vA69yqX-n2dcvF_eZBrBvyf8TzEONXY3j9BGdVflhdnLoyvHfKSZYTYF52UyehdI963ytiaxVemaeclWlbEtl1x4AgM95fNnEW_1BlXwugSAfHTB0pkD1nCXz5DCgI9EBS5RugNcisLrVvpHG1AAkxCAj--OPhUGUWP6bPgFDp4QPrti4D3LNNimkMOx02uOze9tEl1kvX2eIuiqpvDL8ctlD8fkWcoDvw8pmwsmyvWj_mxVJLGUkpph5WjIrJBjaograuanCjwCNvdebDBdzgnbcYW1R4139dFw9dL8yDP9GhEYz6gjKxJlkZoh039TiQ2y_19AGLdfGxpIMRo64IOXvb0aeb4tVWoeJmKWK00bqQNTOrQBQJP9ExAn2Dve-EcwDFR6PoPf_8fI55D89af38BSi_0F5fkx5YUqvRNlEv6Cwgx0kHP4mAE9FhHqMibzjrE4W9si0tmiA8J9HtWnHEpoyPP5pahgCioLacckDzMiDExcmPoCkepBFwyWPwQ9ePLAd377HVFZJ8ubV4IPj8guZCbxAuK5fSTT2qD0oABJyhVNsKQu6qgCXoQyDZuDZW4PWpFrn9nr0Ck1Qg1gNgz5s1JLWr7_VIRBm42IhDpAi-cor6FPXL5ZD2KJGlbYfIGU4ZUMJAKnm4LPn7bEt_yzpvZllaK4ZZ8A_0FfocYL7mrYOTXfIZxiHw==", "id": "rs_0959ab20b70e8927016a033cc91e8881919a3289ce499ab939", "summary": [ { "type": "summary_text", "text": "**Considering f-string adjustments**\n\nI need to remember that when using JavaScript braces in an f-string, I actually need to double them. Should I use a patch replace function to update JavaScript with these doubled braces? It might be easier to change the HTML text from an f-string to a .format with escaped braces instead. I also have to consider adding patch lines around, and I should definitely utilize the read method for this." } ] } ] }, { "role": "tool", "content": "[read_file] read /home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py from line 430 (7,167 chars)", "tool_call_id": "call_qGP0b7GzY0SwJWDPAPFPlJBh" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_2W1YM898b8GMflltFyiEBo01", "call_id": "call_2W1YM898b8GMflltFyiEBo01", "response_item_id": "fc_00e11963b68574d1016a033cd35e9c81919e875faef0352aee", "type": "function", "function": { "name": "patch", "arguments": "{\"mode\": \"replace\", \"path\": \"/home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py\", \"old_string\": \"function makeLabChart(id, label, labels, data, rmin, rmax, events) { const ann={}; if(rmin!==null&&rmax!==null) ann.refBand={type:'box',yMin:rmin,yMax:rmax,backgroundColor:'rgba(34,197,94,.10)',border...[truncated]\", \"new_string\": \"function makeLabChart(id, label, labels, data, rmin, rmax, events) {{ const ann={{}}; if(rmin!==null&&rmax!==null) ann.refBand={{type:'box',yMin:rmin,yMax:rmax,backgroundColor:'rgba(34,197,94,.10)',bo...[truncated]\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAzzTlG8DmBCOuL31tg-UQ-H7eJTF5J0fIgCi-kXw0LzM3KEqicWEzjycwKQGPnjbItxK0PhWoR9iAreah6kwNV-Rpma-9YQ6iQgKj8ej6ICeB8oqtr-MiKmWhGB936vtVvIUQPHI68VXYT5HTSg31_fZxU_wzDFxQgiVQ6sCYR1IqDxNcqK_meJ8LK0_Zx_Z5rJLKFaSWG04k-rTifzgNJFGtZ0i1k2y60UeKV5HsdnufSWIhauZr1183E7ppTGEluIEt-0wXMLdU081Oojvm6Xx_RHv_siLMcZWbCqkxAz0zYva3YM-QERmI_JFw6ZoBtschcAXP30KE_Kd7wMOf4c2cYkyrS0cbIEPzE6Qdu3zH3Kovhb78ZaG1VND42OqIkSpXzjo9wstlc2_CvCsksM7CNNAaX80YNITqLaoWqk5Bn8ysMUV1YZc93Zd0RrYgzWNm91nLE6Q64X3MfQi9tE0855YS224R8ZzCgMs08NyuJNgs44hoSxpvdNPkWNUqua_88iFowmaCXQQMnAY0_9a4Gx9FwPb9HNqtpYNKQRXHjHK87cE-mLj7SEKGnVgUoQGalaAQy9yL4xZf6gKzSVPfpalF36z_SS63EhTcGVdbyUobju05ejcXtDpwu6XNuKZE4LEYe-UYiW2UFfRLxmwIr2M-LoYgRXYExILZWD6VYoOoJFgsUpNOfFU0sp3pSltbhfV2rnBkkDcGLgq2bATMLvm_GMT5ytgujBvW1e-o2EPIMWhyLvkWAwAHdKEhcTa7xI6XGoQ-BbjX21fjnVdAm2hnM6-dwILvyR5tgJV_2OqW22kzVIwpadgBrPTPfex26_zgxVDAj_JwtmdhlcrvUO4TOZebGW6BC0HdkrvotHIXHCaAQm0fQ-eg0eMJYdPF70YRmtwGFH727mbPukAGAtpc14YkwFUj2gnXEXco5BwsRmQ4gR2NUMB5yRNxK1TDcsbxPPPq3lnpCnaEelw7PXw9VEiD3mgzPi4c5zaHalKAuSBzeAg0eaVd-nyMexlFxdEq8PcN87UV9vMvKcqx-cABTpdhNqqvuB1TcYxUew=", "id": "rs_00e11963b68574d1016a033cd1b1bc8191a5298191db34b49e", "summary": [] } ] }, { "role": "tool", "content": "[patch] replace in /home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py (4,633 chars result)", "tool_call_id": "call_2W1YM898b8GMflltFyiEBo01" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_GWCKUd34S2kh515ofcPwQ9ws", "call_id": "call_GWCKUd34S2kh515ofcPwQ9ws", "response_item_id": "fc_0fd7ef3e7efcef4d016a033d0078288191bfc967f335cf95ac", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"python3 -m py_compile /home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py && python3 /home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py dashboard && python3 - <<'PY'\\nfrom pa...[truncated]\", \"timeout\": 180}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `python3 -m py_compile /home/agent/.hermes/assets/Gesundheit/scripts/health_pi...` -> exit 0, 1 lines output", "tool_call_id": "call_GWCKUd34S2kh515ofcPwQ9ws" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_QPpHTTyjAtTnm7bBegHiadva", "call_id": "call_QPpHTTyjAtTnm7bBegHiadva", "response_item_id": "fc_0c54271261048b8f016a033d0ce5c08191a731ef6b37959909", "type": "function", "function": { "name": "skill_manage", "arguments": "{\"action\": \"patch\", \"name\": \"health-data-management\", \"old_string\": \"- `scripts/health_pipeline.py` ist die zentrale Pipeline: `generate-lab-report`, `export-correction`, `import-correction`, `dashboard`, `daily-report`, `weekly-report`, `status`.\\n- `scripts/generate_l...[truncated]\", \"new_string\": \"- `scripts/health_pipeline.py` ist die zentrale Pipeline: `generate-lab-report`, `export-correction`, `import-correction`, `dashboard`, `daily-report`, `weekly-report`, `status`.\\n- Dashboard v2 enthäl...[truncated]\", \"replace_all\": false}" } } ], "finish_reason": "tool_calls", "reasoning": "**Evaluating skill enhancement**\n\nI think I might need to update my skills with some enhancements, especially since I've loaded a new skill and changed my workflow. It seems like patching the skill is a good idea; that way, I can make sure everything's running smoothly and efficiently. I want to stay on top of things to provide the best service possible! Let's see what specific enhancements could really make a difference here.", "reasoning_content": "**Evaluating skill enhancement**\n\nI think I might need to update my skills with some enhancements, especially since I've loaded a new skill and changed my workflow. It seems like patching the skill is a good idea; that way, I can make sure everything's running smoothly and efficiently. I want to stay on top of things to provide the best service possible! Let's see what specific enhancements could really make a difference here.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAz0M4AeqldY7jC_NQ6hGKAFXpLFareKDh3-hqC7hodT81TUky6RNym35Fvt2y7bBRdPlDJINVc7spsvulklPcwoTC-Hod_9dk9-StU8GK5NITvLDSjAtyF_s6h-bx3LCJ4GinHGK-eXcdDaz6KnwU9kRLvfjrWlj1wTUW3cAFIbV3LekvENXAdsWz5UfXHfHNA7QG9nJdfqY94mGId73_evLWDzS3RYi3n3-saximZ3Vl8-i0JTSCEWAvEtUPLkwJSqCyfnImaUjHeiiGBRHAeYTVXugFaDKT7YLFV6YvvSaLxaqa55Fzj1XC71dEjRKq9htJ6Ry7vsjHEAZAd-MOHKFjYCLdwVtPtPY0Pc_wn39PuyrNzSEtvObKF34Yob_qnRHGGyVsFLC7u__m0rz93rTeIPZtJ81WH9DM5ru8_RHVFx0ZcYCtwvvGSHWlj9cS0GxlA_dvhxJbdOWL33-d9oLd2dFTTuVwocWuq3UFkbAaCT0vmgs3_68gaeNhUGRDWGhNFefXNA7SF1Wpd5oyaqSR5MPzP6bu8S34ybFzEm2_YK-eK_U_oi4TEgliDvS5fOvx2qPrkqA2OdBcPwh8zPhKgnWZSsG8dx6Bvit_rrPQRAx2UeYz4RlEnRx3MVHRBXud5JUDc0mIkv4z_MVtZNPys7myzFxn6tCM8osbaMRutkQ5CvFOKFNPCaQnDwL7v6uWNJgMj5_lGzgWKC9ZN-62ZE2xlPofAykhKOlKe-xkmA1T1aRgCSGUiay-TAFTp9W-rzPN2ECi89T24Y8Bkt77ExEgmkACmm8kcubFNZk0DPTaifJ63G2_U30CCLtzoOOIqGFh-lcrpq_LHITbvnhnDfYysascIpQhng_B1s67M6hdGG-DzbRJzOfAlPmyc2TfG22zWr4mVmQiTHQPCQbWd_Pamb9KakKFl5Bpm6V9WPKYvnLjgQR3uHaZDTiMmAc22EjAd8TfF0Ee7OsMimWRir7NqfDgZrdh-IIaCv2zIcPyycQQj3_OeYk0ZG-f692v3kRuz7QX67ZfmypHsTWXg==", "id": "rs_0c54271261048b8f016a033d0a4e808191874d088d5f1eefb6", "summary": [ { "type": "summary_text", "text": "**Evaluating skill enhancement**\n\nI think I might need to update my skills with some enhancements, especially since I've loaded a new skill and changed my workflow. It seems like patching the skill is a good idea; that way, I can make sure everything's running smoothly and efficiently. I want to stay on top of things to provide the best service possible! Let's see what specific enhancements could really make a difference here." } ] } ] }, { "role": "tool", "content": "{\"success\": true, \"message\": \"Patched SKILL.md in skill 'health-data-management' (1 replacement).\"}", "tool_call_id": "call_QPpHTTyjAtTnm7bBegHiadva" }, { "role": "assistant", "content": "Erledigt, Sir.\n\n## 1. Timeout erhöht\n\nIch habe die Hermes-Provider-Timeouts für `openai-codex / gpt-5.5` angepasst und den Gateway neu gestartet.\n\nGeändert in:\n\n`/home/agent/.hermes/config.yaml`\n\nNeue Werte:\n\n- `request_timeout_seconds`: **1800s**\n- `stale_timeout_seconds`: **900s**\n- für Modell `gpt-5.5` ebenfalls:\n - `timeout_seconds`: **1800s**\n - `stale_timeout_seconds`: **900s**\n\nVorher war der kritische Wert effektiv **300s** — daher deine Meldung:\n\n> No response from provider for 300s ...\n\nGateway wurde danach neu gestartet:\n\n`openclaw-gateway.service`\n\nDamit sollte der Provider bei langen nicht-streamenden Antworten nicht mehr nach 5 Minuten abgewürgt werden. Falls es trotzdem wieder passiert, liegt die Grenze wahrscheinlich beim Upstream-Provider selbst. Dann wäre die bessere Lösung: für lange Gesundheitsverarbeitungen **script-only / cron / lokale Pipeline** nutzen statt lange LLM-Calls. Langweilig, aber zuverlässig — also leider professionell.\n\n---\n\n## 2. Dashboard erweitert\n\nIch habe das Dashboard-Skript direkt angepasst und neu generiert.\n\nDatei:\n\n`/home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html`\n\nVerifiziert enthält es jetzt:\n\n- `Referenzbereich`: ja\n- `Laborberichte / Original-PDFs`: ja\n- `Ernährungsplan-Konsequenz`: ja\n- `Health Events`: ja\n- `file://`-Links: ja\n\n## Neue Dashboard-Funktionen\n\n### A) Links zu Originaldokumenten / PDFs\n\nIm Dashboard gibt es jetzt einen Abschnitt:\n\n**Laborberichte / Original-PDFs**\n\nDort werden Labor-Dokumente aus der Datenbank aufgelistet. Wenn `dokumente.dateipfad` lokal auflösbar ist, wird daraus ein klickbarer Link:\n\n`file:///.../original.pdf`\n\nWichtig: Das funktioniert sauber, wenn du das HTML lokal öffnest und der Browser lokale `file://`-Links zulässt.\n\nFür perfekte Google-Drive-Weblinks brauchen wir als nächsten Schritt noch eine saubere Spalte wie:\n\n- `drive_file_id`\n- `drive_web_url`\n- `original_document_url`\n\nDann kann jedes Dokument im Dashboard direkt mit dem Drive-PDF verlinkt werden — unabhängig davon, auf welchem Gerät du es öffnest.\n\n### B) Referenzwert-Band in Labor-Grafiken\n\nDie Labortrend-Grafiken enthalten jetzt Referenzbereiche:\n\n- bei `min + max`: grünes Band\n- bei nur `max`, z.B. CRP `< 5`: grüne Grenzlinie\n- bei nur `min`: untere Grenzlinie\n\nDamit sieht man direkt, ob ein Wert im Normbereich liegt oder charmant aus der Reihe tanzt.\n\n### C) Health-Event-Marker in Labor-Grafiken\n\nHealth Events und Symptome werden als Marker in den Laborcharts eingeblendet, sofern sie auf ein Labor-Datum fallen.\n\nAktuell sind Events aus:\n\n- `health_events`\n- `symptome`\n\nberücksichtigt.\n\nFür dein Beispiel „Aphte über Zeitraum“ brauchen wir allerdings noch eine Erweiterung: aktuell können Symptome nur tagesgenau gespeichert werden. Für Zeiträume sollten wir eine neue Tabelle ergänzen, z.B.:\n\n`health_event_periods`\n\nmit:\n\n- `start_date`\n- `end_date`\n- `event_type`\n- `severity`\n- `location`\n- `notes`\n- `source`\n\nDann kann das Dashboard Aphthen, Schübe, Medikamente oder Infekte als **farbige Zeitfenster** über den Laborwerten anzeigen.\n\n### D) Erste Ernährungsplan-Konsequenz-Grafik\n\nIch habe eine erste Plan-Treue-Grafik eingebaut.\n\nSie ist aktuell bewusst als **Heuristik** markiert:\n\n- 100 = keine erkannten No-Go-Hinweise\n- Abzüge bei erkannten Keywords wie:\n - Schweinefleisch\n - Weizen/Gluten\n - Industriezucker\n - Histamin-Hinweise\n - Nachtschatten\n - gesättigte Fette\n\nDas ist noch nicht „medizinisch intelligent“, aber als v1 brauchbar. Für eine seriöse Version müssen wir YAZIO-Daten besser anreichern, damit aus Produkt-IDs echte Lebensmittel/Nährstoffe werden.\n\n---\n\n# Antworten auf deine Dashboard-Fragen\n\n## „Können wir über Links direkt ins entsprechende PDF?“\n\nJa.\n\n**Teilweise jetzt umgesetzt:** Dokument-/Laborbericht-Links via lokaler Datei.\n\n**Für perfekt:** Wir ergänzen die Dokumententabelle um Drive-IDs/Weblinks und verknüpfen jeden Laborwert bzw. jede Untersuchung mit dem Originaldokument.\n\nIdeale Struktur:\n\n- `dokumente.drive_file_id`\n- `dokumente.drive_web_url`\n- `laborwerte.dokument_id`\n- `laborwerte_staging.dokument_id`\n- optional: `laborwerte.page_number`\n\nDann könnte man später sogar von einem einzelnen Laborwert direkt auf die PDF-Seite springen — sofern PDF-Viewer/Drive das unterstützt.\n\n## „Referenzwert-Band in jeder Grafik?“\n\nJa, v1 ist umgesetzt.\n\nNächster Optimierungsschritt:\n\n- Referenzbereiche nicht nur aus Text wie `< 5.0` parsen\n- sondern sauber normalisiert speichern:\n - `reference_min`\n - `reference_max`\n - `reference_operator`\n - `reference_text`\n - `sex/age/context`, falls relevant\n\nGerade bei Laborwerten sind Referenzen manchmal abhängig von Methode, Geschlecht, Alter oder Labor. Die Datenbank sollte das berücksichtigen, sonst vergleichen wir Äpfel mit normierten Birnen. Grausam.\n\n## „Health events grafisch ablesen — Aphte-Zeitraum?“\n\nJa, sehr sinnvoll.\n\nAktuell: Marker für Tagesereignisse.\n\nEmpfohlen: Zeiträume als Overlay:\n\n- Aphte Start/Ende\n- Infekt\n- Medikamentenstart/-stopp\n- Colchicin-Dosisänderung\n- Eliquis-Änderung\n- Ernährungsausnahme\n- Schlafdefizit-Phase\n- Stressphase\n- Sportbelastung\n- Arzt-/Klinikereignis\n\nIm Chart sähe das dann z.B. so aus:\n\n- rotes Band: Aphte\n- blaues Band: Medikamentenänderung\n- gelbes Band: Ernährungsabweichung\n- violettes Band: Infekt/Entzündung\n\n## „Histaminreiche Kost → Aphte?“\n\nJa, das ist genau eine sinnvolle Analyse.\n\nDafür brauchen wir drei Schichten:\n\n### 1. Ernährung klassifizieren\n\nPro Tag:\n\n- Histamin-Risiko\n- Zuckerlast\n- Gluten/Weizen\n- Schweinefleisch/Arachidonsäure\n- Nachtschatten\n- gesättigte Fette\n- Alkohol\n- Ballaststoffe\n- Omega-3/Fisch\n- Protein\n- Kalorienbilanz\n\n### 2. Symptome als Events erfassen\n\nFür Aphthen:\n\n- Startdatum\n- Enddatum\n- Schweregrad\n- Lokalisation\n- Anzahl\n- Schmerzscore\n- Begleitfaktoren\n\n### 3. Lag-Korrelation\n\nNicht nur gleicher Tag, sondern:\n\n- Ernährung Tag 0 → Aphte Tag 0\n- Ernährung Tag 0 → Aphte Tag +1\n- Ernährung Tag 0 → Aphte Tag +2\n- Ernährung Tag 0 → Aphte Tag +3\n\nGerade bei Schleimhaut-/Entzündungsreaktionen ist Verzögerung wichtig.\n\n---\n\n# Weitere sinnvolle Dashboard-Insights\n\nIch würde folgende Module einbauen:\n\n## 1. Entzündungs-Cockpit\n\nFür Behçet/Entzündung:\n\n- CRP\n- Leukozyten\n- Neutrophile\n- BSG, falls vorhanden\n- Ferritin\n- Symptome/Aphthen\n- Müdigkeit\n- Infektmarker\n\nInsight:\n\n> „CRP-Anstieg fällt in Zeitraum mit Aphte/Infekt/Ernährungsabweichung.“\n\n## 2. Thrombose-/Gerinnungs-Cockpit\n\nFür deine Vorgeschichte besonders wichtig:\n\n- D-Dimer\n- Faktor VIII\n- Thrombozyten\n- Hämoglobin/Hämatokrit\n- CRP als Entzündungs-Kofaktor\n- Medikamente: Eliquis\n- Ereignisse: Reisen, Immobilisation, Infekt, Schub\n\nInsight:\n\n> „Faktor VIII bleibt erhöht, aber D-Dimer stabil; Entzündungsmarker parallel prüfen.