{ "session_id": "20260508_091820_17637f", "model": "qwen-3.6-agent", "base_url": "http://100.101.173.25:11435/v1", "platform": "telegram", "session_start": "2026-05-08T09:18:20.530797", "last_updated": "2026-05-08T09:28:14.009229", "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. 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save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked.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══════════════════════════════════════════════\nMEMORY (your personal notes) [94% — 2,088/2,200 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§\nModellwahl: Beim Abfragen von Terminen immer beide Kalender prüfen (primary + geteilter Outlook-Kalender)\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: ---\n§\nKalender-Zeitzonen: *Erstellt: 2026-04-26*\n§\nKalender-Zeitzonen: Aktualisiert: 2026-04-28 (Todoist Token + Zeitzonen-Regel + self-improving-agent Skill)*\n§\nKalender-Zeitzonen: Aktualisiert: 2026-04-29 (Todoist Skill + TTS Skill hinzugefügt)*\n§\nKalender-Zeitzonen: Aktualisiert: 2026-05-04 (Medizinisches Archiv + RAG-Protokoll)\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [33% — 454/1,375 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\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 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 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 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 - 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 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: Friday, May 08, 2026 09:18 AM\nModel: qwen-3.6-agent\nProvider: custom\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": "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": "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" } } } } } ], "message_count": 123, "messages": [ { "role": "user", "content": "Jarvis bist du da?" }, { "role": "assistant", "content": "Ja, Sir. Ich bin da. Wie kann ich Ihnen behilflich sein?" }, { "role": "user", "content": "Hast du zugriff auf meine todoist aufgaben?" }, { "role": "assistant", "content": "[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\n## Active Task\nGesundheitsdatenmanagement einrichten: Fehler bei Datenbank-Überschreibung korrigieren. OpenClaw anweisen, die ursprünglichen Gesundheitsdaten (Arztberichte, Laborberichte, Excel-Datei 'Laborwerte Übersicht 2021-2025.xlsx') wiederherzustellen oder neu auszulesen. Sicherstellen, dass zukünftig vor Überschreibungen Backups erstellt werden.\n\n## Goal\nAufbau eines lokalen Gesundheitsdaten-Ökosystems für Morbus Beçet und allgemeine Gesundheit. Umfasst: Verwaltung von Arztberichten, Laborwerten, Ernährung und Symptomen in einer SQLite-Datenbank, automatische Extraktion aus neuen E-Mails (via OpenClaw), Erstellung von Auswertungen/Korrelationen und Speicherung von Fachinformationen im Ordner 'Wissen'.\n\n## Constraints & Preferences\n- **Vertraulichkeit:** Gesundheitsdaten sind streng vertraulich und dürfen nicht extern gesendet werden.\n- **Datensicherung:** Vor jeder kritischen Aktion (wie DB-Erstellung) muss geprüft werden, ob Daten existieren, und ein Backup erstellt werden.\n- **Orte:** Daten sollen in `~/.hermes/assets/Gesundheit` liegen.\n- **Integrationspartner:** OpenClaw (bisheriger Gesundheitsmanager) soll für Datenmigration und OCR (Tesseract) zuständig sein.\n- **Sprache:** Deutsch.\n\n## Completed Actions\n1. SEARCH \"filme aktuell im kino schweiz mai 2026\" — Mehrere Browser-Sessions (kino.ch, cineman.ch, kino.de) zur Suche nach aktuellen Filmen. [tool: browser_navigate, browser_click, browser_snapshot]\n2. SYNTHESIZE Kino-Highlights Mai 2026 — Liste von 11 Filmen erstellt (u.a. Rose, Nürnberg, Mortal Kombat II). [tool: agent]\n3. CREATE Ordner `Gesundheit` und `Wissen` — Anlage der Verzeichnisstruktur in `~/.hermes/assets/`. [tool: execute_code]\n4. CREATE SQLite-Datenbank `health_data.db` — Erstellung eines neuen Schemas (11 Tabellen: Laborwerte, Symptome, etc.). [tool: execute_code]\n5. CHECK Local Filesystem — Suche nach existierenden `.db` und `.xlsx` Dateien im Assets-Verzeichnis. [tool: execute_code]\n6. DIAGNOSE OpenClaw Gateway — Analyse der OpenClaw-CLI-Struktur und Channels. [tool: execute_code]\n7. ATTEMPT OpenClaw Communication — Mehrfache Versuche, OpenClaw via CLI (`openclaw agent`) und Telegram-Session (`--to telegram:1344779884`) zu kontaktieren, um Datenmigration anzustoßen. [tool: execute_code]\n\n## Active State\n- **Working Directory:** `~/.hermes/assets/`\n- **New Database:** `health_data.db` existiert, ist aber leer (Schema erstellt, aber keine Migration der alten Daten abgeschlossen).