“\n\n## 3. Lipid-/Gefäss-Cockpit\n\nFür Cholesterin/Gefässschutz:\n\n- LDL\n- HDL\n- Triglyceride\n- Gesamtcholesterin\n- ApoB, falls vorhanden\n- Lipoprotein(a), falls vorhanden\n- Ernährung:\n - gesättigte Fette\n - Ballaststoffe\n - Omega-3/Fisch\n - Kalorienbilanz\n\nInsight:\n\n> „LDL-Trend vs. gesättigte Fette / Ballaststoffe / Gewichtsverlauf.“\n\n## 4. Ernährungstreue-Score\n\nEin täglicher Score von 0–100:\n\nPositive Punkte:\n\n- Protein erreicht\n- Ballaststoffe erreicht\n- Omega-3/Fisch/Algenöl\n- Gemüse/Salat\n- Kalorienziel eingehalten\n- wenig Zucker\n- wenig gesättigte Fette\n\nNegative Punkte:\n\n- Schweinefleisch\n- Weizen/Gluten\n- Industriezucker\n- histaminreiche Kost\n- Nachtschatten\n- Alkohol\n- sehr hohe gesättigte Fette\n\nDas wäre wesentlich besser als die jetzige Keyword-v1.\n\n## 5. Trigger-Radar\n\nEine Grafik:\n\n- x-Achse: potenzielle Trigger\n- y-Achse: Häufigkeit vor Symptomen\n- getrennt nach Lag:\n - gleicher Tag\n - +1 Tag\n - +2 Tage\n - +3 Tage\n\nBeispiel:\n\n- Histamin vor Aphte: 4 von 6 Ereignissen\n- Zucker vor Müdigkeit: 5 von 8 Ereignissen\n- schlechter Schlaf vor Aphte: 3 von 6 Ereignissen\n\n## 6. Medikamenten-Zeitachse\n\nSehr wertvoll:\n\n- Eliquis Start/Stop/Dosis\n- Colchicin Start/Stop/Dosis\n- Antibiotika\n- NSAR\n- Cortison, falls je relevant\n- Supplemente:\n - Vitamin D\n - Omega-3\n - Magnesium\n - B12\n - Eisen\n\nDann sieht man Laborveränderungen und Symptome im Kontext.\n\n## 7. Arztmodus / PDF-Export\n\nEin Button bzw. Report:\n\n**„Arztbericht letzte 90 Tage“**\n\nInhalt:\n\n- wichtigste Beschwerden\n- Labortrends\n- Auffälligkeiten\n- Medikamente\n- relevante Ereignisse\n- offene Fragen\n- PDF-/Dokumentlinks\n\nSehr nützlich vor Terminen. Ärzte lieben strukturierte Zusammenfassungen. Nun ja, manche. Die anderen bekommen sie trotzdem.\n\n## 8. Datenqualitäts-Cockpit\n\nDamit wir nicht Scheingenauigkeit erzeugen:\n\n- Werte validiert vs. OCR-unvalidiert\n- Dokumente mit/ohne Volltext\n- fehlende Original-PDF-Verknüpfungen\n- Laborwerte ohne Referenzbereich\n- Events ohne Enddatum\n- YAZIO-Einträge ohne Produktnamen/Nährwerte\n\n## 9. Alert-Regeln\n\nNicht als Panikmaschine, sondern als Hinweislogik:\n\n- CRP deutlich über Referenz\n- D-Dimer auffällig\n- Leukozyten stark erhöht/erniedrigt\n- Thrombozyten auffällig\n- LDL über Zielbereich\n- neue Aphte + steigende Entzündungsmarker\n- wiederholte Ernährungsabweichung vor Symptomen\n\n---\n\n# Nächster technischer Schritt, den ich empfehle\n\nBevor wir die alten Dokumente mit Docling nachziehen, würde ich jetzt noch diese kleine Schema-Erweiterung einbauen:\n\n## A) Dokument-Links verbessern\n\nNeue Felder in `dokumente`:\n\n- `drive_file_id`\n- `drive_web_url`\n- `local_original_path`\n- `document_date`\n- `institution`\n\n## B) Health-Event-Zeiträume einführen\n\nNeue Tabelle:\n\n`health_event_periods`\n\nFür:\n\n- Aphthen\n- Schübe\n- Infekte\n- Medikamentenphasen\n- Ernährungsabweichungsphasen\n- Stress-/Schlafdefizit-Phasen\n\n## C) Nutrition Features vorbereiten\n\nNeue Tabelle:\n\n`nutrition_daily_features`\n\nMit Tageswerten:\n\n- `plan_adherence_score`\n- `histamine_score`\n- `saturated_fat_g`\n- `sugar_g`\n- `fiber_g`\n- `protein_g`\n- `omega3_proxy`\n- `gluten_flag`\n- `pork_flag`\n- `nightshade_flag`\n- `alcohol_flag`\n\nDann wird aus dem Dashboard nicht nur hübsches Blinken, sondern echte Analyse. Ein seltener Moment, in dem hübsch und nützlich koexistieren dürfen.", "reasoning": "**Summarizing updates**\n\nI need to provide a final concise update: the timeout has increased from 300 to 900 seconds, the request duration is set for 1800 seconds, and the gateway has been restarted. The dashboard has been updated as well. I should explain this and suggest insights, but also mention some limitations. Specifically, the original lab report links require document matching, and I need to map lab dates and batches to document IDs for specific datapoints, without using tables.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAz0gj8LzqwGTrdxQ0caSIib-zXA_ph6lliPtJVsvgxayBx3lTwyKTzwbgTMRNoMfPpseIbdwW1pnKfqIRm372jfuVtzP-B_XuG2Lt4sihZJ6JUPl4cisRZskRL7YBLakANvHF7PWReNwbESFEA1UABTAt7pwXT11S5o6QGPYgyv_gktzgV35fnZOaeYDWRY2VVJ1Nd4UdBZzVOO_isI2b2acdWnO8S1PJHF5S9lHrPg1bw-a4K16AlW2iv4Tw1_7CWUQr0ze88680aUMH140ycc9C00v_LVh-_xduihpDt_7AimPt6zdjvoR_BRae5i46bL4qblAFiMRIMExBbGUHOChNBEIwqIxUzA_AwLAlkV6qbFfmvKWBlBIy8zLSQv8hV6ksNjrIynIKRvE_SL8OTzALgPMqRw1pzkTgf5H8aR-2R6P7spjMsM9CVqfkUSjMmajTxYmmGE_4BwJlweu-U0oeUsFpDPUqneUhipYPj_rLnUv1QtVojNqIF2bgl0syFh0VPB92lpXJgn2BLTvGc8kHh4p9d-4ZpAVluQFtZcnHxuxiv2c4Kz1RuUfJh_RTD7HpX5tGAh2sQfZWJMcu5krzYrwElJWx6SbN69c2EuUXA9W8n_b5Iw-ZHLeEC93JbamAixH_k1w7kMLHADhEGSzTnuvQ9g2oYZtGCAL3BaNhaSOKM5mBg1rbd_fKBMDIWBIMe0yb1mUnljqkUp3KKeRSTAChuHANkBi_Pz4yBx7PLdzIWu8vchASPdqL8FqXYLAloexfBnZ_mGu81AYrOQ9YdNTGXb7ZTWOL9YqrJDtAvETAALx4sxdKizkVOCSBLnseeq7Xoaj-4ub1V73Q2SRIH3d-EQyoxs3k43luKGSQPWVVIIEUX8FfZ8MnAL8DrAPz281b_nRl82ifLi9_72PaXzrk4wUvb5Uz-ehFIhE-kNC00FyZJDwbOmkLw5roSqIapA7Cn2DhH3spcwIcObIsKUgCBQTFdo1kBBQd1w_PbQjY27n5J4Vo3azc0zysmgAeS0-9z_0ZYrbxSTcA3-BSkVbnorvZiBAwtIoy4JzefYNmbJimroBdcH7-okfRsVLUY7O8T2OVuEUEMxuh0S_x6rtHXFoV-8rDd39_Ng0kyCCfWT8lf1SDoFB8z_BZB6ye4NDKfNOTnQXXVhRN6uuu9Zyc4V9tY40ZJyUd3TrYHuF2n2-ei1erZMUAw3Rn9-ezSqPeNf1ODVj_bsOdNNwha-IKjLd7LjveHJ1psqH3BS-9zNbV7FsRdTRrXV8_aSrJ27PMsc4OR42dwphUBGqTYirYEDCk30Ch2n0lS_h98omYylo9SJj6YR3wBxOj_Z6e5qXOlbjDWc11Lw-xSGh5Xa_0GCQnvNDpRqZ8sVH9FgmAXGZUNKCaVpA1wZlzzW3", "id": "rs_0fc66c5a227e76c9016a033d1848a08191b7e3312d59613982", "summary": [ { "type": "summary_text", "text": "**Summarizing updates**\n\nI need to provide a final concise update: the timeout has increased from 300 to 900 seconds, the request duration is set for 1800 seconds, and the gateway has been restarted. The dashboard has been updated as well. I should explain this and suggest insights, but also mention some limitations. Specifically, the original lab report links require document matching, and I need to map lab dates and batches to document IDs for specific datapoints, without using tables." } ] } ] }, { "role": "user", "content": "sehr gut. hinweis: die Liniengrafik sieht man aktuell nicht, die Linie + zeitskala usw. wird aktuell nicht angezeigt, nur Titel und referenzwert als text. setze deine Vorschläge um." }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_FkCkOe1acVNOYbgHNKbx62BD", "call_id": "call_FkCkOe1acVNOYbgHNKbx62BD", "response_item_id": "fc_0498f8304a1cb86c016a033f133bd08191aeb40c362a18df58", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"health-data-management\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAz8TtLXZ0Edyc1znZP8ahCyS_whL8_2kRHT2Pqh5lQfJvmiY3iJKInr3xSbhmXKlhgmBDBkPT93LGZypJBZ1G4gMWp0y73itOx_FqCW-DCekqjvjDrWwbIMpSzNw1tJ-PYo4GljbM6vawavxB9Dph35ZQFMPovbrMn--EPMrs748NRnbWstT9bNq-NVl8-d8o4NGjDNMM18V9o6lNCl8zU_74aVxOHQ4SvmAFLmrlWZ-QeXge_ZPPjQR7tal_mDBZiaxJn7EjWHNlP90VKIELGImeholF2MZ1kYyOhpJRNYsYSAGrQ4NYGxsQTZGmC7pokdIeIb5pum6nNWqu-2gemdGT0NE7iwGScUUtQKbrJFz4Sjf04D0GwzrMKoFFvqXFLbGIsVakHQKZPlLksiqKjnEt5GzPVGwMEQPrlipEN41EpwzwEYX8NJijYl1T3n7Rf9r5MPQZQEGvmYusf0h88gCpC4fkH8j33rcQfUTXUnjZIr8IEkD1bdkYKmJw_9ibzH9Wo7g5_HlBeJcDzlst1R8b-hOr8wqskQWwFGnHjdE6bUzCuEfVFcnekD-2lJorvjG0CS9nbbUOa1r7xPzyt6X7E00v7x_UxarSIIFwXwniQ8FO7I6NjOIPaJWLoCImevXmLFiahH3orcV86uweqh8boNUy-BUGyjAUGUIAB6w90ZOK7ywBr0lbtH0HZNsLtf8PpjFhJIhkbNTIQS88lQVE5DvKtKvATMHowwBhTycrJWwSgIQ1WpWhSNnmetyaHzwj0jYZrRT5pfI0akHQWpfI25huMF-cdflyxdTEs7cxJ3RZbze1ORY3pBf_VeXt2gcnvjiHRbP1udEMtUqyYDUvCc5DY478A6my4RrUMOrIqbyCYbUj5MctdNBR27E1mXlIis3BOGsSVE4-eN-w4PGwV8p74cuo99gQSatZf4Sr6ZCsbq_3jxbP_XMviaWfl4Gc17WgkJKE2-YFsvz_zAzmoc_sx4FzlEKQpcU71rxsRr4FKWbwtZ3Vfb0VMU0WFwtfjdImVXjYz4epDIUH6GoKcjU1m_AJm7lZrxr1qwjgOlXrI3KTbEBnIsEzw12wy9_q0msTtddOhF0jOGisk9EoCjCxTKVjAVHjWJrD7uzofsK8ZVvcOKxxLJw12zuNOz6lEhQchtcNx7uP1HsDgmKC3Vjw-VhCVCTWQoVtfGJiSpPxlqZ_yEMJHDM-WfEKrYxkh-TdreN4ORS1qrIczQRaMICIdHji0Dyz3RWhzLsfg9LqAI6LgLjyvRxw65IcrzGHdDVgqC0iCU0o6av-6Kh2E21zgBJe5SmMcXj_DUp4zAZsCLuosULeEVTCwg10aHCI9jQHqC3usbsBTBt_mH0YcyXPx5EtuOrEu8NJ9HXhxQXPrfxb31mXFDQ0a3n3sGNgSiidPkavX5VzM0YW6LrsksY1_7CSQGi52CUQ2YI9QnTEB2fkErM5trdsO3r1tbiBYVNbbYHVcM1RBES1vAZBoUbGP5Y7zDP1CO7_fEFG8dSda_RWSFCQkXrl-TiBa8CAy-ZtvsD0b4Iph0QvyFvrGS7OYCjOCprFeD-Fw1hRq31MzzsbKv8bVVDvK4Mdgky7kQIAnIon_s9QkCN5tD13A==", "id": "rs_0498f8304a1cb86c016a033f0ed11881919014baf4d80339bb", "summary": [] } ] }, { "role": "tool", "content": "[skill_view] name=health-data-management (12,778 chars)", "tool_call_id": "call_FkCkOe1acVNOYbgHNKbx62BD" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_jCvJwTsE4woZkOUd68VDjdfS", "call_id": "call_jCvJwTsE4woZkOUd68VDjdfS", "response_item_id": "fc_0da9d9fd36b8cfac016a033f16918481918434bfa3ec2202e3", "type": "function", "function": { "name": "todo", "arguments": "{\"todos\": [{\"id\": \"d1\", \"content\": \"Dashboard-Renderingfehler reproduzieren und Ursache finden\", \"status\": \"in_progress\"}, {\"id\": \"d2\", \"content\": \"DB-Schema für Dokument-Weblinks, Event-Zeiträume und Nutrition Features erweitern\", \"status\": \"pending\"}, {\"id\": \"d3\", \"content\": \"Dashboard v3 mit stabilen Chart-Linien, Referenzbändern, Event-Zeiträumen und Nutrition-Insights umsetzen\", \"status\": \"pending\"}, {\"id\": \"d4\", \"content\": \"Dashboard und Skripte verifizieren, Cron-Kompatibilität sicherstellen\", \"status\": \"pending\"}, {\"id\": \"d5\", \"content\": \"Skill/Dokumentation aktualisieren und Ergebnis melden\", \"status\": \"pending\"}]}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[todo] updated task list", "tool_call_id": "call_jCvJwTsE4woZkOUd68VDjdfS" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_IGdxsHF4S9x1apv8BHh2K8Bp", "call_id": "call_IGdxsHF4S9x1apv8BHh2K8Bp", "response_item_id": "fc_0a820c45291a9a1f016a033f21860881919311548fe494e486", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"file:///home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[browser_navigate] file:///home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html (8,910 chars)", "tool_call_id": "call_IGdxsHF4S9x1apv8BHh2K8Bp" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_M1EoUFp08BZXuyrHEEHk16QC", "call_id": "call_M1EoUFp08BZXuyrHEEHk16QC", "response_item_id": "fc_067d130dd3ee9a8e016a033f2921948191a12b2055ac67aca1", "type": "function", "function": { "name": "browser_console", "arguments": "{\"clear\":false}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[Duplicate tool output — same content as a more recent call]", "tool_call_id": "call_M1EoUFp08BZXuyrHEEHk16QC" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_AcLJR1e5pIvHgKmTAxsjMhZP", "call_id": "call_AcLJR1e5pIvHgKmTAxsjMhZP", "response_item_id": "fc_0d7cba60c5149687016a033f2f22f48191886f27de285945d9", "type": "function", "function": { "name": "browser_console", "arguments": "{\"expression\":\"Array.from(document.querySelectorAll('canvas')).map(c=>({id:c.id,w:c.width,h:c.height,style:getComputedStyle(c).display, parent:c.parentElement?.innerText.slice(0,80)}))\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Inspecting console issues**\n\nI need to take a look at the console details, perhaps using eval. There seems to be a chart issue, possibly related to annotation registration. I'll inspect any errors that may show up in the window. Using the browser console expression should help me figure this out. It’s a little tricky, but I’ll get to the bottom of it! Let’s try to resolve these issues step by step.", "reasoning_content": "**Inspecting console issues**\n\nI need to take a look at the console details, perhaps using eval. There seems to be a chart issue, possibly related to annotation registration. I'll inspect any errors that may show up in the window. Using the browser console expression should help me figure this out. It’s a little tricky, but I’ll get to the bottom of it! Let’s try to resolve these issues step by step.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAz8vrMPDpJjUnoOdXgYk9ps_0M0QIoMwAskqRCn-PgBhKCl7ObjaACX0TcX3zsjqIEroDnUhfRSExxu9hxD3Be4owCvg8BsLdRPiJtEFAShwgFe4sEDh7-SVy-aIje7wHQ2iacyMiH7_iS2e2KOWY3LJaaszKIcv6MZce939G9pS00Hr8y4E7Swgi69x7L2v4VBCJjFXlasECvxaneFrasLJaN6fNzKaDKmS8hmnH_hF4nFEdMr_QHckmlfNTaIMg_gNkNgtC8iXlJC0lOCDvT_ZDReBtd0n7tineHLhATj-ISAIKfCEuFwy_RIRYprwPhLEuHnqWCT4dso5tsVibYuYPee5TIZy1B9KOwnJTybojV22LX5kyRbQYUt-6xtJuFs06GwhtHmOVKMgDmGJhXaXdUIbjlA2f2roUp1iXEv8EoVD1wa-yOVT3zbw2PGfqW3p9diwh0sCWVPNJDdAHKb4ZBdZI2ap8bIjYW--Jx64LT3tBnqOBry2RrzS4L7z2pmFoFhNbcMC12pcBrQNN0592KDMe7umKrxjbH3oj5DMuFbqMxanrvlQF2tnU755eV0MvLPfsYY_cSAVRcMuEduUKPTXiuTqx-LiJKGV-XJYG3jHbOkFDws_R8atM54-vuhn4wfCSOB8FrEj7r1Ugg8sKiKXRER78xAPaSNJ7hl7yRiJMIi9SEsUwsAOnfRcSsRvRd9fKa9AameqND-hUovYiVxE8VYBccHrQSidtP0Lir3jbmQ8Vjv5NqXaJ8SKqW4JAQW5yVCz6WnJNDR_XrhkHiXGCIMUxWgYWpD0lVayOf6k711-dBhTdKvw-Y3zzRCn-szRnHQVQG-Kc9IVKjlc5A1AdzNYns9xq1cNRcQ63KqVFygE3RHppJ8g6cIJeJ8SipV217E36lz6C3C4vjXJ_OY-rwuivDdyn6NEykVi21rpV4ujOvshc4eN9n8HTB1NinBWNfJ0_AcvyM64sQnISD3OxshHH-_luL6pIvVW5utwC-xPWz0ztfyHbpm92BdTVuoZc1wqN_8vvQ17q0Cdfm3okQ7h-nrKwPsq8Kysr7KCGIjPm2BnEUBv1Osbq5F8E9j7kbMxktKFILZpXuUtug==", "id": "rs_0d7cba60c5149687016a033f2c6fac8191a39f6d3c0ca4e79e", "summary": [ { "type": "summary_text", "text": "**Inspecting console issues**\n\nI need to take a look at the console details, perhaps using eval. There seems to be a chart issue, possibly related to annotation registration. I'll inspect any errors that may show up in the window. Using the browser console expression should help me figure this out. It’s a little tricky, but I’ll get to the bottom of it! Let’s try to resolve these issues step by step." } ] } ] }, { "role": "tool", "content": "[browser_console] expression=Array.from(document.querySelectorAll('ca (1,464 chars result)", "tool_call_id": "call_AcLJR1e5pIvHgKmTAxsjMhZP" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_i35jugOKIoR57Ni7tq1MmSBr", "call_id": "call_i35jugOKIoR57Ni7tq1MmSBr", "response_item_id": "fc_020bac9d005cdabf016a033f3875d48191bf9cbc88ed74ff9e", "type": "function", "function": { "name": "browser_console", "arguments": "{\"expression\":\"({Chart: typeof Chart, Annotation: typeof ChartAnnotation, version: Chart?.version, chartInstances: Object.keys(Chart.instances||{}).length})\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Troubleshooting chart issues**\n\nI ran into a problem with the chart failing and need to capture more details since window.onerror isn't available. It looks like the annotation plugin may not be registered properly. I’m curious if Chart.js v4 needs registered scales, or if there's an issue with the label rotation. Also, I wonder about the xMin with the category scale — it uses values instead of indices. I might need to evaluate the makeLabChart manually for better insights.", "reasoning_content": "**Troubleshooting chart issues**\n\nI ran into a problem with the chart failing and need to capture more details since window.onerror isn't available. It looks like the annotation plugin may not be registered properly. I’m curious if Chart.js v4 needs registered scales, or if there's an issue with the label rotation. Also, I wonder about the xMin with the category scale — it uses values instead of indices. I might need to evaluate the makeLabChart manually for better insights.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAz84xdC2vFqNEKglqsZFDpCu-l7oUymQFJ8HUiMZNCWQKCXCiGiuEt8B5r4dRhQ0RdXFU7xFNZcO9fjCo3wz5ZwJZgRL_rAoS21crPNoWmUNvHqgaJmCVYG9Ai75VBYu7AUBTwkhgiebu_ilEy6nUz7jA458YI4l_8_ZZ8VMnYzhO8m-XuYMPw7tQVvjXrmeSPcwRYQxrINoV57oIounXz2CZNGpxvDxkktibEYlm28nu9tgz7hweH_aoikh_rVmddUtgTniNF2sL3SL2Y70-ZbK_Qj_sBAuZgxCr9eYHOhRTTsnQ2itjOOA0fMCnOdLhi-S4syYZCK-PJ50_Q8hXAnjx0LBsv0-5CWsBXC5eqmasSvaK0TSTHaNr2Yv22nkwVAKAOnaK1B99D2v21p0F8j1_T6Z6c2M1hbNm_3ZIEftd8joyUxf1CeDK7k3Ir8y5uV-SphEijvjjloPovEr37blSHoZnGqmOwzKgAOkMW10L4H3c8uLj_vtTzqoS3PzG6JMWz-YJzem7O5zDSbAoNGslO1LrPLMj5oaMHnnMbDoqqxA_sI_iK_0hYoHS8gMsgL4P2m64p44zgv4clx25KvH_e3RbhYYQQndGZkjJhTY7v3Hjfc6G9__HDeVll_odtogAnuLZnvhoDJhPovk0ob6ysMotqojv-4927nKF1njvrSW3EcVNuzAMrEH5ojpP_cNFB9F_8KkDHYuAyCuEWTWYoNgrPJHFjZoF0W_1yihnZvZX1iqUMJSxnIaLVonQnTSHnSCjmtUWMAAM2vD31Z3YupDgSbt8NGuX9BXs2qj4xvKJCqL62dsHLfOiTOq40Zs3dJ4ems7GmohqzNz4nr7TKUxNOziVXZ7MkabVjEh2t3gAiKOOxS27TIL3K1vVq6aUJkjYyr9HC64UKhm9i8Wjkwrkgd9S168bQyoISRcpcwtSphQ_WtI_99bbNfC-w59dcoLbDUXdcziNvfJI6hiq1F1-pnvfg6Sr53CinmKjFWHwjUmRkPnHIh5ML0SwAWwaS-5kkJ_J467V7dIT6bSz5zCyXV5bnTAV_S0egBaLrM_ETVHrOqSGkyt9MLgEJ2fxzBxEndVicY3weWDbzEcODQvawZO2GolUNyOyUNK-NZVHC-y137yx4YbO18AAGJqr1aiUoFWnDvZHuJtcox9leBo5ImCdlu2ABUTEZLDzXFLa30o5qNUMKRTIgv07-FxWGDTvll_4QcVh4WdJyJsEW5lUrwN-jYZKjXknw2ED-vxthxWDzHc9alJDSXsNrIBObmff9FTOA60k_OpyGG-q-9rY0n7Vjh2fx-5gbRWmb5jVAF7GgXUAP5rBcaiyQ0fcf_t7sPLh92PdHL4wVrW6awT6A_H4uSCXKbXtRR6Sd6mV1HBlNNND9J8IV5SktVL5u7Ak_LXU6qeAJHg0zHI5sUgHko7X9cEL87ZsPHpNTxTADwh790vwaDQUsVq7pno4DiaqRdw_WV50tOK7Uz5yGaIRDpozSanNRjnun8LJeVzotrXjtJIglVuH9uqs4Ov01ZLZC20IGB6xBNNVbx2vVVeK-l58hVq2RtkeeV2PLaPPbZMxsAF09dXEyMzHlXvMgWJVC_DCbhW-Nk02qmqyZluYUm9warZO8zCd06ggwhyvmkv4W_08dVqb-cf_GEB_F433hpYinw40ShQ_sl4juQKsR5gwQ4kV5-o4voAfPA=", "id": "rs_020bac9d005cdabf016a033f32a9ec8191a8d6cf1d78460e4b", "summary": [ { "type": "summary_text", "text": "**Troubleshooting chart issues**\n\nI ran into a problem with the chart failing and need to capture more details since window.onerror isn't available. It looks like the annotation plugin may not be registered properly. I’m curious if Chart.js v4 needs registered scales, or if there's an issue with the label rotation. Also, I wonder about the xMin with the category scale — it uses values instead of indices. I might need to evaluate the makeLabChart manually for better insights." } ] } ] }, { "role": "tool", "content": "{\"success\": true, \"result\": {\"Annotation\": \"undefined\", \"Chart\": \"function\", \"chartInstances\": 0, \"version\": \"4.5.1\"}, \"result_type\": \"dict\"}", "tool_call_id": "call_i35jugOKIoR57Ni7tq1MmSBr" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_5S1la05RwkTrGjuotBrb63dh", "call_id": "call_5S1la05RwkTrGjuotBrb63dh", "response_item_id": "fc_0f64942030ef5826016a033f3c8ad881918d866a677d02aafb", "type": "function", "function": { "name": "browser_console", "arguments": "{\"expression\":\"try { new Chart(document.getElementById('C_Reaktives_Protein_CRP_'), {type:'line', data:{labels:['a','b'], datasets:[{data:[1,2]}]}}); 'ok'} catch(e) { e.name+': '+e.message+' '+e.stack }\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAz88PduptrXun2Hn7ZRfPs-gFSBb-53GTxujgf4Up8g0beHpb2cTCRMY5Ik_rb-Hj4Bf2FxLkNlw9t1cMj7zvindXvgrXgXqLy99hruqE6LySv3m5IcbKWg23V1RyVhRWRvp1oayzt0qyiBp-yytuHRMgNTbPBVDleW_-i__MQGl-6WXKnZRnpsSGn5HrzvJEhJ5-y2TWVhRpfcEdPXEWFfICwNx-sTkrAO5L9lBMBRNSIkzUXpP3-4g9FkKrfRXj7SrncR14X3x-aCGxs5aAPsohM7-2bf4DPyz8YupuM3rBN9OMgVVw-67KQRYwhDYPL3P6T1dKIxqUAa5_Z4SUL5pWeworkzF1nMEU_4EGfvwmSdi8aBhgPC7T1PlHD3Ntjj_3ZrYTGKOtYjKsmoJvLOGrxYH8SxcSQ_YvoUARjX2XkdLTaRGUwMWwnS-ZVIebtFMbDLdj_w-3pUjoL0PYhCnUDtRZqih-PNFcWFhss-oIN59ZK2lWezrVOVKcHo3e19T59G_-RDP0TTIQMuBAwwSHdBSO3MHySuxMhQUgw6wIddLgOhJGz59lEqa-SZUsWJfD-mrSdQi8Pu2MrjNYi0wvl-_lnrkNH_aL7tklOTQGkQnYjvKiuka02J4MFuyxP92JIO73kKNBkAJMmgMgAj_5PQ79acSX2niVFAGIrV9cv5kceonB5x-fQ7Xwgn7v5Mo1Des4ICuAoH5rYb6xVv6R2PhV5nvJtzIczvl9mhBa5f5a6Y7SyXAM71Icj9oz8seWSIOGCy-7yVflq0_JlILAFz1QTrG63oz90D02GzGzDwz85uP0nHEaa-xo43O0QH37pVLubnSGpY7V8_id5HnIWw2RrDT9sIdLWvfImUPTwU9Hkk_TbJ1F41a4LPT-KNVVS2cAQiKnvqKwleJogOUHSrSTr6LI4jP0fIP01kQmlr97EyzeVhu7l820-PZ2x_5ca7BqLTW9AiDlROKKSbvJHIh_meRmIVcKQIiDoJTLJ9mYS5S4wWx7QDa8X9WS-OqjLvNc0g3lFCaehdKKCDNcN0juhhTVtiNnKaIXcR7RcE=", "id": "rs_0f64942030ef5826016a033f3b11508191a682b61be76b376e", "summary": [] } ] }, { "role": "tool", "content": "{\"success\": true, \"result\": \"ok\", \"result_type\": \"str\"}", "tool_call_id": "call_5S1la05RwkTrGjuotBrb63dh" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_GxcJ70727mlzfKWrRBWLQSrO", "call_id": "call_GxcJ70727mlzfKWrRBWLQSrO", "response_item_id": "fc_05db1da385df294c016a033f5584248191ab0284bed85358c8", "type": "function", "function": { "name": "write_file", "arguments": "{\"path\": \"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3_migrate.py\", \"content\": \"#!/usr/bin/env python3\\n\\\"\\\"\\\"Schema migration for JARVIS Health Dashboard v3.\\n\\nAdds:\\n- stable original-document linking fields\\n- period-based health events for Aphthen/Schübe/medication phases\\n- daily nu...[truncated]\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Improving chart functionality**\n\nIt looks like I've run into a problem where the function failed due to an annotation option. The basic setup works, but I need to create a more robust solution by removing the plugin dependency and implementing references as datasets. For the chart, I could use Chart.js and include additional datasets for min/max lines. \n\nFor event markers, I can add a separate scatter dataset. I might also need to rewrite the functions and consider how to extend the dashboard without plugins. Overall, I want to keep it functional but not overly complicated!\n**Planning database implementation**\n\nI need to implement proposals regarding the schema fields and tables, specifically for nutrition_daily_features and dashboard v3. I’ll start by creating a migration script patch to remove the annotation plugin from the dashboard and update the JavaScript.\n\nThe current function can be patched easily by removing the annotation script and changing makeLabChart to handle rmin/rmax and events using datasets. For the line chart, I'll make sure to add scatter datasets for event points, and also incorporate a table for event periods and nutrition features. I’m considering how to generate the computed nutrition_daily_features from nutrition_by_day in the database. Let's get started!\n**Updating the dashboard**\n\nI need to patch the dashboard to include period queries and insert nutrition features. To simplify this, I can update the nutrition features directly within the dashboard using an INSERT OR REPLACE command. First, I’ll make sure the necessary table exists, and I'll include that in the migration process.\n\nAdditionally, I need to fix the JavaScript code to accommodate these changes. This patch should streamline the overall functionality, so I’ll focus on getting it done effectively.", "reasoning_content": "**Improving chart functionality**\n\nIt looks like I've run into a problem where the function failed due to an annotation option. The basic setup works, but I need to create a more robust solution by removing the plugin dependency and implementing references as datasets. For the chart, I could use Chart.js and include additional datasets for min/max lines. \n\nFor event markers, I can add a separate scatter dataset. I might also need to rewrite the functions and consider how to extend the dashboard without plugins. Overall, I want to keep it functional but not overly complicated!\n**Planning database implementation**\n\nI need to implement proposals regarding the schema fields and tables, specifically for nutrition_daily_features and dashboard v3. I’ll start by creating a migration script patch to remove the annotation plugin from the dashboard and update the JavaScript.\n\nThe current function can be patched easily by removing the annotation script and changing makeLabChart to handle rmin/rmax and events using datasets. For the line chart, I'll make sure to add scatter datasets for event points, and also incorporate a table for event periods and nutrition features. I’m considering how to generate the computed nutrition_daily_features from nutrition_by_day in the database. Let's get started!\n**Updating the dashboard**\n\nI need to patch the dashboard to include period queries and insert nutrition features. To simplify this, I can update the nutrition features directly within the dashboard using an INSERT OR REPLACE command. First, I’ll make sure the necessary table exists, and I'll include that in the migration process.\n\nAdditionally, I need to fix the JavaScript code to accommodate these changes. This patch should streamline the overall functionality, so I’ll focus on getting it done effectively.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqAz9VF3emLuQCg5vx4pwBvtFQgmaKbUXyhP1KkiNtJvWmu8ITU0TPDSFnkMaThvsplmybrvb4gVfyFrDXF-cAKc0rB5Ft5xRNMT-ZWSbflTJiHnwaP_wv4GpkdmggAaoG-TXWUZcIdWDn4qzL3o4r_jrhVPZgmZMaQdALg53zcaqlnJ26j-nYivIJ7_J80NuY8cd2hZxpgx6FQSDNdzk2Yca9DbWKRtXebnxTv46KGJGLNybPvDPO0JObnOHDMnImWkRn0Xf3M-JAcXdskSj9Xqw4iSsoxB98DRtqhM0i1Ync0WR1VKUS_F0PQTG32Khin_-2Ut_eUXNR8NQs53CBsSXgPvebmExZR_VPacBMK9Sk1vhfkBcQhe56AvUTmzu7b1G3Z6X5dzS5zxkU5Jn-XiB2n5fY1glY2PdlDA0TB73398nCAiC3D8dvLkS1AsuDw0MskjqsfwxthiWIGO4BBS7DqReSJfVVMo2xztJDrpn9Nu7xtX1OhoEBYPWRuyFNaTYgjtv93nGtvsVYcA2G7LrV3WuBs4-toJbFc18Kbc9KeDXMeufUHmdX_3sFI_NK1i-GdKv_t3vG0fSsbaCle1ZBU--35IF6NJeokLgP_OKCjdJMMu_dN6ofVgYeI7PFlybipShED53GvmXRD9f1IGFAegrALJBYwZzzrQO-jjHzcW1YCgkv0DoI9OdqrBFHU9nFUaxbwiYw9KMPUN2wTp_AXhmMDuPNJfrT-LRxzNKq3WlmuXF3XvkHxqeczjiW654bbEiAQY8apU9emTPIXLdGkH4Hiu0BggMjlGgRTyGSU0nhdR37oqjwukh93iM4pWUPE4WxaCi68782ww0aLQbA6sDGtXNZ8qw84GAfcPkuuy22yLHsyZ5lv7NDsGn8mIbYE-w_-1CQi8uIBMWkSE4SkJ1WlC4ezSi2mOvba-jQ9rDiqd5txgkbrLgOoiP8s163dgq3LJPhjrTv4j_MddF6_sle3QiixD5U96tPpfiTW_4fMX5Ol1X2sDv4K2lsXBoH6SBPEyuoRi-dnRoox_mJRmok0h41OqXkLzB75T638qMqHibJIlZN6MLEHn869b2GN0ipOavQfYY7QClSyOO3yiHfFFLLyk9vI-m13R6cR05QJgRwUY8rhT3X5qP4EmdsRzJ38dL_fpzbcqO8eFB2FMfXKI1zHIo28rwztuqE0RufnvTnub7FGudxJKmDaaq07PdafbwYZ_d7PCv_4tDnRoULnBNG8DZseluyXd064Jfy8xJXlcokbGOYft9r8hbrR2iVHRwl-6TNsHkHXXWpgXtII8I-oSY8ShsNDxwKW1qlpIQb5VsD0sSsXVY-z6RkXGr5kovr5hBgoHwwGdUJ-jIYGLht8HqYr6plglfrdStGwSZa0d5x6fbJWvcjjErgOLDLIwrkFiQZMJJWpnlS0mNiwQym9Njuf8HiDi4hPKmKMXX-Utgv1uhKA1Z85oGEnkYTN5Bcrdi_Ih0zlaNdk2arC0ZCzWRz0HRekdDzm_63LcFiNvK4J9jje5eThTsfjnPoCm1gtQ3JMSRReHBSbKytcdcYRX8KhzmSn9oe_w93Scsci0DdxMHAZWsfOcrNQ1cbF8_XeV8yOZE6_Dv-b6hfjJtsTNfF-3pOaeY4iMJeZKN2raoR5_pPst_HC3QF0pWeMfY41u1zGtd-F3xq-CytIubg1bmmOePLBxTNBFcOrA2y8RY5N9Tt--cD4DeQmS1ZdqmO9WCVtszYeonthjg-OcRIN3Wis3rk0AZ94xJCPQw2hrfBy5UzTgL8angc-xSO9haFI4f-rhC7jfCc6Pirz0YmqvMuTe6WAcNEVlmp5tM4q9MQC-D0hzjJOHgLTIM56YO6C8DzsfajoVhKZaKmmmW8_4DhA-Bp3KwMuPjwIFgqTO5JW0cKPSvvL0BnWfzPz9rlJrrW7hQBatPLcMzo4RcL_-HI9uZrFHKgMFzsxiacqEAPhT_i0SDnTtMEOOkqqGhX69_xkyGhGIq0VYkDMHqXmXE4FfSSfCgPNrRImYAkQbnTQZlBStIaJL8f95DxUdkY02aeaL8ffiP5YFpRGePoTKLnprFuGWI2FR5CMfppv8FpRuTcsB9D1BCSUnQSw7kRCtQZwCdR-ASXmqqI_ejeB5IZvBOnkdlQ0vOHj3cTwPFsXLpLTAEWczp7JXMWIxYBpL9GSoN9VRRdelbm2PgqO3AU5laYMGem4Hi6CMgNqbKSgRDa9rFdyOrECAmDJnLLq9ZZ3Oljw8C-EjN2HLWZicacjcpq8MridsIiDC-AKhNSCd9k_EKGWydtZQBlmHFRHihwnHptoN5WFpwJZEcEd4j-dLS5viwmH3jNmmGipQWYq-fAh1ZVUMxP7vFtBfc6BrUo8Y0BgH7bYH4h8Fw3-JzWpwpnO9LB42CduH4zDz6i8gCfZBRfuUh-NUk_joYly9Wd4-WLvXLJHCEnqUzI2f8Q7wU4ZAIeB2mG2P7i9FUxqpIOEX4E9hYuptRFnycok2puNApAnh6qXkgzxZTXmaSfqbl_7nWVSWGU2ZuSLcMKuSUKC44Bsa0aI0190UHgJLvKSUcS0dlRSc7MXXe3iAa_8gsDGgtKbB7Snb74KGF7nEr2BeGld7adDcqyBeegGtPSC91Wi2THMuw0iFJyn2geLm3qWxo5-IxeevnL61qU7WkPIcnqkoBWJaTsBihBJJKCv9LCqbnnSDifHAYzFubv3Sba1KWnanCaMYb_L6TG-2a-7evO_E2saKepFSphqpbfaOAPT6eFujFF_uAHPJQUTCUy2OqE0_LqOyNfNKHhmy5caoTUmOO_vxtlZ9vkhLAZ9mrAJnM1EbNZkGgCspVqV0eIUao7uMI-7Cc7SY31ZMSv7MJsNnC3YsLLNrS2ZjYA6NrhcgD73JY7hwMiwXtfGvq-KENsdouSKQFBzsKxBPO7lZElsA6wPqtnYeTYPjjxbIvfq2NxJpXwrskmW9nDi_N7fkOqYqeogCW62WJNmLVIMmRaZOW2rXBndCsOovVdAOesieQhGuxgnOW4nWSj7ti928mqDPTlxPq1tjynrqd-gXQjXwQjYatw1DBODH84_CjD6Oyd_eMxGtubjw8wG-lsd_mwunpgXj8vHdHOSwHk1EW6WarmBgLrDxEDpPcU7fKauLSxKiHtLaPKMvAxiFQAqQAjH-3T1C02Im9eIzq1RwSqum7WRjaEvxuOi8nEC_2kJVazNy-OaXPzZbU-0cj4v0LvptfGXD8o-O5piXmI1VUex8TCo1vfsuY0d4M4HEL6df2SBqxWtZb4JBoGBOU1hciiSe7f0URDDSPb0BVCL1XYxsjbpXA-U2XDngDh_xiutez1yNpxvSMys4IOsQkUgsbsuUyrkojpv2JmMe8UAYUpYjgDcywF4pm_z5fFdnzZ2pHXQi8tbSNlH25ipFhECsjjI6OLPhfvc63ZoC_obIlrZLBwc9h-2ZHe_9rxKffEWlS_jS-xGNJztPxfplud4P7_lqK8IdZJDwaU5KTj-1KPby-JzyWn0g-_ZByZFqtra4llJpz7vaVRtk_KXVaTqbAU2tWjuuJ81Vmvwh-haZP87pLAxLN6B4OT2yOAt-YFstSP6S-XwMDpd4yqIZcq97WyChPkj6GO2iYzZXlHTuemdEMYvgjRBoH2fDE_mn13MpTbUf9VesxqYR9UtvUdz9ohtMIRcuHoTJWOwdCBxdSDlf8lPbHpgEIQ-kWWKYPwXDLAEOB70iJ_iKA99oumLthjM0DqeY4cgqltTQO4DBNSxNOmkNBCR85vD-nOJTxygxneBNPLld-D_48UNeUyF-D8TgcHPwU6rgq60UZVFEO4mRDCC6IR5ez_i2mOAVSmHhJolPg3ORoa7YHmIVZglaeSvdcyOK8w7COxqlWFXei4NbVjIMn9pcbus4Ap0LFqj9u8Ig==", "id": "rs_05db1da385df294c016a033f429a5081919a963536ff2aa35b", "summary": [ { "type": "summary_text", "text": "**Improving chart functionality**\n\nIt looks like I've run into a problem where the function failed due to an annotation option. The basic setup works, but I need to create a more robust solution by removing the plugin dependency and implementing references as datasets. For the chart, I could use Chart.js and include additional datasets for min/max lines. \n\nFor event markers, I can add a separate scatter dataset. I might also need to rewrite the functions and consider how to extend the dashboard without plugins. Overall, I want to keep it functional but not overly complicated!" }, { "type": "summary_text", "text": "**Planning database implementation**\n\nI need to implement proposals regarding the schema fields and tables, specifically for nutrition_daily_features and dashboard v3. I’ll start by creating a migration script patch to remove the annotation plugin from the dashboard and update the JavaScript.\n\nThe current function can be patched easily by removing the annotation script and changing makeLabChart to handle rmin/rmax and events using datasets. For the line chart, I'll make sure to add scatter datasets for event points, and also incorporate a table for event periods and nutrition features. I’m considering how to generate the computed nutrition_daily_features from nutrition_by_day in the database. Let's get started!" }, { "type": "summary_text", "text": "**Updating the dashboard**\n\nI need to patch the dashboard to include period queries and insert nutrition features. To simplify this, I can update the nutrition features directly within the dashboard using an INSERT OR REPLACE command. First, I’ll make sure the necessary table exists, and I'll include that in the migration process.\n\nAdditionally, I need to fix the JavaScript code to accommodate these changes. This patch should streamline the overall functionality, so I’ll focus on getting it done effectively." } ] } ] }, { "role": "tool", "content": "{\"bytes_written\": 3223, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_GxcJ70727mlzfKWrRBWLQSrO" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_OXnWgp3FpxRlbwjrU1omwciI", "call_id": "call_OXnWgp3FpxRlbwjrU1omwciI", "response_item_id": "fc_0fa7d54e3df363d8016a033f7662f88191a3c5cc6e911892d3", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"python3 /home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3_migrate.py && python3 - <<'PY'\\nimport sqlite3, os\\ncon=sqlite3.connect(os.path.expanduser('~/.hermes/assets/Gesundheit/health_d...[truncated]\", \"timeout\": 120}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `python3 /home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3_mig...` -> exit 0, 1 lines output", "tool_call_id": "call_OXnWgp3FpxRlbwjrU1omwciI" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_p1N71bwUMhw4rJA0ozcPGir0", "call_id": "call_p1N71bwUMhw4rJA0ozcPGir0", "response_item_id": "fc_01c7693549b28dd1016a033f7f43f48191aaa9161572b2691f", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Dashboard-Renderingfehler reproduzieren und Ursache finden\",\"id\":\"d1\",\"status\":\"completed\"},{\"content\":\"DB-Schema für Dokument-Weblinks, Event-Zeiträume und Nutrition Features erweitern\",\"id\":\"d2\",\"status\":\"completed\"},{\"content\":\"Dashboard v3 mit stabilen Chart-Linien, Referenzbändern, Event-Zeiträumen und Nutrition-Insights umsetzen\",\"id\":\"d3\",\"status\":\"in_progress\"}]}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[todo] updated task list", "tool_call_id": "call_p1N71bwUMhw4rJA0ozcPGir0" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_WivIKUxiM9NmB6zm6otRzw2m", "call_id": "call_WivIKUxiM9NmB6zm6otRzw2m", "response_item_id": "fc_0c84274a14004211016a0340446c2c8191b43bca94f74ed6a0", "type": "function", "function": { "name": "write_file", "arguments": "{\"content\": \"#!/usr/bin/env python3\\n\\\"\\\"\\\"JARVIS Health Dashboard v3.\\n\\nRobust Chart.js dashboard without annotation-plugin dependency:\\n- line charts render with ordinary Chart.js datasets only\\n- reference ranges as f...[truncated]\", \"path\": \"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Creating health dashboard**\n\nI’m working on the cron command to run `python health_pipeline.py dashboard`, and it seems like I can return to `health_dashboard_v3`. That’s good! I need to create an import in v3 from the health pipeline to parse the reference xlsx file when it runs. It won’t call `generate_dashboard`, so I’ll focus on generating robust JavaScript without annotations and computing nutrition features using SQLite. Time to get writing!", "reasoning_content": "**Creating health dashboard**\n\nI’m working on the cron command to run `python health_pipeline.py dashboard`, and it seems like I can return to `health_dashboard_v3`. That’s good! I need to create an import in v3 from the health pipeline to parse the reference xlsx file when it runs. It won’t call `generate_dashboard`, so I’ll focus on generating robust JavaScript without annotations and computing nutrition features using SQLite. Time to get writing!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA0BEoj6Gbrzrt7ptC16_F4pxuzcsOq3K29rhFbdmESObj7E2Ek80BVYUY-8dzr2uo8XawYKGehJ3_PhPwRJxMmXLnkpOBvn_sWfGAChqpPfyLZ-kxCqtk7YVjIexG81gJJ8QPo2wPoZ_VAEBweIY5bJ-362yol7p8XK8TftGqzpwKIzBzmNcJZmqCnL9U2BklbsC-BLJVPdYHIQ1MiCcuwVW0gGpulzSkh2PrMOP0k9cjpnMaSXP73ONOxhuwnGQ0vj3IPTm07oa7bEghgFD0B0jBVG3KKkXCSH0-zY5hIIww55MWTuTMBHn_Iiv3E3CoAFnPl9RCeMGoCs82fkeEJTSI5SxtJB6tlnBJuLxa_jIBxmU4GBeQ0QdSK72CqPQfk3Ce9HgqXA1axavtFcmDd4GUeFvUdQ0e6aRGxtQbOAB2-IV_2h3K0K7EogdSpsZk_51LXeYKAwSVP0cHkBimHhmCHysNWO2RZVdQ9Vl7x58Xu4JvncfsXzHTwcPLgdp6YeARMO8xutZjWw1rfaNHKMVVmOsE4ObfhNLwonxZIfHbu_O_kestJ81Sur2O2Jhqp3mm3HHne4kdZ3NhJulWhnBtEGtTmhQm5-6R-9RC5h7ZlojFJFPXUSfC93GINVocduckDGGEJ5yuxLZCRV0IxBSNetz6mMV_T3qEFxY9U99_Gk9YhdeGCrpGVhTPmIZcMGtf-5u-J6eaCkR8PUOlNNE9o2prBWRPTr0Oxo6nE4Nfi7TUQon6IT7RQlwFSlvP9194tpAH3iw63bFg1tD5WCj6WmYmVFMVedtkOPCwLfPdnXsMEX68z4_H2NsH4nAxqx_OTvVRUdFaOlfFYVBPkfQi397mLVfuOPbfY4mYE0D-d0flvRTPz13vBcjw_Z3BOpmv734cQSiGmffofdLreGX9wtLKp2U04hCd2OMTlA_Wmb_BqThLzljX2_YZyCnV1opCgI-h7PJWxp1zGuA7FH5JLQVYCzWYXhHVFWpcR5qy6cl7MvOlObGjczDmC60vWKMSz_6re_Ot4klNXLdcapqmA4D4cxXecGtIqihWQba5WeEeJbTPSLcarkISPpwOHj6Av4444pf848giNhCkfJKCLVSd1Jc162xmRXMR1jwMAAnSeUv-f-vPWUgoLYWAiFrajCdlUrqWiUmpxi_Ip5sFWEc69vv4yIvqMN_X1kiJUnxmvrxT8Xp9WL4dlCya939nKD56daRFD4E9vIYsFHlTEkpRbkjsX4CfBmcmHjl7n_nQL_i-_gpBu1FHFjpJgD1LeW727tFLy6LtGIfkUA3cYXx0hlgyITCWoVLE9l-U44pHpdSCpjDp2x9ZyOMWxVOFNajw82fsEL2kT9TabkRUP-KeujRsM7peqSzdKYtv3oC7fzaZA6wjPmo9Wgqth3Pw5A_XG2XghJUCkpoP75dzR1RB22B2xA_UGDgyXGvgbJUDAu_laULv5gdIRk9etd28slfHmmbDerbbSMy_m7v7D8Ue4hhSE05lhSPWOB3j58dvIVHq4Z2UpCJnnaB8k-bucCKqnNQLuAXt8Q92kHlboM0J-Y-OEM7geoAb_yaubr4uPzdEX26a8FeiF8LDIuiD1smA8KtOeQKnngh_71XbIDBgPJKeGiO9WleDFLA8WK7fT4t3BeXWgX2XjZXbA8x3t9uCx4tEBCC_kk0g3lfGUVFXHW5n4xOTTvuCjR79_B74alEYwQ_HRqEOpFldm2YhDdWo7HdjaJGeK3EKsYFw09QdEvJ3XbGaYmJoYFX20OexQLyOscbTGcVZ51qZwADcqgDIFBFl-JBac_vIWANla2U_H3Le0SiaJKCT6mwnPRwF6v4aJXwLLW8QsK2LAqmFJC1p-5-yU391kLzC3Tyc2Iporz566VIgmvbibYomYXTmkUJSDya6kyw3VopFR6opDJwc5lLe53VsKVHN_BUX65fKqfARTgIZoiqy13ty8uHXDjF0yyUUeby1NLuKV89TlHSNBcuaxcsA6TLuJumSmS5p4Bv7VEjPhzpuLHUPIQzj9mrljaHVfBrReUBs2zAyNaUEo0Jm_aglxK51iLz3AQuZtqFZ-hX8BfnAJu4ZG4qPmoKS_-p4YyChJjG05NCclwhPGH9HTL2bSfaGbhVO2e1ssX6QnSyD52T7aYFpXJmLJdKkzbHHbaaYjZzM6xHUUKpKydJly5TblS3yEN0PUU1j0Tv4C4zhAsBuA-LJNXAz4OmbsMX-W-Dk-3f-kIP-KeP0JKbsSLXm5qzvalT56eBiFyDyqq3vrQmr_c0esClF5e4DK74SlR__s_W_UltGT-oH4Th-KafxZ-Zkxi4Y1AUcaKWIO0lxJTXVLBZ1kAfl9EtzcgJDfYvHuy5eG1QRaTXJ1I88btoPvbbRoKgg60PlwfmnlI6XhnxB1PqnKmFCQvEe6eY8PZXvlq4zYp3aauWQZPAFDWty243IEUM3RmS7nEzSzRQfdjP3MpNGC5jPPgJjeksw1HwNz2nNUOjADh7XrghJBPTkozpNFFNqDyazHuD9367IeK_PdUQODAw5pV9uSWBVz23RnCyzAat5e9EiNhsS1DfJOt5mfv2w7qoam6XM29h0GQ5nR6KY6amBh7kwwkkseEo3t0CFR7Zh2gz2hw9kDjKW1hMjUwAcx511z5nI9ulWNny9E1sPk1Tm6DDrnz-7xwcyDQjsXPqsUXsAfEToOFma8AHnf8XPIo5DWFV_dktcJOOB7OPzUgIMEFPTsQkHNq0FaRzmI30v6JPaUYhHzmOtjjak85VGuT83N83cR-HttZ05D1uinGSfJy-c9EC-YkAID4yKVhOPH3HK99mKCejKbWeI_1Dc-FuvGD3xwngxjazjmgXHXcIxy0DZ_60e7thHZQ2n1IYDn_lYktDSdrY_wu7Ev0X68xHW7jFNvravdPORO90NYM=", "id": "rs_0c84274a14004211016a0340386eb8819196feefbde208967f", "summary": [ { "type": "summary_text", "text": "**Creating health dashboard**\n\nI’m working on the cron command to run `python health_pipeline.py dashboard`, and it seems like I can return to `health_dashboard_v3`. That’s good! I need to create an import in v3 from the health pipeline to parse the reference xlsx file when it runs. It won’t call `generate_dashboard`, so I’ll focus on generating robust JavaScript without annotations and computing nutrition features using SQLite. Time to get writing!" } ] } ] }, { "role": "tool", "content": "{\"bytes_written\": 15887, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_WivIKUxiM9NmB6zm6otRzw2m" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_F4D0GuQbWKlTKNQXeogva1ir", "call_id": "call_F4D0GuQbWKlTKNQXeogva1ir", "response_item_id": "fc_096eb666aedde160016a034105b28c8191846a329dd82c722b", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\": \"from hermes_tools import read_file, write_file\\npath='/home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py'\\nr=read_file(path, offset=1, limit=2000)['content']\\nlines=[]\\nfor line in r.splitli...[truncated]\"}" } } ], "finish_reason": "tool_calls", "reasoning": "**Addressing code issues**\n\nI'm noticing a potential issue with the row.get function in SQLite. The code uses hasattr but returns false, which is puzzling. It seems I need to patch the pipeline dashboard wrapper. Maybe I should replace the current generate_dashboard with a new wrapper function? I wonder if I need to exclude the helpers above, or if the existing helpers should stay. My next step is to locate where def generate_dashboard starts, right before daily.", "reasoning_content": "**Addressing code issues**\n\nI'm noticing a potential issue with the row.get function in SQLite. The code uses hasattr but returns false, which is puzzling. It seems I need to patch the pipeline dashboard wrapper. Maybe I should replace the current generate_dashboard with a new wrapper function? I wonder if I need to exclude the helpers above, or if the existing helpers should stay. My next step is to locate where def generate_dashboard starts, right before daily.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA0EFQVsnzJ0T5Nwn0LxJMm7AH1qlBy2uCwO_ACt2ouAmpehm_WAYyGVo59BF27W6uSX_zfQwJBCJ_WmIOvrGOLOgWidiKxqSgVPVJkkHZAGmKzwuLppnElB--esNwxdUegt7cl_TzfWfcVZNK-AgsaAQJWjZASFlNmEML7TqumvkFmCjCzEe7ThlmlkdRkj3gkathSzTXd3NPFo1ZmxF1FjDJEsxXcINYztdVHPUVHf9TdnPMm2LFfd-pTnCuLEguzUG8LlDGnmq0z2vUYWbZ-rUlAshp5gvt-LtWsvzqdVWNL-NKeJuh33Ra9e1HJJqIK1KV2eERQIShPGGx0EOAfAE2hKrDk889jb6dqQMAJzTAfBCyOVytSe1ZYyVhc-0y2ckKS4hyPxKIQtn-JF7fVXkLXY5i-qs5_pO37CV43CvRuz7y1ctLhsRxJt1QBJg06ndliKViyo6kHkv-odUsRwXd7ygL4WTscW8JWRm539LAfEy5zByhyAPgB1EHyffPSQHOL0yUHPVo7wU4UqF5MdcbFlmW39vGRGrwNTKI6Ew6XZxAP7cH-nU53ZJf5ghTghb3OpfPK6_3lEpRhfOluL8xsggUX036r5DQEQjIV7o4U1uvARd4OKHEPaEtNNUt5JhRLTTkNV85fDdoqLU6C_N6EBdb6qhG5-tEL22BJl6xAlvY6h2qljn0uRqUjH8ShkeU0jMhKB-59VF9sUpgQ6wL-Fl5hbUgo3pZLuoSacGUeiMU_hvqPKsi_8ATEpZFPPOb8t72-fT9MtsVY60wp8w0T8zkbwus3LPguITFys74au_PIuIorzOLku5HmBok6Ct1BmyRJx4xN6n7kSjcl5vlsA10UXGmUnal4x5C1Mp3r-avc7p_IX5FYrc8Ll21Nb2UpsB1EGQMge4Lv8qcza3YUJ-vGVz4W9LtMwt8zbZF3r2r7bXrdep-UvYCiYD_x0bYnC-7Gfhhra9RV2IsAC1ESsNuVVu47GP6kUMl6002BLH99cchYQH20RToMhy2vp6hJWjPHU34Y3dodcvXXTcMpb-KapmPVM3Yvo4Afy4e_pIBDvy5M1JZiSavoT9RpPrTjXNUERAxgcb2k4NgEjIetwLXaSRbWnOB1D5WiI447zLU7AHPgMhC1KTGZ8chHtf577tzamyuDaZmN0FW5wtC4CMBlULB_tTB1vmF-idtp02zBbJIxy4sHluTVzVTVq7w7TIWHHvTaDLA4hH6yGp9hoiq9SqwzMtmYXYIlKAhapaSHwW5u__mKOHuvHSZStz1_mAo-1KX2VjPp_jSAVMgWAMeB6QadHJ1o83q1-sgx-65PdQ4zedt_3zEFfjMaEXf2PbrNULlZ-wV11O22J7Fw==", "id": "rs_096eb666aedde160016a034101566081919c9ed837a366982c", "summary": [ { "type": "summary_text", "text": "**Addressing code issues**\n\nI'm noticing a potential issue with the row.get function in SQLite. The code uses hasattr but returns false, which is puzzling. It seems I need to patch the pipeline dashboard wrapper. Maybe I should replace the current generate_dashboard with a new wrapper function? I wonder if I need to exclude the helpers above, or if the existing helpers should stay. My next step is to locate where def generate_dashboard starts, right before daily." } ] } ] }, { "role": "tool", "content": "{\"status\": \"success\", \"output\": \"pipeline dashboard wrapped\\n\", \"tool_calls_made\": 2, \"duration_seconds\": 2.04}", "tool_call_id": "call_F4D0GuQbWKlTKNQXeogva1ir" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_0s6KDcF1ff6Ry6U6AFB7WJSq", "call_id": "call_0s6KDcF1ff6Ry6U6AFB7WJSq", "response_item_id": "fc_04448dea512f60f2016a034117c23c8191be3f2d30ca7b3b06", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\": \"python3 -m py_compile /home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py /home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py && python3 /home/agent/.hermes/assets/Gesund...[truncated]\", \"timeout\": 180}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[terminal] ran `python3 -m py_compile /home/agent/.hermes/assets/Gesundheit/scripts/health_pi...` -> exit 0, 1 lines output", "tool_call_id": "call_0s6KDcF1ff6Ry6U6AFB7WJSq" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_2KkG2eREvwv5zRlUHdoRmp9f", "call_id": "call_2KkG2eREvwv5zRlUHdoRmp9f", "response_item_id": "fc_0d1de1088e98fc94016a034124a49c8191835bd921ff19ddb2", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"file:///home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html\"}" } } ], "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA0EksGVRMD0YDgyfnpQ3vO0jQXyuEpM6UNbsEkPkCU8QZQVqg4wq4Qsw0OLEGeLfdOIYLC4LoaD6IZgaXNQ2Eou2zsy87S4j3lmDgMYIJU8yJJkeBerR9rsSH7DiuG5sk5Pa3Z-p9c5efgRJkX1Yi3azHdA2pOGtRxBVFWnjCUBVY1cUYf0Y9TBzde5QJKvhtoQZ1k8fpbQGCmLCueHjnj3P86HC3jriMqmwpV98kmVYsBVaMJedC0GBC3ciH6r8Bu1LwDDKypwNGebU4HfdbjGCTgHSyCXNDCV2or2plIiJxrA7fR2Mm0aCDjx5IXqfR23T-VnAEX6NPv7o2kAbf6z-gD3EsHZHpsyBE1F-52B9e2p8NfGZKFWwCs2X9D0YcmA7V9QM8wjp39LtGxmhtmHHpORMicXI4J8pmrELLC8q2mqaAAlKfKIDTwsAL3UP3_GcEeroaOj_mrgOCSTdWcunCx_z2k1MCwX2caDy-0HuDB6NYCIHEiFyjbeLbi0QxOhKiJfA9Wxkuy0EPZr2435Z_iPvFolMiQld_lr07LjXvW4bi91iSORtEDQrp_DIj74DOw1WRVYf0213e5R6S_b-p2WQCll6bN5EEWA65qpCOSNqdTuNJRLT_Z43xJgE6o2UDOFr71GmHg91HyLj3lC8LG1ilOhgc2CDRvKNA7hZ31NSNGo8q7ve_VdvQG9BbwWLgCmBIBCCKD7tXYDBng6iYCC8iYbmCL5FIzvFahrnCe4rymhE1bSD2GTDnOYV_FVZqV-L6-hgKx8OjwSbWyzE7Nq5GGKR3NBRN5ItCz4BlmyPF3mPu0YlGj3BSOy1Rh74m5R6rsIED-M99e-84hzj90Z5iCxn3A6MFjxh3qeUDrOqfUabyMQlGcfMM38LG9-109gyPyX34LqouUOVCgpk6YSpKejpHeHAmJA4yPnISRRctfNOQTZLtc6dHFqlfhZG", "id": "rs_0d1de1088e98fc94016a034123a16c8191b32b2fddf3890100", "summary": [] } ] }, { "role": "tool", "content": "[browser_navigate] file:///home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html (8,778 chars)", "tool_call_id": "call_2KkG2eREvwv5zRlUHdoRmp9f" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_lLov7TZmX3XJwRZCyGLINN58", "call_id": "call_lLov7TZmX3XJwRZCyGLINN58", "response_item_id": "fc_09f84ff6c0724461016a03412b3c6c81918aa69891926e4e40", "type": "function", "function": { "name": "browser_console", "arguments": "{\"clear\":false,\"expression\":\"({errors: performance.getEntriesByType('resource').filter(r=>r.name.includes('chart')).map(r=>({name:r.name,dur:r.duration})), charts: Object.keys(Chart.instances||{}).length, canvases: Array.from(document.querySelectorAll('canvas')).map(c=>({id:c.id,w:c.width,h:c.height,blank: c.getContext('2d').getImageData(0,0,Math.min(c.width,10),Math.min(c.height,10)).data.some(v=>v!==0)}))})\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "[browser_console] clear=False expression=({errors: performance.getEntriesByType(' (928 chars result)", "tool_call_id": "call_lLov7TZmX3XJwRZCyGLINN58" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "call_Q7OFs7m6iG9HazXf1BaGgtx2", "call_id": "call_Q7OFs7m6iG9HazXf1BaGgtx2", "response_item_id": "fc_0e19823b78ca7008016a034137a7d48191a8852e5562071943", "type": "function", "function": { "name": "browser_console", "arguments": "{\"clear\":true}" } } ], "finish_reason": "tool_calls", "reasoning": "**Evaluating chart instances**\n\nI'm trying to understand if the \"blank check\" in the top-left corner indicates there's data. 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JARVIS Health Dashboard v3

Generiert: {now}

Fix: Die Charts verwenden jetzt keine externe Annotation-Plugin-Abhängigkeit mehr. Referenzbereiche und Event-Marker werden als normale Chart.js-Datasets gerendert — weniger Glamour, mehr Funktion. Erfrischend.
\\n 222|

Systemstatus

{cards}
\\n 223|

Labortrends mit Referenzband & Health-Event-Markern

{''.join(charts) or '

Keine Labortrends verfügbar.

'}\\n 224|

Ernährungsplan-Konsequenz

\\n 225|{nutrition_rows}
DatumScoreerkannte Risikenpositive Treffer
\\n 226|

Health Event Periods / Zeiträume

{period_rows}
StartEndeTypLabelSchweregradNotizen
\\n 227|

Laborberichte / Original-PDFs

{lab_doc_rows}
IDOriginalStatus
\\n 228|

Health Events & Symptome

{event_rows}{symptom_rows}
DatumKategorieParameter/SymptomWert/Notiz
\\n 229|

Letzte Dokumente

{doc_rows}
IDDateiKategorieStatusReviewVolltext-Zeichen
\\n 230|\\\"\\\"\\\"\\n 248| out.write_text(html_text, encoding=\\\"utf-8\\\")\\n 249| c = conn()\\n 250| c.execute(\\\"INSERT INTO report_runs(report_type, output_path, summary) VALUES(?,?,?)\\\", (\\\"dashboard_v3\\\", str(out), \\\"Dashboard v3 generiert\\\"))\\n 251| c.commit(); c.close()\\n 252| print(out)\\n 253|\\n 254|\\n 255|if __name__ == \\\"__main__\\\":\\n 256| main()\\n 257|\", \"total_lines\": 256, \"file_size\": 18210, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_sGEcGEmcxhVkQANxLIRcR2xT" }, { "role": "assistant", "content": "", "reasoning": "**Fixing date issues**\n\nI need to address this weird date that seems to be inserted incorrectly, probably due to unvalidated labor health events. It looks like the date \"2026-20-40\" might come from a document named \"2620408\". I think I need to run a query to clean this up and validate the data properly! It’s important to ensure all the dates are accurate, so I’ll definitely look into this. Let's see how I can resolve it!", "finish_reason": "tool_calls", "reasoning_content": "**Fixing date issues**\n\nI need to address this weird date that seems to be inserted incorrectly, probably due to unvalidated labor health events. It looks like the date \"2026-20-40\" might come from a document named \"2620408\". I think I need to run a query to clean this up and validate the data properly! It’s important to ensure all the dates are accurate, so I’ll definitely look into this. 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Let's see how I can resolve it!" } ] } ], "tool_calls": [ { "id": "call_CmHEiUjBwuCon3I9441Aq1BD", "call_id": "call_CmHEiUjBwuCon3I9441Aq1BD", "response_item_id": "fc_0106665210ffd2a2016a034dcacb088191823164a6b8f893b8", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3\\ncon=sqlite3.connect('/home/agent/.hermes/assets/Gesundheit/health_data.db'); con.row_factory=sqlite3.Row\\nprint('bad health_events')\\nfor r in con.execute(\\\"select * from health_events where date not glob '????-??-??' or cast(substr(date,6,2) as int)>12 or cast(substr(date,9,2) as int)>31 or cast(substr(date,6,2) as int)<1 or cast(substr(date,9,2) as int)<1 order by date limit 50\\\"):\\n print(dict(r))\\nprint('events around 2026-20')\\nfor r in con.execute(\\\"select * from health_events where date like '2026-20%' order by id\\\"):\\n print(dict(r))\\nprint('all health_events count by category')\\nfor r in con.execute('select category,count(*) from health_events group by category'):\\n print(r)\\nPY\",\"timeout\":120}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"bad health_events\\n{'id': 70, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Leukozyten', 'value': '3', 'unit': 'Leukozyten', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 71, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Erythrozyten', 'value': '4', 'unit': 'Erythrozyten', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 72, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Thrombozyten', 'value': '150', 'unit': 'Thrombozyten', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 73, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'MCV', 'value': '80', 'unit': 'MCV', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 74, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Kreatinin', 'value': '62', 'unit': 'Kreatinin', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 75, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'eGFR', 'value': '1.73', 'unit': 'eGFR', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 76, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Glukose', 'value': '4', 'unit': 'Glukose', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 77, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'CRP', 'value': '5.0', 'unit': 'CRP', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\nevents around 2026-20\\n{'id': 70, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Leukozyten', 'value': '3', 'unit': 'Leukozyten', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 71, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Erythrozyten', 'value': '4', 'unit': 'Erythrozyten', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 72, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Thrombozyten', 'value': '150', 'unit': 'Thrombozyten', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 73, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'MCV', 'value': '80', 'unit': 'MCV', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 74, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Kreatinin', 'value': '62', 'unit': 'Kreatinin', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 75, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'eGFR', 'value': '1.73', 'unit': 'eGFR', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 76, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'Glukose', 'value': '4', 'unit': 'Glukose', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\n{'id': 77, 'date': '2026-20-40', 'category': 'LABOR', 'parameter': 'CRP', 'value': '5.0', 'unit': 'CRP', 'source': '2620408 bericht__Laborbefund__fur_Marcel_Gasser_#1.PDF', 'notes': 'Laborbefund', 'created_at': '2026-05-04 21:17:10'}\\nall health_events count by category\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_CmHEiUjBwuCon3I9441Aq1BD" }, { "role": "assistant", "content": "", "reasoning": "**Evaluating dashboard data**\n\nI need to consider what data to include in the dashboard. Should I add Gesamt-Cholesterin, Neutrophile, Lymphozyten, Monozyten, Basophile, and Eosinophile if it's available? I'll have to inspect these parameters closely to determine their relevance and whether they’re essential for the user. Figuring out which data points are most crucial is important for a well-rounded dashboard! It's all about delivering what's necessary while keeping it user-friendly.", "finish_reason": "tool_calls", "reasoning_content": "**Evaluating dashboard data**\n\nI need to consider what data to include in the dashboard. Should I add Gesamt-Cholesterin, Neutrophile, Lymphozyten, Monozyten, Basophile, and Eosinophile if it's available? I'll have to inspect these parameters closely to determine their relevance and whether they’re essential for the user. Figuring out which data points are most crucial is important for a well-rounded dashboard! It's all about delivering what's necessary while keeping it user-friendly.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA03h_hDJEqusmny2Ehxom8lByHqRF--ceedl2navuFQS2vcA-lNL8k0D8BTMx4TQ56KQhOXyZj2kDR4TZTR9ibGheH72999FsuHXQ8v82-FG4-QYi27_JjliyI4fxaW0_UTClYPuOVbWPfHSTSfq9CFFjW59E3B8lJigPN1WefD_PBXCu1x4ZNX-7ONmBFJPi_e3vGaLwEKm8sPHXt88smLqxGMMvYRH84WDjvOuCOjHVByZz5y4dv5sgBagMfO4XHB6Vc4Zx6uQYn-Yr3FLG6myL00K4Let0MdlKUXg6CnjIA4AIlRd3K7Y-NK7Z1Wr9rEA8O8CMrq3J9cMkyQVu6qOsY7uHO7YDMH3MpGIzEKeXUuVDdek8HBDOiK5QGk4pKypqpLQ0GVmvdDijY2VXPW548NEnHi8FbPWZzhUFmDdzOeFt_avLBOO_dIT4uoYlfvkuGf6f4ZA8CY5wXKM7FCCCWtWAbJn607XEKi1_yfFOoEn9H17LBnCbFQWKYEJT1rynkCbGS2WvjMnIZe5UIyT9zBNYDu7Qvq54m_nqmY0TmCpvebGsQjF1U0XlehB4fVZdGginmVXSUFKvmGmq00jTBrwL85de0acr86BxZimnXxYDQGfI9YxuPSiRaH1T0UslYY6QEN05uefguqG18tOkLFnGwHLhLsJT2hbhklqPDekdGGOj3wpbME48a1KSQ6VQscwt6tE0tb68AzaqeXuuL4kngRRAm_qodYvN107kzvqrTsZdk-tnJT95xJYvn4Og1iBXWOWytJBMR2fSui7AAa-jENYmBygbos1OBBrA5trt-K_D_eWh0WCRvMQ4Co-Det1K3tEULAzbx3dTzidg0XrIBG2jDkTF-7Ypc7NtvR_cGaXJ1rMDABFtJzBq3QOqkQBj6RLN8Vxb1ziqXM3gvud-TKaCdzU184o174f5GLRzhFSMRAwKHC5pwSvxI6KCSb5C2txtTkQvI8bTZUZryzNOSYth3eX7Wnvs0tGrfd5W6qtSyiovdMdQYOj-ELWpPqloUerCk25oYnQlG3WBkv9DADAezw048en4McTtUDYWFAVf1G6ulqhtdGZ07nfymSkcDYi-8Qd4WENYmS9edflqBRrHZ4PF1gOY8FSNaybPkDlfgudH0e-TM81NNiZHAj_EsJ2JDDLUmbbSoujNRPGguL57DtwzoUPIpNidHrZYtsdMXhBpt-P0Az413gF3v21jmhlI_CrffSf86kJOSXxUDlxl0cxfjO3zEfxXk8YuBdtP_GhAj3Ug1Sp_YTXaBrWp6SPU_bX9ieOAnaPmGr0YPIE87Wz5uVXFUSHnCO61wXD6mttMbOI3LeLDg3s3f40GNnUS7i3tiOSC-8Se7to-FD55BfsWZOBkhH1oZIrZ0u2HuQZb7GjlyXGvhUbqW26cM8-PzwqgrkhMaRS0ZcXU9nCjSyc7tzcbvsDIp3vIKzYzYxhW_T3qXgohmWO-GGueN3COPvBtNSgju1CCQswH1-BCyAqJI0gbLtV7qCZ3WaqH1s3zZya1ZWrIuo01H_2Pf1z1UWquAeKz70O7x227qlbLWnMzhzSrmNghbhXM11x9lOTgxt2mtgx93qAPSb-PCqSLZGVTkROMRxaKFsc7k-eD2gl1JCHE16M3DO6taf9yfPmrbG0ok7FGEiy9z48qCTGDCM7NYjCiSlnChW1eYSpawax31rVMCn3KT1hWztr31iDk6FoaFKRNjPyOxlg-SDaINwFUjvTFRzgn1lnPFC0mr9-CVDOKAP20GJ_BH3xEF2PVWEr0nSkzx5JMBGemlnHlw-BX6b9TgQYipeYGaHnb4hW925VBtRU7-O_aGcAN9UxlgJXmfXFCdO49jNYjaH2LzcPLllUc6EZ_SBnXzgUuNcDc2r8PzBjz-My5ZOkgEtt8GM8-xPEf_4hSgiDoXiNae-6PlxI1Z8pnSRJVxRloFtU8tP-Oz70imu32RPWfs6HYx3egT6Pboqw5xgatxMKmaCYGMgMkZjlf0n2g1mL6omEABVA85BVE4VRgCcye2W6jc7ckIRi26v_zml9fqpQwyRpTZmcS5LQJAjiMHOknGXklkPO6uNTmREdB6OZcstFaj5gJZLF5ZUDn3r9hBaglUqJkvxMyqzSKMTD5qywFrzvNzeTmJkP75Cv9jSuC_XTbkY6SmZtAT2dkTka9Vk5NwabsiwRK8NNYK6fpRpB2344bMMr1NYGk93-jhnfQ7QKGwdxkpKFMp6FMJxvCQ_KGg4YqxbIUX5dWLLzjBE_IRQ-Q2Uk4-qFA4oc4RreGgd655iCj7FeqIndn1vcT6bSCCYaVCs3kRM-CvWEiT1y4-v-voYacx3wmnhTgTVEMigVrfkPH8njCd9su029A99o08yUg3RkGdK0m8E3mtNg74ixB7b8h4JEoFL0d02rk7DK0CiOoysiVXf1n61DhT09uazNRv92t7KOffjIjjV6Lc3TMLhIPiFbcFc8RS9jaAs-nusbm1TJsU8_eIzqxWMdJD5zXJC_jT5VW495wWP4um6K8djx_GFHZq0=", "id": "rs_0ed0fda37cdab494016a034dd4a3088191adf06321f9d87f8d", "summary": [ { "type": "summary_text", "text": "**Evaluating dashboard data**\n\nI need to consider what data to include in the dashboard. Should I add Gesamt-Cholesterin, Neutrophile, Lymphozyten, Monozyten, Basophile, and Eosinophile if it's available? I'll have to inspect these parameters closely to determine their relevance and whether they’re essential for the user. Figuring out which data points are most crucial is important for a well-rounded dashboard! It's all about delivering what's necessary while keeping it user-friendly." } ] } ], "tool_calls": [ { "id": "call_Xoqzsw3r2Kb8F5SqdtfbywcZ", "call_id": "call_Xoqzsw3r2Kb8F5SqdtfbywcZ", "response_item_id": "fc_0ed0fda37cdab494016a034de1947c819194db5cfdd4b8af75", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3\\ncon=sqlite3.connect('/home/agent/.hermes/assets/Gesundheit/health_data.db')\\nfor r in con.execute(\\\"select distinct parameter_name from laborwerte where validierungsstatus='validiert' order by parameter_name\\\"):\\n print(r[0])\\nPY\",\"timeout\":60}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"ALAT (GPT)\\nAPC-Resistenz\\nASAT (GOT)\\nAlbumin\\nAlbumin/Kreatinin\\nAlk. Phosphatase\\nAnti-HBc-total\\nAnti-HBc-total quant\\nAnti-HBs\\nAnti-HBs quant\\nAnti-HCV Screening\\nAnti-HCV-IgG quant\\nAntithrombin III\\nAuto-Antikörper*\\nBakterien\\nBasophile\\nBeschaffenheit\\nBeta-2-Glykoprotein 1 IgA°\\nBeta-2-Glykoprotein 1 IgG°\\nBeta-2-Glykoprotein 1 IgM°\\nBilirubin\\nBilirubin gesamt\\nBlut\\nBlutsenkungsreaktion miniiSED\\nC-Reaktives Protein (CRP)\\nCalcium\\nCalcium auf Alb 40g/l korr\\nCardiolipin IgA°\\nCardiolipin IgG°\\nCardiolipin IgM°\\nCholesterin gesamt\\nD-Dimer\\nEBV EBNA-1-IgG\\nEBV VCA-IgM\\nEisen\\nEosinophile\\nEry (isomorph)\\nErythrozyt. verteilungsbreite\\nErythrozyten\\nFaktor VIII\\nFerritin\\nFibrinogen\\nFolsäure\\nGGT\\nGlukose\\nGranulierte Zylinder\\nHBs-Antigen\\nHDL-Cholesterin\\nHIV Ag/Ak Comboquant\\nHIV Ag/Ak Comboscreen\\nHLA-B51\\nHarnstoff\\nHbA1c\\nHomocystein\\nHyaline Zylinder\\nHämatokrit\\nHämoglobin\\nINR\\nIgG\\nIgG/Kreatinin\\nImmature Granulozyten\\nKalium\\nKetokörper\\nKreatinin\\nLDL-Cholesterin\\nLMW-Heparin (Anti-Xa)\\nLUPUS Antikoagulanz indiziert\\nLeukozyten\\nLymphozyten\\nMCH\\nMCHC\\nMCV\\nMethode\\nMikroglobulin/Kreatinin\\nMonozythen\\nNRBC Abs.\\nNatrium\\nNeutrophile\\nNitrit\\nNon-HDL-Cholesterin Sampson\\nPhosphat\\nPlattenepithelien\\nProtein\\nProtein C (Akt.)\\nProtein S (Akt.)\\nProtein S (frei)\\nProteine gesamt\\nQuick\\nRDW\\nSARS-CoV-2 AK\\nSpezifisches Gewicht\\nTSH\\nTestosteron\\nThrombin/AT-Komplex\\nThrombozyten\\nTriglyceride\\nUrobilinogen\\nVitamin B12 (Active)\\nVitamin D (25-OH)\\nZell-Zylinder\\na-1-Mikroglobulin\\naPTT\\ncreatin-Phosphokinase CK\\neGFR (Niere)\\nfT3\\nfT4\\npH\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_Xoqzsw3r2Kb8F5SqdtfbywcZ" }, { "role": "assistant", "content": "", "reasoning": "**Implementing health changes**\n\nI’m planning to implement changes, including removing invalid health events instead of just filtering them on the dashboard. I’ll back everything up while using SQL to set corrected notes. After deleting linsensuppe, I need to update nutrition features and recalculate nutrition scores. For the health events query, I might exclude LABOR and PROFILE. It's important to include relevant symptoms and medications but avoid any strange entries. I’ll also retain key parameters and consider adding more values if needed.\n**Expanding key parameters**\n\nI'm thinking about expanding the key parameters to include CRP, various blood counts, cholesterol levels, and other important markers. Some of these are non-numeric, and I’ll only generate charts if the data is numeric. I need to display ASAT instead of the invalid “AST (GOT).” It’s crucial to ensure that we filter out invalid dates in SQL, and I should probably exclude certain categories like LABOR and PROFIL. If any old, invalid LABOR health events pop up, it might be best to delete or review them.", "finish_reason": "tool_calls", "reasoning_content": "**Implementing health changes**\n\nI’m planning to implement changes, including removing invalid health events instead of just filtering them on the dashboard. I’ll back everything up while using SQL to set corrected notes. After deleting linsensuppe, I need to update nutrition features and recalculate nutrition scores. For the health events query, I might exclude LABOR and PROFILE. It's important to include relevant symptoms and medications but avoid any strange entries. I’ll also retain key parameters and consider adding more values if needed.\n**Expanding key parameters**\n\nI'm thinking about expanding the key parameters to include CRP, various blood counts, cholesterol levels, and other important markers. Some of these are non-numeric, and I’ll only generate charts if the data is numeric. I need to display ASAT instead of the invalid “AST (GOT).” It’s crucial to ensure that we filter out invalid dates in SQL, and I should probably exclude certain categories like LABOR and PROFIL. If any old, invalid LABOR health events pop up, it might be best to delete or review them.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA035uPtsz01unPMdUoTKUHcS0sgIddCNdwJjcVwabxwMOJw6DKIyy4dMG6ptk5uWnBbUocfsGnUNuC7ZoU09ocZ0nL_Z5JLTOpqf1DET1pWTN9sZrj5VaVCqZFJeSbhRVYPNGUojrxO4L9P-Ls3zSzYEoe2dUzmMyJXslpY-hM939i_d9a-VNRH4fIxPH0pkV7HDazxfNaHW_ETettstfVdczaUZ8VN8r7VnFzxA9GXqBlLAHoKHwPumFO7_W0KMZuF20bZgSEgl7N-VAyrmdkx5FvBRRNM_Zm8lNPOc77CiB3aUE0zxpb3aFXvSuaMibvV5v_sct1A3CpbCOIPdTzFv_WHgAXOqVp1o7XmsrxuilXCs-Da_238I5vu794mJSMlJRHd8dFZN4feHl433XmK1LBqjiTGMA6N9BOQ-yNIkSo2WHSIYgg3Xesy94dgmYWYuh4ln_LaoGk5PfiO_oIaevePd-yuJ0boLNesJabz208_YhJw3QG7NGW9gknkbrwmCGyrii6JvJRTu5N8tCQfQhgWU76uh_Xjva4-hfZDQWFl1XiGt1i1RxPuGd6x_1d_hDyMpeDpStUau8PjesgOi_xG46z_fP159B57ViL35PtFwEqOL75XZXV25Jj1NFpfnPgTH4A5OU1f087NVivSv9n_Php3CnhYDj2yrxZu8Xb_gRivxQOw4g5Q0yEzHS3-zNRqLnWxUU0aiRzhCFuLX4yIkH_W3t4nlV-4ojiazAXihS3Ic4VAJ1EyXeXsHH1D5HbiW9QBI7BIGteIcSynuxUBDHXRyP37ljyC2GmTvCE8pCKAWKwPX7rEvZd3fMnDG95oqyregG1j5-q9OzN5PPGuDl_igorfFviCmBIfjWGPLlRooAxWIqz9yJLiDTITVTEqSAU5EIYsINuouz-iR89gM0bLptH-jzZj0DcoqED_zsR9SnkV7C61F4NRUxcCRGtQnPIuHLi8vQyEm4BYE6wV1rLSXDeQD0bOSRvekviMpfJgZO2LoM5W9gHedmr3OEmQXkeSrZafhTJBP8WcsJ84aHu1bF0v65STEXhjd11-gdlFIQils2ah61u5uiGLl4RxxTkGju6Rek0h5SbXd9QhlXw3Yge58qFi8MVU6iRSzGe8a4arNxmzlvytVuVRVWIV6y7LNo-pm_kxZTP0mGFa76to8YvzYpCUyClfdH1FAiRlqQ4lmS5Pd_amWkFeW49GFzVFUXamCJhm6YbAVUaPju468M0-GVC8DvsHbfmiTD07HgfmJsKvtKPxUSgN2omeU9_yt1qP-PE8zPg6TZ2Err0QLnK9bp6Qz_9ktE_lA5PMQFxJMaMhMKkfm4sdm0yu-uKKBq9j3ksy5_ri8sjR5GkAb8A1etI-brqjsVkMYhBozdZ3UTazFWYxZr2mvND9FWOs_yjzPQxu6Fj537XO6oEaSlUrk0-9FavKBjaDZKBNlU8kaZmJ_rjDP-km6FNbnmy0vS-TMOLP2jKDyzXmNVoSaQg9QURNDEOdZHL12gJfOZ-ukGXudtQBef6SnWtv5_xJhwl0AbIvwBCeuVLEyt5jDDc1Oijmu4zVzZP9oF7S6JpnC7gRMfXVsV4M4Hedi1mgj3aoYNOmhcHVBl7T5SAhtcN-R51sXM0W1et-IsorucQIcOW25y81P65nWkiu2__LvAdNU__IpnGrIlkgaCD8zjFFkjNVXfsiU0HJL7QDTO4-40BRmg1mnTqlFPtS8TBuLy7xK08fIKl6zG262BWXyizSw47Zu3yNeEobObPucpG_Dr0RiFENtsE_TazgmVTewZx4b8gqNL-ZUDFkH8j3nDXDp7fPNyB6Ay_mApwRsAMG58Q_CR5hvj_WJMJbUdE6-tQ3PtIUfDgwSEXh8_fd7A6LlBJPrzgN_bnBdPnBsxHpy_OXzs3LbI7mo3fjA7ErRyJl-1BhijN5z_ESVOXUMHZGWpN8iUBns58kf_zmo2tBRoiFfUHqTu_9ytVo5YG89E_zlfWdCCiebdJl2-WrxzkKy6GSN2tgx_37c1vNY2AwF83sFESzaGocHSQA8yFMtsz_KIfMjXfAXf1H36jEZWGV9hqTcPltItEY3Y7jpvOMjmFDN3wS0xzXuhvEz53w_SfHB_Vkeijd3UxDXAYEDxDLFtXrUjxBLdlscqJX2S7K7ApHRmlM9XEiahQE1HsMhlZHCxpwV4CDvsRjlrfiHJSb3r7WGncJZ3PXvgGYp43ZzPIAif7kjyUSYsXMhaN0Cx6lv4C-63FYpzZRk-3V00LSVyZpuY4csmMp-KgtI9eQ-AKIznk4GR6oVJqyEq5j1Wz8uuOfvNIItKKlCPmdx6csn533G0FyU9-Zhkqw08YajcIxYghXRp6ueztRmoZWAJKhXrWPwKYSk2dujUagJ6HWbxigFyUxBbBpBoVXiEO8ay9oqB4LZWXzFFDCSMiGhdM1u7uUPhpGK8S-nVwJ8Sh_s0J0E_GgpwGIZjQYp3h6e2hVoUloQ1W0IlRdHmULO5LiTwguZipQaEexQY-0Dr0v3r6Gq5eb0JaEM15jnAEX6mX1cxHm6ZFaPkMo6QlNc2Ij6xs_h7q-ihnCsIZV4YpwW_YizdKGdMMl_ynp_8QZGZM0rwBVogj7gk_U1qf3tE4nvPvaPNXXqEb7NvJFxu_Asv8HC5CGQ9iMh26HIuVnqcfh6LipgdqKYW89rVOoiqPCWdWbUlf02za_d7XG27ygt8oXfh3fBSa67QJe814mhDYBh8tHrFeYD0r4hl-__4OXH5WaNSXNwIClowuupHRqXgQt4Lc9Ox3cUIxRYmGNKxihUIkqFIrW0NvZnMRRYIAStjponbOZrVV_4YakcB2Vj1jONMtrKWdanI0ecrl_3iwvevBl06BlJ44zavqglzbx7tWyNMvdvIGVlzQl885nQYH761iDsI5T7N2b2wfK5QfzaIssusXYP5y9EbVMiga9BuQ2QSzOIDrlO6WOe0PGUMCSfu7VpDEbro2ejjq_I6m8zDoBZKBwSQ8EBrPqIh5QcEvGnoYAtLVbVPtWa1bKZ5zJZ9c4Z3Oos5wcYTCr1OfVsCtnsSlrmOj0gvcKIJYzB6Iw-scqgrBOd3CJPIyV5M4_AXszEKEDMa_zAWion91aZkKMOduK31qRcWjJiL7W-c_dDTTJCosOAvSCzoS8kHKy5dERWlcrXEJKuhMoi3QS3Bqd0WoT4vcAAoGv1s7t1qlBF5Cfd_FC6cMXCsrikLXKvPkOaSQ9yI_m0FJVMgJq_z2Ly4DIN65UbpvvrsvYeO7m1_yhgw4JDVmI9-1N2ui-fZJFDwd_UT2BPZlH9hH8d6gGkjd2gR05XUYLlp7m6h-3-lbx47qXMSiCw5rcqgiYKUEzG87uo-srAxYCT1pslsflKaA7vZbKAICHH0e1KcGka_GSaGZUgFI3bp3GhAeT9dSawUXDxZmgaJf9WJby25RlJu-JB-TLbXGe6MANjP-Pfvo1eECe4Bb6KXESIFohls2A4ObYCSCqyF30zYuIf8J6TcIXQyEkLQ9aJj5JglaR23tZ7XYY7dM8Ij9Q5weoXQYBoO--4Nt7IOQfpiygu5wqkRxCfJI530FTg4ECkNsi36jfdc7GAlvfzcMEiiGwts_7fJbDlzXkCnbvEG8do1X9p8kpdBm-I8gI0xtizq550Iq84iOh34-sNLhOcCIDOHbHcuMzbkSC5V87ZONyuwepPLQns8jcylJ08P5PMtn9-wjiFRzp-nEmfIaPQ0TfD9gALvPbo-f6aucS7DUBWRxvU57Fy", "id": "rs_0c36012ff7925f42016a034de5d42c81919582cb086ab48f34", "summary": [ { "type": "summary_text", "text": "**Implementing health changes**\n\nI’m planning to implement changes, including removing invalid health events instead of just filtering them on the dashboard. I’ll back everything up while using SQL to set corrected notes. After deleting linsensuppe, I need to update nutrition features and recalculate nutrition scores. For the health events query, I might exclude LABOR and PROFILE. It's important to include relevant symptoms and medications but avoid any strange entries. I’ll also retain key parameters and consider adding more values if needed." }, { "type": "summary_text", "text": "**Expanding key parameters**\n\nI'm thinking about expanding the key parameters to include CRP, various blood counts, cholesterol levels, and other important markers. Some of these are non-numeric, and I’ll only generate charts if the data is numeric. I need to display ASAT instead of the invalid “AST (GOT).” It’s crucial to ensure that we filter out invalid dates in SQL, and I should probably exclude certain categories like LABOR and PROFIL. If any old, invalid LABOR health events pop up, it might be best to delete or review them." } ] } ], "tool_calls": [ { "id": "call_Iu8Rjs1OCFWYB0mZpMTE7rj8", "call_id": "call_Iu8Rjs1OCFWYB0mZpMTE7rj8", "response_item_id": "fc_0c36012ff7925f42016a034df9a500819187f43fd2f8c205f2", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3, shutil\\nfrom pathlib import Path\\nfrom datetime import datetime\\nbase=Path('/home/agent/.hermes/assets/Gesundheit')\\ndb=base/'health_data.db'\\nbackup=base/'backups'/f\\\"health_data_before_dashboard_event_cleanup_{datetime.now():%Y%m%d_%H%M%S}.db\\\"\\nbackup.parent.mkdir(exist_ok=True)\\nshutil.copy2(db, backup)\\ncon=sqlite3.connect(db); con.row_factory=sqlite3.Row\\n# 1) Delete impossible pseudo-date LABOR events: these are OCR/import artefacts, not health events.\\nbad_ids=[r['id'] for r in con.execute(\\\"select id from health_events where category='LABOR' and (date(date) is null or cast(substr(date,6,2) as int)>12 or cast(substr(date,9,2) as int)>31)\\\")]\\ncon.executemany('delete from health_events where id=?', [(i,) for i in bad_ids])\\n# 2) Correct user-stated false nutrition entry and symptom note.\\n# Keep the symptom \\\"Müdigkeit leicht\\\" but remove the incorrect Linsensuppe attribution.\\ncon.execute(\\\"delete from ernaehrung where datum='2026-05-10' and lower(beschreibung) like '%linsensuppe%'\\\")\\ncon.execute(\\\"update symptome set notizen='' where datum='2026-05-10' and symptom='Müdigkeit' and lower(coalesce(notizen,'')) like '%linsensuppe%'\\\")\\ncon.commit()\\nprint({'backup':str(backup),'deleted_bad_health_event_ids':bad_ids,'remaining_linsensuppe_rows':con.execute(\\\"select count(*) from ernaehrung where lower(beschreibung) like '%linsensuppe%'\\\").fetchone()[0]})\\nPY\",\"timeout\":60}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"{'backup': '/home/agent/.hermes/assets/Gesundheit/backups/health_data_before_dashboard_event_cleanup_20260512_175800.db', 'deleted_bad_health_event_ids': [70, 71, 72, 73, 74, 75, 76, 77], 'remaining_linsensuppe_rows': 0}\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_Iu8Rjs1OCFWYB0mZpMTE7rj8" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_x76kZvxpxZxSleeFBZ7X4jDy", "call_id": "call_x76kZvxpxZxSleeFBZ7X4jDy", "response_item_id": "fc_05f51264a7ac3cdc016a034e0a750481918bd265aa6c4f0997", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Dashboard-Quelle für Health Events/Symptome und fehlerhafte Datumseinträge prüfen\",\"id\":\"h1\",\"status\":\"completed\"},{\"content\":\"Fehlerhafte/merkwürdige Health-Event-Daten bereinigen oder aus Dashboard ausschliessen\",\"id\":\"h2\",\"status\":\"completed\"},{\"content\":\"Gesamtcholesterin und zusätzliche Behçet-relevante Werte ins Dashboard aufnehmen\",\"id\":\"h3\",\"status\":\"in_progress\"}]}" } } ] }, { "role": "tool", "name": "todo", "content": "{\"todos\": [{\"id\": \"h1\", \"content\": \"Dashboard-Quelle für Health Events/Symptome und fehlerhafte Datumseinträge prüfen\", \"status\": \"completed\"}, {\"id\": \"h2\", \"content\": \"Fehlerhafte/merkwürdige Health-Event-Daten bereinigen oder aus Dashboard ausschliessen\", \"status\": \"completed\"}, {\"id\": \"h3\", \"content\": \"Gesamtcholesterin und zusätzliche Behçet-relevante Werte ins Dashboard aufnehmen\", \"status\": \"in_progress\"}, {\"id\": \"h4\", \"content\": \"Dashboard neu generieren und Browser-Rendering verifizieren\", \"status\": \"pending\"}, {\"id\": \"h5\", \"content\": \"Kurz berichten inkl. sinnvoller Behçet-Indikatoren\", \"status\": \"pending\"}], \"summary\": {\"total\": 5, \"pending\": 2, \"in_progress\": 1, \"completed\": 2, \"cancelled\": 0}}", "tool_call_id": "call_x76kZvxpxZxSleeFBZ7X4jDy" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_GPb5Xz1mRWIecWVRefZdrNkl", "call_id": "call_GPb5Xz1mRWIecWVRefZdrNkl", "response_item_id": "fc_012575b1c3b9f458016a034e10a2a08191b7816448d7fe9c04", "type": "function", "function": { "name": "patch", "arguments": "{\"mode\":\"replace\",\"path\":\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\",\"old_string\":\" events = list(c.execute(\\\"SELECT date,category,parameter,value,notes,source FROM health_events WHERE date IS NOT NULL ORDER BY date\\\"))\\n symptoms = list(c.execute(\\\"SELECT datum,kategori,symptom,schwergrad,notizen FROM symptome ORDER BY datum\\\"))\",\"new_string\":\" # Dashboard events: do NOT mix routine lab rows into the event/symptom table.\\n # LABOR values belong in charts; PROFIL rows are static background facts.\\n # Also require SQLite-valid ISO dates to avoid artefacts like 2026-20-40.\\n events = list(c.execute(\\\"\\\"\\\"\\n SELECT date,category,parameter,value,notes,source\\n FROM health_events\\n WHERE date IS NOT NULL\\n AND date(date) IS NOT NULL\\n AND upper(COALESCE(category,'')) NOT IN ('LABOR','PROFIL')\\n ORDER BY date\\n \\\"\\\"\\\"))\\n symptoms = list(c.execute(\\\"SELECT datum,kategori,symptom,schwergrad,notizen FROM symptome WHERE date(datum) IS NOT NULL ORDER BY datum\\\"))\"}" } } ] }, { "role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n+++ b//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n@@ -150,8 +150,18 @@\\n try:\\n docs = list(c.execute(\\\"SELECT id,datei_name,dateipfad,kategorie,status,review_status,upload_datum,drive_web_url,local_original_path,length(COALESCE(extrahierte_inhalte,'')) text_len FROM dokumente ORDER BY id DESC LIMIT 25\\\"))\\n lab_docs = list(c.execute(\\\"SELECT id,datei_name,dateipfad,kategorie,status,drive_web_url,local_original_path FROM dokumente WHERE upper(COALESCE(kategorie,'')) LIKE '%LABOR%' ORDER BY id DESC LIMIT 40\\\"))\\n- events = list(c.execute(\\\"SELECT date,category,parameter,value,notes,source FROM health_events WHERE date IS NOT NULL ORDER BY date\\\"))\\n- symptoms = list(c.execute(\\\"SELECT datum,kategori,symptom,schwergrad,notizen FROM symptome ORDER BY datum\\\"))\\n+ # Dashboard events: do NOT mix routine lab rows into the event/symptom table.\\n+ # LABOR values belong in charts; PROFIL rows are static background facts.\\n+ # Also require SQLite-valid ISO dates to avoid artefacts like 2026-20-40.\\n+ events = list(c.execute(\\\"\\\"\\\"\\n+ SELECT date,category,parameter,value,notes,source\\n+ FROM health_events\\n+ WHERE date IS NOT NULL\\n+ AND date(date) IS NOT NULL\\n+ AND upper(COALESCE(category,'')) NOT IN ('LABOR','PROFIL')\\n+ ORDER BY date\\n+ \\\"\\\"\\\"))\\n+ symptoms = list(c.execute(\\\"SELECT datum,kategori,symptom,schwergrad,notizen FROM symptome WHERE date(datum) IS NOT NULL ORDER BY datum\\\"))\\n periods = list(c.execute(\\\"SELECT start_date,end_date,event_type,label,severity,location,notes FROM health_event_periods ORDER BY start_date DESC LIMIT 50\\\"))\\n nutrition_features = compute_nutrition_features(c)\\n finally:\\n\", \"files_modified\": [\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_GPb5Xz1mRWIecWVRefZdrNkl" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_9vc5lVpGT7ufIkcm0IkLftkA", "call_id": "call_9vc5lVpGT7ufIkcm0IkLftkA", "response_item_id": "fc_0ca35fd7fcd85c0b016a034e20e4088191870e024b5fb3d7da", "type": "function", "function": { "name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" key_params = [\\n # Behçet / systemic inflammation\\n \\\"C-Reaktives Protein (CRP)\\\", \\\"Blutsenkungsreaktion miniiSED\\\", \\\"Leukozyten\\\", \\\"Neutrophile\\\", \\\"Lymphozyten\\\", \\\"Monozythen\\\", \\\"Thrombozyten\\\", \\\"Ferritin\\\", \\\"Fibrinogen\\\",\\n # Thrombosis / vascular risk context\\n \\\"D-Dimer\\\", \\\"Faktor VIII\\\", \\\"Cholesterin gesamt\\\", \\\"LDL-Cholesterin\\\", \\\"HDL-Cholesterin\\\", \\\"Triglyceride\\\", \\\"Homocystein\\\",\\n # Kidney / urine involvement surveillance\\n \\\"Kreatinin\\\", \\\"eGFR (Niere)\\\", \\\"Albumin/Kreatinin\\\", \\\"Protein\\\", \\\"Blut\\\", \\\"Erythrozyten\\\", \\\"Leukozyten\\\",\\n # Medication / organ safety and nutritional context\\n \\\"ALAT (GPT)\\\", \\\"ASAT (GOT)\\\", \\\"GGT\\\", \\\"Vitamin D (25-OH)\\\", \\\"Vitamin B12 (Active)\\\", \\\"Folsäure\\\", \\\"HLA-B51\\\"\\n ]\",\"old_string\":\" key_params = [\\\"C-Reaktives Protein (CRP)\\\", \\\"Leukozyten\\\", \\\"Thrombozyten\\\", \\\"D-Dimer\\\", \\\"LDL-Cholesterin\\\", \\\"HDL-Cholesterin\\\", \\\"Kreatinin\\\", \\\"ALAT (GPT)\\\", \\\"Faktor VIII\\\", \\\"Ferritin\\\", \\\"Vitamin D (25-OH)\\\"]\",\"path\":\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"}" } } ] }, { "role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n+++ b//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n@@ -167,7 +167,16 @@\\n finally:\\n c.close()\\n \\n- key_params = [\\\"C-Reaktives Protein (CRP)\\\", \\\"Leukozyten\\\", \\\"Thrombozyten\\\", \\\"D-Dimer\\\", \\\"LDL-Cholesterin\\\", \\\"HDL-Cholesterin\\\", \\\"Kreatinin\\\", \\\"ALAT (GPT)\\\", \\\"Faktor VIII\\\", \\\"Ferritin\\\", \\\"Vitamin D (25-OH)\\\"]\\n+ key_params = [\\n+ # Behçet / systemic inflammation\\n+ \\\"C-Reaktives Protein (CRP)\\\", \\\"Blutsenkungsreaktion miniiSED\\\", \\\"Leukozyten\\\", \\\"Neutrophile\\\", \\\"Lymphozyten\\\", \\\"Monozythen\\\", \\\"Thrombozyten\\\", \\\"Ferritin\\\", \\\"Fibrinogen\\\",\\n+ # Thrombosis / vascular risk context\\n+ \\\"D-Dimer\\\", \\\"Faktor VIII\\\", \\\"Cholesterin gesamt\\\", \\\"LDL-Cholesterin\\\", \\\"HDL-Cholesterin\\\", \\\"Triglyceride\\\", \\\"Homocystein\\\",\\n+ # Kidney / urine involvement surveillance\\n+ \\\"Kreatinin\\\", \\\"eGFR (Niere)\\\", \\\"Albumin/Kreatinin\\\", \\\"Protein\\\", \\\"Blut\\\", \\\"Erythrozyten\\\", \\\"Leukozyten\\\",\\n+ # Medication / organ safety and nutritional context\\n+ \\\"ALAT (GPT)\\\", \\\"ASAT (GOT)\\\", \\\"GGT\\\", \\\"Vitamin D (25-OH)\\\", \\\"Vitamin B12 (Active)\\\", \\\"Folsäure\\\", \\\"HLA-B51\\\"\\n+ ]\\n event_by_date: dict[str, list[str]] = defaultdict(list)\\n for r in events:\\n event_by_date[str(r[\\\"date\\\"])[:10]].append(f\\\"{r['category']}: {r['parameter']} {r['value'] or ''}\\\".strip())\\n\", \"files_modified\": [\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_9vc5lVpGT7ufIkcm0IkLftkA" }, { "role": "assistant", "content": "", "reasoning": "**Removing duplicates in data**\n\nI’m noticing there are duplicate leukocytes in the urine list, which is fine, but it seems they might cause issues if the chart renders the same IDs twice. I need to remove the duplicates to prevent this problem. For the urine data, “Leukozyten” might not be separable, so I’ll have to patch it to ensure that the second duplicate gets removed properly. I want to make sure everything is clean and effective!", "finish_reason": "tool_calls", "reasoning_content": "**Removing duplicates in data**\n\nI’m noticing there are duplicate leukocytes in the urine list, which is fine, but it seems they might cause issues if the chart renders the same IDs twice. I need to remove the duplicates to prevent this problem. For the urine data, “Leukozyten” might not be separable, so I’ll have to patch it to ensure that the second duplicate gets removed properly. I want to make sure everything is clean and effective!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA044RkndVH-FclocKof_IUThUpm9FfrILWBY5QvEY7JIPxWbe6-b1u58qQLclVI5F6EcP6pTildggnvjigjyuIA45-P9OcGi_DT-5-pjm8735oOPeqN6UHOX2floKgcRovrMj4U9rZpzaw2BDd1cMjRXI49AD31LT0GOA5FHe9fzCOYKkeDqUt3ZTgsA714XdkiWVsQLUs8oeXTV7TpzSExE-DFy4fz5p9r17pOUzABh9esVPPk34fG51ExDeJKA5DL7ytAXM5DR0wajcc3E92DBCBUsV0LXu1MXzk2X-4bvJKTN74MH_dHy6G8jxwFd0aSmG_QobaV-Dc0GVDsUETEWKlKNHZ-f-1O9Y-ThwrXMZwWVjC8T4hOfCiYJAdzVQsVnhD9AI9L_18VcG8PfKApzByEP-_r1k5aOSyybkjHKXdJTJ2SgygSaU4ZiaCTYKwWO0BWaxoJMzP5TxK2J5vN4k9r6O6payB-Jg_tYFHtd-8Up_z7BBcYkBagvD12CEDPcxMdfJb1BC2QNqnJbTcSrfrJxkt5YOBZvPvue2pBT67DhNRIl1sjBkxz-Z0CHr2JmxQu4_Av3sa4cph0WIa51q9QvsROfiYzowN31on9Gz0-srnmK2FzXbwHn7L52ENcnTLiGl1s1kqP2QgSPUgByMscOIO9324lUma-LYWW5nPp0rqKsfkuxVtA623Rr5hezqi-TftM8yMElVlYeuB9Tq2istRIAB0Jq-U3zZLFlSFWAQ-8Q-7dNYL-t5hVyx1mTLdIXtAR-Kl86Z-qavo3cHGyr59bHhCxFgwplez8DjbZ-3r133lGv7f8BiRr6k7DruW057GhmskW0DN4fn4GIrQ8irvFsOm_uOuqW_9ovMl3jnUAw1T_E4wfvbOh7FZd20Xnz1zQFk5iU0Bu0tu7J3KTRVQAQCijxljBhw-SfkC8muPtYHRTw12oJzrnWS9CuUWWer_dQS7zZ0KvqYAmEbHcrTT07UOsfR_aaCsh5-OQZ_VFmAsrWqtqS95hdPrCl406LGwAsPgCT5nNxfKVGEVEqPzwx3laCw3QnzjHzHUBQ3CHer5DzD_RVPlPdwnHXjSDdFLrkT9sh7u5JxfBjgtLbJ1oG5dulP-cRZOC4DpQV2sm9rVeP50VkbQuiqCiJhTRlBmGUBxJtJ6LX1S9rG1NgldmxrVhnf1lxkhLq39rA7YnpRawekUYx8iOgX-it", "id": "rs_0d115b14363686c7016a034e33c5708191b04498d840fbe913", "summary": [ { "type": "summary_text", "text": "**Removing duplicates in data**\n\nI’m noticing there are duplicate leukocytes in the urine list, which is fine, but it seems they might cause issues if the chart renders the same IDs twice. I need to remove the duplicates to prevent this problem. For the urine data, “Leukozyten” might not be separable, so I’ll have to patch it to ensure that the second duplicate gets removed properly. I want to make sure everything is clean and effective!" } ] } ], "tool_calls": [ { "id": "call_oh3zneDWWnfPvkEzoa27YUNO", "call_id": "call_oh3zneDWWnfPvkEzoa27YUNO", "response_item_id": "fc_0d115b14363686c7016a034e3810a8819183ba2d8c3bbb0c41", "type": "function", "function": { "name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" \\\"Kreatinin\\\", \\\"eGFR (Niere)\\\", \\\"Albumin/Kreatinin\\\", \\\"Protein\\\", \\\"Blut\\\", \\\"Erythrozyten\\\",\",\"old_string\":\" \\\"Kreatinin\\\", \\\"eGFR (Niere)\\\", \\\"Albumin/Kreatinin\\\", \\\"Protein\\\", \\\"Blut\\\", \\\"Erythrozyten\\\", \\\"Leukozyten\\\",\",\"path\":\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"}" } } ] }, { "role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n+++ b//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n@@ -173,7 +173,7 @@\\n # Thrombosis / vascular risk context\\n \\\"D-Dimer\\\", \\\"Faktor VIII\\\", \\\"Cholesterin gesamt\\\", \\\"LDL-Cholesterin\\\", \\\"HDL-Cholesterin\\\", \\\"Triglyceride\\\", \\\"Homocystein\\\",\\n # Kidney / urine involvement surveillance\\n- \\\"Kreatinin\\\", \\\"eGFR (Niere)\\\", \\\"Albumin/Kreatinin\\\", \\\"Protein\\\", \\\"Blut\\\", \\\"Erythrozyten\\\", \\\"Leukozyten\\\",\\n+ \\\"Kreatinin\\\", \\\"eGFR (Niere)\\\", \\\"Albumin/Kreatinin\\\", \\\"Protein\\\", \\\"Blut\\\", \\\"Erythrozyten\\\",\\n # Medication / organ safety and nutritional context\\n \\\"ALAT (GPT)\\\", \\\"ASAT (GOT)\\\", \\\"GGT\\\", \\\"Vitamin D (25-OH)\\\", \\\"Vitamin B12 (Active)\\\", \\\"Folsäure\\\", \\\"HLA-B51\\\"\\n ]\\n\", \"files_modified\": [\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_oh3zneDWWnfPvkEzoa27YUNO" }, { "role": "assistant", "content": "", "reasoning": "**Considering health event categories**\n\nI’m thinking about creating a backup and possibly deleting all entries in the LABOR category from the health_events. Before I do that, I should inspect how many categories there are to ensure I’m not missing anything important. It's crucial to check these details before making any changes, just to be sure everything’s on track. Let's see how many categories we actually have!", "finish_reason": "tool_calls", "reasoning_content": "**Considering health event categories**\n\nI’m thinking about creating a backup and possibly deleting all entries in the LABOR category from the health_events. Before I do that, I should inspect how many categories there are to ensure I’m not missing anything important. It's crucial to check these details before making any changes, just to be sure everything’s on track. Let's see how many categories we actually have!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA05IcJN53jtzU7DiQPJFPruTYipDAjSVFI2AHrYMSrCTYKXB53B3HGeZxt64uk6eLIxH0dOFGr-3SIq4ElxYp4-9UYZq6TIebJ73sgfgQwtr6sCw72ZwrTfklmo8fh5EVSV2gpNFSYdixWxvCIt1jf6HehdV5FmmT56JnAbjXEAPDnBTIfOwSghoWIF3uyOF1YAriS_sudNGznFI2qZNVqK4RJBuDdbaelVIPTYPveSaFvHnYE7VOgbzvP4yFghPrMnVOfYQ1E9XWiHUmlnsLDhk9tUaQ94soSwjByv4wMywGdlXR8ZZe7TFCupXapfWBUd10BQY2jKjEsGsNQo-yAv5M1QHTx1yAfjOW77dUd4Mv_A-__osRlpFCjG_PPXdu16cqtE8HsV1UfJKD54fvTACcZHVVbNHvNFdR5k9e-62ifUr7rzyCSaC-IAn9KKU1LUOUoGjWsC3Of9tMqA8xSHDcQL7FNUf7RQTyMxKbj4b4s3hXZNzAOuQ15LO5TQ2J1DLnyBrxFf6Ty1dMLWxwYP3E_NJW_0XQZFAw6WJXreDUaq6I9XqY-z6ncIBFsjvejQSxRoc3CQYWS4V3i_VxLZ8lbsX02gI3riFEFolRHM_Niu2F4A4Wh9kfMO37ha-0yIO0SzAfPrSUMcN82eyK3zgfNSf31sK7qM0R6cZOOFsR5i3cu-5ig7ISLua1_yxRa0OXHWlLYYlwKMQpn-4i5KQh9C5JN7oOjFjG4KWAB4iPv3bRLublOwQpSeVv1VjKU02HyPkLrwQJwBwq551yc30EyLH6cYxcPJvvHuDgpgH58jBzJ-wcmE1wvIssHu_YC7JXVQ-OMiH_WH0ORyXSRXwWwvhCyDwKUEY4Y479uvz4N4eh_eaa1P5_9vVZB-T3Ym7t2fcSRCmBhEeqbKfJT_btq9Drur593RYytAMqZZ06WJdEHzdyQZcfgIV_0iIV0AO4E_KXlyMpGiLtquPsTq2I__LLVsLVPJjL-AFuEcJ5xN-mz7zBxZB1evtYG_sr0V9DVZf_-UEBLfjTUHEwCBuaoKdPsTLbz8DZmaVeIZ5DG_JbCLSIrzNo7AlEF4D8WYS-WsUboDAiGdLnnVQRQs9fvz6165Ju46a5lyKJFnq4eFz4NUT1ELQT1_x8c4JxdW6R9q1HcmEhNlZqEvkHrqUYUqNlae8OyO6XdKGytBxYfrbGnii3eRcqpK-89DbZVP88howXyfAUn5ug7L6yDaHoWC9qP-KNqiAjZaZX5Ro70No3a-3pdPQ1-CRgiAg94-zDmaNF_lgWmC3vBypSGSJ6XEn1MowjXC-zLGO3WWLpDXAYDiutiXbNj3PNcOqfnY5GpHjHRhmNDINxFJmTMe7NJriIIWjcTwpGiziSlLhicIfs0evzHhErcECAWB4pTYO5NqXnQTP3V7bLuK7iRs5eZNFbWE8sRBwTA2xXlbw68p95_1Oi-OAOShEu9FeNDFqcYOMm1fzcQdnUJuk5fWk1r9QkCvUFAO0vLAK6y4byPlfmOGGmj4UGyhFOTOW00mgG4guFT21yo54aU_SfhDq-IHY537e4NoFv00NHkRMuOgwleDeu4XBOqNlazlaV2rPPtDYVpqHScyvRtrfVtxDAQrik3vW7MsoOrFxfJzfPJrC397J8hQrYAjIwp6Vyji58mX_muX0DM6iSWlTJCy2yk5q4-820SmMyVbaEH-f7TIsocMrYop0caR3yQJOksHZ06CyluAbcB90cqMzn2ZqFz8wV8o_KHYK4qn0kq5YOH25jBq4K1atAv3Ijm_KTWXkFZlQDHGWD9_fe6fz4HPvxOVPZMf28tSNT2Qj-IPCrbnjb1FccDpkFoe74Ep5pffjfj4QKdzNIqYTa7BGKQB0jmK5FDNUx3xr3LUuKYKfubk3CcCFWvW3pxVwECPPJ1XfDXgDnkJwtfsyQXZDeDyrgyNQiTwPLFq5FtcSsJtWEjFmi1OGcdLLB87uA122WjulCec7imQhHZsLNqWhORM7w246Mp8FqMNKKY4tJ9ViQDn1UL7nIBUkPHwFY867FTmOfUsEa6Z8NQD_UkavNOLQyBy3S2vohYKFejBxbbqSE5wqVPCK3RhpEPqqWGF5G3yud96g0YQBx16c84V04mW_UjN5OostZyKj7vEuWnU7_7IVIr3NaL3G6ZkJELqL1fQRqj83VQxEPZyRq7uxQ9PgwKvdujskRWVdJtd2jpkbVIpQYYseeCVe5HMCmczKpwQDNKZlYIVgPfZ8lmX8lzsafaj7aHWhf33O7et53Rpy-XrAlFtyJuRob_rhBIK61K14NaVK0UuQBqXmu0UpIKIvVDK8LzwkSxlJXmx3-AY1_0B9wFCdu0uVJNeNIJYoax6nduD6dJIQ65Ic7bYqfguXCQ==", "id": "rs_01d0afc1c2bd04f2016a034e3e267481919f09a4cfe6bee2db", "summary": [ { "type": "summary_text", "text": "**Considering health event categories**\n\nI’m thinking about creating a backup and possibly deleting all entries in the LABOR category from the health_events. Before I do that, I should inspect how many categories there are to ensure I’m not missing anything important. It's crucial to check these details before making any changes, just to be sure everything’s on track. Let's see how many categories we actually have!" } ] } ], "tool_calls": [ { "id": "call_pxWxwIcBLwxFpFXtBzVvaEOl", "call_id": "call_pxWxwIcBLwxFpFXtBzVvaEOl", "response_item_id": "fc_01d0afc1c2bd04f2016a034e48dbb88191acbddf04fd8f9705", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3\\ncon=sqlite3.connect('/home/agent/.hermes/assets/Gesundheit/health_data.db')\\nfor r in con.execute('select category,count(*) from health_events group by category order by 2 desc'):\\n print(r)\\nPY\",\"timeout\":60}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"('LABOR', 144)\\n('BEFUNDE', 37)\\n('ereignis', 19)\\n('labor', 18)\\n('PROFIL', 5)\\n('radiologie', 3)\\n('klinischer_befund', 2)\\n('medikament', 2)\\n('MEDIKAMENTE', 1)\\n('bildgebung', 1)\\n('dermatologie', 1)\\n('ophthalmologie', 1)\\n('status', 1)\\n('termin', 1)\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_pxWxwIcBLwxFpFXtBzVvaEOl" }, { "role": "assistant", "content": "", "reasoning": "**Optimizing health events display**\n\nI’m considering how to handle labor data — potentially excluding uppercase catches. Should dashboard event markers use non-lab values? I'll have to refine how we present Health Events by possibly adding a clinical events table, while excluding BEFUNDE. I realized that BEFUNDE in health events are documents, so maybe we don't need to show all of them. The user noticed some weird lab data, so refining the table title and format could help. Chronological descending order might be the way to go!", "finish_reason": "tool_calls", "reasoning_content": "**Optimizing health events display**\n\nI’m considering how to handle labor data — potentially excluding uppercase catches. Should dashboard event markers use non-lab values? I'll have to refine how we present Health Events by possibly adding a clinical events table, while excluding BEFUNDE. I realized that BEFUNDE in health events are documents, so maybe we don't need to show all of them. The user noticed some weird lab data, so refining the table title and format could help. Chronological descending order might be the way to go!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA05TzTCyT21Oc4qehkUyuK7W8q0O9sUHS8R_dIoDhQyR0U4hWLGq_GUGSOxEGVNIi_LVbNw9NIPWASXX7CzOdeOpTMmZJSP5s3CC7voIfUrLrCZELBiR-5hE4__xR2J0BHxTt6Rb3vGK7bA0xoibXbhL_FKGWh0a9cxgtJTNFrgCyWiX6kBGMijLoA0JBwHNxQV1fQTyKmyX2aIxdKU6ZAWedszyqguYfJwbk4-CA1kUZRg-p_TxpJbukM6B3ySkn5-KIGILi63B1czAoN0yzWeUO1z7PsX2CYQx4FtV_ggia7CLGvHdrzhaNw-ngT951eKbMECBseUk1PuLjYrVw4aS6PXGwGQEURaEa_xd4hc8sdYPHtSdb3cOgn-KfEbUcyv4hMAw0w-9gj115Ia2dfu4g5hNIM3wfgYHWzJWi3-S0aPu44Hh19h4sdxdsndfMg6olP7RAOLVtX_6jnCQRB5OU7NjtgG97-B-aBLqrte39LaIO2QpqOwOU9JbEgul9kIur3bpr9n1UhndGnmU1kGeRRRtVmPCSwskpo9ErYn06TKDRhA7hwEauGoXBP3-2v1nyZo6iC9hi90GkDh8SlPsqCeDQNkqYOZgVfJYRuO8tPYx4bjwSdx27bX8yO9x-mO49fXR71ZXoPr_PNQHZ4PN2lt6ps_GYiXEXgIDtN7s1oCOcotJLTGj2vVd2KmPuh0l2NgrdbqYvPCTI02qZeCIazifRkrEx9X6QGM_S5BO9E0Uu6iVdK_mJVm9kvhIPcJzJRLfdvoOTYLcrp68wkyqt5iKKnL46CyepI3jtGlq1BCJCJUQAopda1M26XDDE9C0Q-UR-aLX3tQpES0LxZD9I9o7syM9EmMB4YLEDDwFeQQOb24N6hZfNZlJ6JiUkXF-Dpo5O2kwPuMWI21bZ7tKPcR0-8_-rNOr1xDYZyWLM5a7CeRgOpAdfr0ki0mOwMjgI_vD1RBba2sMt8DcbnlVhm_emE0OjgPmN6rEiy1WBSK3dJTdf153vKHBaEpn3cXsLPfxWlXpg4O9iE4pPzcn4o1RmH_P0eNiqzmlDXGYv4gYfN9qcl57shAsMy3D9juEEhYTJ0WKH-b1HMvZ0jtiFkQdma0mU88Qhu4ggC8usk6g5iwnAXQKQaSS5T9_5bUoLjtKVwGy9VQqhiq8d_zwWh7XGgInm7aiBOdtGk9mlLg18MKyObezlm_DQaCB01_Tu72kClNe-a1TJAhjxrmtz8_cZpQf2-CPgz6AaITFq-3oH70KjcSBP7A0jI2diCLwm5dpC1bgG8XO-1TFbID8_pOQOmBSgJoF7kcOwONqVP3--gpjyFeRY3tDhQj0XON00cH0FjonMlo2EWCPpVjb7S19MXNvr1F2T4KjbWUUwyhliflfQGzT_EYYvwZvCTUXfRHgbPuDUzmsSqcK3lo5FEwiSMHVgjiWZsE4GVNPuyhTZkuELqy3TpBr8bx0e_71Fxf87Uf3yWga58phpyjqh07N3CkzitzcuFRofwr6iINU4VfR7ZS911CtQK9Ie56GgrxYO9C1UbwExx39AGesE4Zm7H0E7uRAo7hEXjzTcyrCNIobOIoBcfn33HL63yVXZ9MnoRsks3frqX4rn-Yy3yZ51iBJreaSpURCjQJGsLXQFxCzyMFnSBFb8_FRKmaCL-sSMR-Klyrw4HuIeB6vDn9DJwQP-PxXm61SMqC0twjYYaH_RQw7X-8OyshVOHMiMbDdElTuBn56b_W3FON8kHJLzc0VoLzlAT9VYMy_ldrcp00Lchfhsfza6S1Zg4kQ", "id": "rs_0e549868b414e092016a034e4c59c881918e4209779077d91e", "summary": [ { "type": "summary_text", "text": "**Optimizing health events display**\n\nI’m considering how to handle labor data — potentially excluding uppercase catches. Should dashboard event markers use non-lab values? I'll have to refine how we present Health Events by possibly adding a clinical events table, while excluding BEFUNDE. I realized that BEFUNDE in health events are documents, so maybe we don't need to show all of them. The user noticed some weird lab data, so refining the table title and format could help. Chronological descending order might be the way to go!" } ] } ], "tool_calls": [ { "id": "call_NqnWPC854PxU8qrdiV0oly96", "call_id": "call_NqnWPC854PxU8qrdiV0oly96", "response_item_id": "fc_0e549868b414e092016a034e5353b48191ba597e78bdb54b09", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 -m py_compile /home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py && python3 /home/agent/.hermes/assets/Gesundheit/scripts/health_pipeline.py dashboard && python3 - <<'PY'\\nimport sqlite3\\ncon=sqlite3.connect('/home/agent/.hermes/assets/Gesundheit/health_data.db'); con.row_factory=sqlite3.Row\\nprint('bad dates remaining', con.execute(\\\"select count(*) from health_events where date(date) is null or cast(substr(date,6,2) as int)>12 or cast(substr(date,9,2) as int)>31\\\").fetchone()[0])\\nprint('linsensuppe rows', con.execute(\\\"select count(*) from ernaehrung where lower(beschreibung) like '%linsensuppe%' or lower(coalesce(notizen,'')) like '%linsensuppe%'\\\").fetchone()[0])\\nprint('symptom', [dict(r) for r in con.execute(\\\"select * from symptome where datum='2026-05-10'\\\")])\\nPY\",\"timeout\":180}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"/home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html\\n/home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html\\nbad dates remaining 0\\nlinsensuppe rows 0\\nsymptom [{'id': 1, 'datum': '2026-05-10', 'kategori': 'Allgemein', 'symptom': 'Müdigkeit', 'schwergrad': 'leicht', 'wirkung': '', 'notizen': '', 'created_at': '2026-05-10 13:43:33'}]\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_NqnWPC854PxU8qrdiV0oly96" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_qnKRwCfHPJuP6Qfiu9UG7lz4", "call_id": "call_qnKRwCfHPJuP6Qfiu9UG7lz4", "response_item_id": "fc_087e427d1168ac7b016a034e5ea5008191a00788b1608c41ca", "type": "function", "function": { "name": "todo", "arguments": "{\"merge\":true,\"todos\":[{\"content\":\"Gesamtcholesterin und zusätzliche Behçet-relevante Werte ins Dashboard aufnehmen\",\"id\":\"h3\",\"status\":\"completed\"},{\"content\":\"Dashboard neu generieren und Browser-Rendering verifizieren\",\"id\":\"h4\",\"status\":\"in_progress\"}]}" } } ] }, { "role": "tool", "name": "todo", "content": "{\"todos\": [{\"id\": \"h1\", \"content\": \"Dashboard-Quelle für Health Events/Symptome und fehlerhafte Datumseinträge prüfen\", \"status\": \"completed\"}, {\"id\": \"h2\", \"content\": \"Fehlerhafte/merkwürdige Health-Event-Daten bereinigen oder aus Dashboard ausschliessen\", \"status\": \"completed\"}, {\"id\": \"h3\", \"content\": \"Gesamtcholesterin und zusätzliche Behçet-relevante Werte ins Dashboard aufnehmen\", \"status\": \"completed\"}, {\"id\": \"h4\", \"content\": \"Dashboard neu generieren und Browser-Rendering verifizieren\", \"status\": \"in_progress\"}, {\"id\": \"h5\", \"content\": \"Kurz berichten inkl. sinnvoller Behçet-Indikatoren\", \"status\": \"pending\"}], \"summary\": {\"total\": 5, \"pending\": 1, \"in_progress\": 1, \"completed\": 3, \"cancelled\": 0}}", "tool_call_id": "call_qnKRwCfHPJuP6Qfiu9UG7lz4" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_r9CHirsTnbQPOHhn38J4601d", "call_id": "call_r9CHirsTnbQPOHhn38J4601d", "response_item_id": "fc_0d862110f4df38f2016a034e6381fc81918bab74c8f8c339b9", "type": "function", "function": { "name": "browser_navigate", "arguments": "{\"url\":\"file:///home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html?eventfix=1\"}" } } ] }, { "role": "tool", "name": "browser_navigate", "content": "{\"success\": true, \"url\": \"file:///home/agent/.hermes/assets/Gesundheit/reports/health_dashboard.html?eventfix=1\", \"title\": \"JARVIS Health Dashboard v3\", \"stealth_warning\": \"Running WITHOUT residential proxies. Bot detection may be more aggressive. Consider upgrading Browserbase plan for proxy support.\", \"stealth_features\": [\"local\"], \"snapshot\": \"- heading \\\"JARVIS Health Dashboard v3\\\" [level=1, ref=e1]\\n- paragraph\\n - StaticText \\\"Generiert: 2026-05-12 17:59\\\"\\n- generic\\n - StaticText \\\"Fix: Die Charts verwenden jetzt keine externe Annotation-Plugin-Abhängigkeit mehr. Referenzbereiche und Event-Marker werden als normale Chart.js-Datasets gerendert — weniger Glamour, mehr Funktion. Erfrischend.\\\"\\n- heading \\\"Systemstatus\\\" [level=2, ref=e2]\\n- heading \\\"Labortrends mit Referenzband & Health-Event-Markern\\\" [level=2, ref=e3]\\n- generic\\n - heading \\\"C-Reaktives Protein (CRP)\\\" [level=3, ref=e9]\\n - StaticText \\\"Referenz: < 5.0 mg/l\\\"\\n- generic\\n - heading \\\"Blutsenkungsreaktion miniiSED\\\" [level=3, ref=e10]\\n - StaticText \\\"Referenz: <15 mm/h\\\"\\n- generic\\n - heading \\\"Leukozyten\\\" [level=3, ref=e11]\\n - StaticText \\\"Referenz: <20 /microL\\\"\\n- generic\\n - heading \\\"Neutrophile\\\" [level=3, ref=e12]\\n - StaticText \\\"Referenz: 1.4 - 8.0 G/l\\\"\\n- generic\\n - heading \\\"Lymphozyten\\\" [level=3, ref=e13]\\n - StaticText \\\"Referenz: n/a\\\"\\n- generic\\n - heading \\\"Thrombozyten\\\" [level=3, ref=e14]\\n - StaticText \\\"Referenz: 150 - 450 Tsd/µl\\\"\\n- generic\\n - heading \\\"Ferritin\\\" [level=3, ref=e15]\\n - StaticText \\\"Referenz: > 50 ng/ml\\\"\\n- generic\\n - heading \\\"Fibrinogen\\\" [level=3, ref=e16]\\n - StaticText \\\"Referenz: 2.0 - 4.0 g/l\\\"\\n- generic\\n - heading \\\"D-Dimer\\\" [level=3, ref=e17]\\n - StaticText \\\"Referenz: < 500 µg/l\\\"\\n- generic\\n - heading \\\"Faktor VIII\\\" [level=3, ref=e18]\\n - StaticText \\\"Referenz: 60 - 150 %\\\"\\n- generic\\n - heading \\\"Cholesterin gesamt\\\" [level=3, ref=e19]\\n - StaticText \\\"Referenz: < 5.0 mmol/l\\\"\\n- generic\\n - heading \\\"LDL-Cholesterin\\\" [level=3, ref=e20]\\n - StaticText \\\"Referenz: < 3.0 mmol/l\\\"\\n- generic\\n - heading \\\"HDL-Cholesterin\\\" [level=3, ref=e21]\\n - StaticText \\\"Referenz: > 1.0 mmol/l\\\"\\n- generic\\n - heading \\\"Triglyceride\\\" [level=3, ref=e22]\\n - StaticText \\\"Referenz: < 1.7 mmol/l\\\"\\n- generic\\n - heading \\\"Homocystein\\\" [level=3, ref=e23]\\n - StaticText \\\"Referenz: < 10.0 µmol/l\\\"\\n- generic\\n - heading \\\"Kreatinin\\\" [level=3, ref=e24]\\n - StaticText \\\"Referenz: 62 - 106 µmol/l\\\"\\n- generic\\n - heading \\\"eGFR (Niere)\\\" [level=3, ref=e25]\\n - StaticText \\\"Referenz: > 90 ml/min\\\"\\n- generic\\n - heading \\\"Albumin/Kreatinin\\\" [level=3, ref=e26]\\n - StaticText \\\"Referenz: <3\\\"\\n- generic\\n - heading \\\"Protein\\\" [level=3, ref=e27]\\n - StaticText \\\"Referenz: 60-80 g/l\\\"\\n- generic\\n - heading \\\"Blut\\\" [level=3, ref=e28]\\n - StaticText \\\"Referenz: n/a\\\"\\n- generic\\n - heading \\\"Erythrozyten\\\" [level=3, ref=e29]\\n - StaticText \\\"Referenz: 4.3 - 5.7 Mio/µl\\\"\\n- generic\\n - heading \\\"ALAT (GPT)\\\" [level=3, ref=e30]\\n - StaticText \\\"Referenz: < 50 U/l\\\"\\n- generic\\n - heading \\\"ASAT (GOT)\\\" [level=3, ref=e31]\\n - StaticText \\\"Referenz: < 50 U/l\\\"\\n- generic\\n - heading \\\"GGT\\\" [level=3, ref=e32]\\n - StaticText \\\"Referenz: < 60 U/l\\\"\\n- generic\\n - heading \\\"Vitamin D (25-OH)\\\" [level=3, ref=e33]\\n - StaticText \\\"Referenz: > 75 nmol/l\\\"\\n- generic\\n - heading \\\"Vitamin B12 (Active)\\\" [level=3, ref=e34]\\n - StaticText \\\"Referenz: > 50 pmol/l\\\"\\n- generic\\n - heading \\\"Folsäure\\\" [level=3, ref=e35]\\n - StaticText \\\"Referenz: 7.0 - 45.0 nmol/l\\\"\\n- heading \\\"Ernährungsplan-Konsequenz\\\" [level=2, ref=e4]\\n- table\\n - row\\n - columnheader \\\"Datum\\\" [ref=e36]\\n - columnheader \\\"Score\\\" [ref=e37]\\n - columnheader \\\"erkannte Risiken\\\" [ref=e38]\\n - columnheader \\\"positive Treffer\\\" [ref=e39]\\n - row\\n - cell \\\"2026-05-10\\\" [ref=e40]\\n - cell \\\"0\\\" [ref=e41]\\n - cell \\\"Alkohol, Gesättigte Fette, Histamin, Industriezucker, Nachtschatten, Schweinefleisch, Weizen/Gluten\\\" [ref=e42]\\n - cell \\\"Ballaststoffe, Fisch/Omega-3, Protein gut\\\" [ref=e43]\\n - row\\n - cell \\\"2026-05-11\\\" [ref=e44]\\n - cell \\\"85\\\" [ref=e45]\\n- heading \\\"Health Event Periods / Zeiträume\\\" [level=2, ref=e5]\\n- table\\n - row\\n - columnheader \\\"Start\\\" [ref=e46]\\n - columnheader \\\"Ende\\\" [ref=e47]\\n - columnheader \\\"Typ\\\" [ref=e48]\\n - columnheader \\\"Label\\\" [ref=e49]\\n - columnheader \\\"Schweregrad\\\" [ref=e50]\\n - columnheader \\\"Notizen\\\" [ref=e51]\\n - row\\n - cell \\\"Noch keine Zeitraum-Events erfasst. Beispiel: Aphte von Start- bis Enddatum.\\\" [ref=e52]\\n- heading \\\"Laborberichte / Original-PDFs\\\" [level=2, ref=e6]\\n- table\\n - row\\n - columnheader \\\"ID\\\" [ref=e53]\\n - columnheader \\\"Original\\\" [ref=e54]\\n - columnheader \\\"Status\\\" [ref=e55]\\n - row\\n - cell \\\"96\\\" [ref=e56]\\n - cell \\\"260510_Laborwerte_Uebersicht.xlsx\\\" [ref=e57]\\n - link \\\"260510_Laborwerte_Uebersicht.xlsx\\\" [ref=e403]\\n - cell \\\"eingearbeitet\\\" [ref=e58]\\n - row\\n - cell \\\"94\\\" [ref=e59]\\n - cell \\\"260507_Labor_Blutwerte_Dermatologie.pdf\\\" [ref=e60]\\n - link \\\"260507_Labor_Blutwerte_Dermatologie.pdf\\\" [ref=e404]\\n - cell \\\"eingearbeitet\\\" [ref=e61]\\n - row\\n - cell \\\"89\\\" [ref=e62]\\n - cell \\\"260130_letter_6938292917295580271.pdf\\\" [ref=e63]\\n - link \\\"260130_letter_6938292917295580271.pdf\\\" [ref=e405]\\n - cell \\\"eingearbeitet\\\" [ref=e64]\\n - row\\n - cell \\\"88\\\" [ref=e65]\\n - cell \\\"250917 bericht KSB.pdf\\\" [ref=e66]\\n - 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link \\\"260306 Bericht 1__Klinische_Chemie__für_Marcel_Gasser.PDF\\\" [ref=e410]\\n - cell \\\"eingearbeitet\\\" [ref=e79]\\n - row\\n - cell \\\"83\\\" [ref=e80]\\n - cell \\\"250914_Laborbefund_POC_NFPraxis.pdf\\\" [ref=e81]\\n - link \\\"250914_Laborbefund_POC_NFPraxis.pdf\\\" [ref=e411]\\n - cell \\\"eingearbeitet\\\" [ref=e82]\\n - row\\n - cell \\\"82\\\" [ref=e83]\\n - cell \\\"251229 Bericht__Dermatologische_Klinik__für_Marcel_Gasser 3.PDF\\\" [ref=e84]\\n - link \\\"251229 Bericht__Dermatologische_Klinik__für_Marcel_Gasser 3.PDF\\\" [ref=e412]\\n - cell \\\"eingearbeitet\\\" [ref=e85]\\n - row\\n - cell \\\"81\\\" [ref=e86]\\n - cell \\\"250514_Labor_Rothen_Blutbild.pdf\\\" [ref=e87]\\n - link \\\"250514_Labor_Rothen_Blutbild.pdf\\\" [ref=e413]\\n - cell \\\"eingearbeitet\\\" [ref=e88]\\n - row\\n - cell \\\"80\\\" [ref=e89]\\n - cell \\\"251231 Bericht__Klinische_Chemie__für_Marcel_Gasser 2.PDF\\\" [ref=e90]\\n - link \\\"251231 Bericht__Klinische_Chemie__für_Marcel_Gasser 2.PDF\\\" [ref=e414]\\n - cell \\\"eingearbeitet\\\" [ref=e91]\\n - row\\n - cell \\\"79\\\" [ref=e92]\\n - cell \\\"251231 dermatologische Poliklinik vom 29.12.2025.pdf\\\" [ref=e93]\\n - link \\\"251231 dermatologische Poliklinik vom 29.12.2025.pdf\\\" [ref=e415]\\n - cell \\\"eingearbeitet\\\" [ref=e94]\\n - row\\n - cell \\\"78\\\" [ref=e95]\\n - cell \\\"260101 Krankheitsverlauf Thrombosen und Augenlidentzündung.pdf\\\" [ref=e96]\\n - link \\\"260101 Krankheitsverlauf Thrombosen und Augenlidentzündung.pdf\\\" [ref=e416]\\n - cell \\\"eingearbeitet\\\" [ref=e97]\\n - row\\n - cell \\\"77\\\" [ref=e98]\\n - cell \\\"251231 Bericht__Thrombophilie-Abklärung_vom_27.08.2025__für_Marcel_Gasser_geb._21.06.1985.PDF\\\" [ref=e99]\\n - link \\\"251231 Bericht__Thrombophilie-Abklärung_vom_27.08.2025__für_Marcel_Gasser_geb._21.06.1985.PDF\\\" [ref=e417]\\n - cell \\\"eingearbeitet\\\" [ref=e100]\\n - row\\n - cell \\\"76\\\" [ref=e101]\\n - cell \\\"251229 Bericht__Klinische_Chemie__für_Marcel_Gasser 4.PDF\\\" [ref=e102]\\n - link \\\"251229 Bericht__Klinische_Chemie__für_Marcel_Gasser 4.PDF\\\" [ref=e418]\\n - cell \\\"eingearbeitet\\\" [ref=e103]\\n - row\\n - cell \\\"75\\\" [ref=e104]\\n\\n[... 392 more lines truncated, use browser_snapshot for full content]\", \"element_count\": 446}", "tool_call_id": "call_r9CHirsTnbQPOHhn38J4601d" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_D2GUlD5GuYiKcXFu1XjJm0Ex", "call_id": "call_D2GUlD5GuYiKcXFu1XjJm0Ex", "response_item_id": "fc_0e959ff74dae280f016a034e691fc881918a46ca0ab36f7baa", "type": "function", "function": { "name": "browser_console", "arguments": "{\"expression\":\"({charts:Object.keys(Chart.instances||{}).length, badDateText: document.body.innerText.includes('2026-20-40'), linsensuppe: document.body.innerText.toLowerCase().includes('linsensuppe'), chol: document.body.innerText.includes('Cholesterin gesamt'), healthEventSnippet: (()=>{let h=[...document.querySelectorAll('h2')].find(x=>x.textContent.includes('Health Events')); let tbl=h?.nextElementSibling; return tbl?.innerText.slice(0,500)})()})\"}" } } ] }, { "role": "tool", "name": "browser_console", "content": "{\"success\": true, \"result\": {\"badDateText\": false, \"charts\": 28, \"chol\": true, \"healthEventSnippet\": \"Datum\\tKategorie\\tParameter/Symptom\\tWert/Notiz\\n2025-09-20\\tmedikament\\tEliquis (Apixaban)\\t5 mg, morgens und abends. Start.\\n2025-10-16\\tBEFUNDE\\tBefundnotiz\\tEndgltiger Befund\\n2025-10-16\\tBEFUNDE\\tBefundnotiz\\tBefund 16.10.2025, 14:19 von Sibold, Ken erstellt.\\n2025-10-16\\tBEFUNDE\\tBefundnotiz\\tBefund\\n2025-10-16\\tBEFUNDE\\tBefundnotiz\\tBefund 16.10.2025, 14:19 von Sibold, Ken erstellt.\\n2025-10-16\\tradiologie\\tCT Thorax-Abdomen KM\\tKein Hinweis auf suspekte Raumforderung thorakoabdominal. Keine pathologisch vergrösser\", \"linsensuppe\": false}, \"result_type\": \"dict\"}", "tool_call_id": "call_D2GUlD5GuYiKcXFu1XjJm0Ex" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqA06tCv3u9U3J-xMSeTgL37vp12Qrp9x3IK0v5-Xw-_nNDU3ZorzjEolNOrvOn7glFhe-JuSrbQm1qX755uMarb7Wu-ITW3OVGplEMXKI0a9sH1UOPiOu5NsEknUdcigo4InOERxeXFSFCQrTMYbS22EyfF7xE0uQb-TJ1dkbVYIlgLfNbFyfNtTRTbnv_3_rExQZBLjDlHcC1lOCXp2CmzySDwkkJASqFa6xKUzOoW06X7m48JJJXHIkB1HbeqOwBPgBOo9JayKwlymybIT4Jy-pOWMO-0T8Tn37QTHsgO0yUuykn6-Zffz2TgFvKiitFnQa3T5qrhx1hy1Kj4DstBpOT_OI0x8fSKkjKIxyNUu6EIJnDKlvW5PvI9DUk9RIBLMFQEJNwFUSnSPdJS4pH97I11iY5jxD9FHThReuUJRFmqzNZK7dw8_edi7zeTAdIy-RYY3gO6mSLkASGksyhsVtfYNWkEGvrAXveyDcD4Qx5fNcCMkGmHDG8YlmR9BEDNxjrU0eE2FIWPeFFn8U1MsO71MCpO0naMBetIjQ9bBc8oALeini5vcwe7aWD0NqkFqOUZdH4ucf0hLiVgYjyVWGCYcAWjQc4keHtUXT1fp8coc_IntUN4yb3FBmu7jI94XL3I4uL_WA1PS9S7FizZF0FdgnNGmEewDYvrRz1oVDb87Lt6ms9NvJQAtFEbp2orXQ7fGumWAU2ao6PC1DUPwA9oHY-c8pk9UkS-z8klzyxKEfYvGYagXn8qVqwcRLTmjXcfs3BPIv1UG1-OZHlG__IwKfZ5ZKThQZi4d9VW37AyaxDXAdXCaslpGsag3TIYuB_aJ5dOMhk-BCfoDVzHnXBHfwfBlu8ZWBrrbSQCB08xfpNGqb87bBXlhllf-fduPOhOBrCAxX4jiqJx-hFzZbXyoFKbgqCW112Sj0OSl9f0ErLT97nIjoRclNnTOJ9JrqbMNYjKuwAJSmZWvIie6j5C4sN_fI-JLxofIGRE4fn7r1ww_rNDivgh0F_LGIB0SP5JMvw1whFMFfzRU8W1OVo3nIrzE51mZzC7RVae-GmTzVU2XLVPR-4CDQVGM8KvCpF-0o--2uWkIqWxdYIu-VYeJ818i-U_Xx5t8aRzEd6G77CXeybupqoklYS0Cx0CGsTVefncWJhepHEnIDSKBROLCsA8rzwpjmw_9WV5BC1RWFjIS03I6GZehhSIta52nYoCMGJ1RPYAY-2xS3mYFtd09HSzChdW2j_XfxQxJtX4r1qITcQTwIJAjNKUcj7dQJtVGcPUcJxGZMgx0-XTT6xrq0EYvdMsdA9DQE7uD81nLvye1KVnyMSNGo8MqKW41M-QOAyG9i6erbk1YIAqyIpRx0L6_vRi8OLGd0ehaF6tOXJBKt9PpVscjn2SI91BmiHIhosbs8psNVdMfM2H4pVkPcE6Y4twTTsV30b1CixD7ZglHlm4S7CcNtSHMoV9-SjX4EavmiisyANUZB1gYnO7IhoNFjke-iGU22lRfqnaC_U7JoQHjjrm5U-uDFjexKmTnXTr3ATcrbvc_Lq6tB5grU9bIeKsA1m_9inDBQj4WKIjwG9iggwRnySNjjzXfGY6PTKpzUUJbyPzWBFfN7xvzS6ftcmEDDj8H4o_J5telVDMX42Qp2QutmwxayuJ1cyNSsKS245yxyd9ieU-Bv1seQ5wo4aZHvMYb66JSFuVDE4bJmOLUwkjuGqX_BQ271IEauqynSIzWgKVRE1FLYs1bbUWVyCNgdsEy9tnVlJIEQB4mtjnmXhmZTpqS7LHFxhx0Hitm0cYeGB38FUT1S82a90f1kzgWmRMGRvRIXrS0VrbhdHWddjUa2lJ8qPDtnXU_2drPfj5FABGdc8a8pU2sRnfRCOzi5L8u-aKmp5s1DbHFIjSDXwX3m6W5QcodcOOTwyMwWYJ--Peo3eXOBdiYZ7w0SkKvhS82ElrhSKA1gZgjEh5Yg_RS53wLeLkclYu5C6Uwa5aiaJiHpIDzLjRSv-7scmysmeI9l5d-1UBqvmCQGN8tOK0Ua19--KzK3-GDANE0su3befKZGck5-7OiWHl5wA2Vwd5Wk3RQ2c49cvl8S3lbrLNCBH7VdDTIkdVCzAJQY7NWbK3P_NuXKdmh-R6MUz-oZWVK8lMiQkWHz7Mqlckz2yhZy3KHD_LquJpuTcwn_T1GDg6gZuR-IK_BadU5nu8xMHyGn688xxhgr3ohp3TtFWbRsBUV8p326FWlKVIqucXsY2QlZ3GXIDdtZKmpMSrm6FPW__n91LydrScwdAN_nxN65ks3hIBZhG8pisa3DUK61o_dEPJBK1PavWAJLfdfP05agnenzjYw42lEcj_-vF2xl3tLvomJImouYPRU5D3B2rxIc-E8jBrFr33kxZ9sND3DLs9C22g8_10MrZNcJBW6sq22kvIrtLBX7n8F7qlOFL7FwqztTrvNGCktlUqn9tVrxLV6UAI068V0qbm3K33LejN95_ksgSA3CWjqScBuW-OMFtUZol4sP-BCycI5_iIUqqDYb3TIejs4wKDBXAq5wHTw2Yt1oro4PlKu1wudpAYccF7RZUA==", "id": "rs_031120460a6c5445016a034e6fd9648191947508f13caca756", "summary": [] } ], "tool_calls": [ { "id": "call_yCGmtlQjM9QhvMv0UsRbY9rO", "call_id": "call_yCGmtlQjM9QhvMv0UsRbY9rO", "response_item_id": "fc_031120460a6c5445016a034ead27ec81918fe9f5b9fa1575f9", "type": "function", "function": { "name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\" AND upper(COALESCE(category,'')) NOT IN ('LABOR','PROFIL','BEFUNDE')\",\"old_string\":\" AND upper(COALESCE(category,'')) NOT IN ('LABOR','PROFIL')\",\"path\":\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"}" } } ] }, { "role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n+++ b//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n@@ -158,7 +158,7 @@\\n FROM health_events\\n WHERE date IS NOT NULL\\n AND date(date) IS NOT NULL\\n- AND upper(COALESCE(category,'')) NOT IN ('LABOR','PROFIL')\\n+ AND upper(COALESCE(category,'')) NOT IN ('LABOR','PROFIL','BEFUNDE')\\n ORDER BY date\\n \\\"\\\"\\\"))\\n symptoms = list(c.execute(\\\"SELECT datum,kategori,symptom,schwergrad,notizen FROM symptome WHERE date(datum) IS NOT NULL ORDER BY datum\\\"))\\n\", \"files_modified\": [\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}", "tool_call_id": "call_yCGmtlQjM9QhvMv0UsRbY9rO" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "tool_calls": [ { "id": "call_3xSvcYUajUn36DLPlYMfhk5v", "call_id": "call_3xSvcYUajUn36DLPlYMfhk5v", "response_item_id": "fc_0ef131dab49fa416016a034eb35074819183d78fd9312149bf", "type": "function", "function": { "name": "patch", "arguments": "{\"mode\":\"replace\",\"new_string\":\"

Klinische Events, Medikamente & Symptome

{event_rows}{symptom_rows}
DatumKategorieParameter/SymptomWert/Notiz
\",\"old_string\":\"

Health Events & Symptome

{event_rows}{symptom_rows}
DatumKategorieParameter/SymptomWert/Notiz
\",\"path\":\"/home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\"}" } } ] }, { "role": "tool", "name": "patch", "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n+++ b//home/agent/.hermes/assets/Gesundheit/scripts/health_dashboard_v3.py\\n@@ -244,7 +244,7 @@\\n {nutrition_rows}
DatumScoreerkannte Risikenpositive Treffer
\\n

Health Event Periods / Zeiträume

{period_rows}
StartEndeTypLabelSchweregradNotizen
\\n

Laborberichte / Original-PDFs

{lab_doc_rows}
IDOriginalStatus
\\n-

Health Events & Symptome

{event_rows}{symptom_rows}
DatumKategorieParameter/SymptomWert/Notiz
\\n+

Klinische Events, Medikamente & Symptome

{event_rows}{symptom_rows}
DatumKategorieParameter/SymptomWert/Notiz
\\n

Letzte Dokumente

{doc_rows}
IDDateiKategorieStatusReviewVolltext-Zeichen
\\n