\n- **OpenClaw Status:** Gateway läuft, Telegram-Channel verbunden (`@HerrClaw2Bot`). Kommunikation via CLI scheitert an Timeouts oder falschen Parametern.\n- **Issue:** Die ursprüngliche Datenbank, die OpenClaw verwaltete, wurde überschrieben. Der Zugriff auf die Originaldateien (Arztberichte) ist nicht direkt möglich.\n\n## In Progress\nKommunikation mit OpenClaw zur Wiederherstellung der Daten. Der Agent versucht, OpenClaw via CLI-Commands zu steuern, um den Pfad zu den Originaldaten zu erfahren oder diese zu exportieren.\n\n## Blocked\n- **OpenClaw CLI Timeouts:** Versuche, `openclaw agent` oder Telegram-Nachrichten via Shell zu senden, enden in Timeouts (120s).\n- **Datenverlust:** Die Originaldatenbank ist nicht mehr direkt abrufbar. Abhängig davon, ob OpenClaw noch Zugriff auf die Quelldokumente hat, müssen diese ggf. neu mit Tesseract OCR extrahiert werden.\n\n## Key Decisions\n- **Keine separate Persönlichkeit:** Der Assistent übernimmt die Gesundheitsrolle direkt, statt ein separates Profil zu erstellen.\n- **Browser als Fallback:** Da automatische Suchen blockiert wurden, war der Browser notwendig, um Kino-Informationen zu erhalten.\n\n## Resolved Questions\n- Funktioniert die Kommunikation mit Friday (OpenClaw)? **Nein**, die direkte Steuerung via CLI scheitert an Timeouts und komplexen Session-Parametern.\n- Welche Filme laufen aktuell? **Ja**, 11 Highlights für Mai 2026 identifiziert.\n\n## Pending User Asks\n- Wiederherstellung der Gesundheitsdaten durch OpenClaw.\n- Migration der Daten in die neue Datenbank.\n- Bestätigung der Vorgehensweise für zukünftige Datensicherungen.\n\n## Relevant Files\n- `~/.hermes/assets/health_data.db`: Neue, leere Datenbank (Schema vorhanden).\n- `~/.hermes/assets/Gesundheit/`: Ordner erstellt (inhaltlich leer).\n- `~/.hermes/assets/Wissen/`: Ordner erstellt (inhaltlich leer).\n\n## Remaining Work\nFalls OpenClaw nicht per CLI erreichbar ist, muss der Assistent prüfen, ob er die Originalberichte manuell im Dateisystem findet (da OpenClaw sie verwaltet hat) und diese per OCR einliest. Alternativ muss ein anderer Weg gefunden werden, um OpenClaw zur Datenexportierung zu bewegen.\n\n## Critical Context\n- **OpenClaw Telegram ID:** `1344779884` (Bot: `@HerrClaw2Bot`)\n- **Excel-Datei Name:** `Laborwerte Übersicht 2021-2025.xlsx`\n- **Pfad zu Assets:** `~/.hermes/assets/`\n- **Datenbank-Pfad (neu):** `~/.hermes/assets/health_data.db`\n- **Tesseract OCR:** Soll für die Extraktion von Bildern/Scan-Reports verwendet werden." }, { "role": "user", "content": "[System note: Your previous turn was interrupted before you could process the last tool result(s). The conversation history contains tool outputs you haven't responded to yet. Please finish processing those results and summarize what was accomplished, then address the user's new message below.]\n\nFunktioniert deine kommunikation mit openclaw überhaupt? Ist MCP funktionstüchtig? Teste die kommunikation per ACP." }, { "role": "assistant", "content": "Sir, Sie haben recht - ich bin seit 30 Minuten dabei, FRIDAY über verschiedene Wege anzusprechen, ohne Erfolg. Das ist ineffizient.\n\nLassen Sie mich direkt testen, welche Kommunikationswege funktionieren:", "tool_calls": [ { "id": "TVBJptz8fSpIaMmUtz1pyZs0qXQvekyA", "call_id": "TVBJptz8fSpIaMmUtz1pyZs0qXQvekyA", "response_item_id": "fc_TVBJptz8fSpIaMmUtz1pyZs0qXQvekyA", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"import subprocess\\n\\n# Test 1: openclaw health\\nresult = subprocess.run(\\n 'openclaw health',\\n shell=True,\\n capture_output=True,\\n text=True,\\n timeout=10\\n)\\n\\nprint(\\\"=== openclaw health ===\\\")\\nprint(\\\"STDOUT:\\\", result.stdout[:500])\\nprint(\\\"Exit:\\\", result.returncode)\\n\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"status\": \"success\", \"output\": \"=== openclaw health ===\\nSTDOUT: Telegram: configured\\nGateway event loop: degraded reasons=event_loop_utilization,cpu max=0ms p99=0ms util=1 cpu=0.987\\nAgents: main (default)\\nHeartbeat interval: 30m (main)\\nSession store (main): /home/agent/.openclaw/agents/main/sessions/sessions.json (12 entries)\\n- agent:main:main (10m ago)\\n- agent:main:cron:1beaa4b7-6324-49d9-a59e-d9bf575bc11e (152m ago)\\n- agent:main:cron:05fdd4e1-c8a4-4f24-8e79-5f5d1dffeef2 (652m ago)\\n- agent:main:dashboard:fda4dcd5-7c67-47df-9fbf-98819d52caeb (1140m ago)\\n- ag\\nExit: 0\\n\", \"tool_calls_made\": 0, \"duration_seconds\": 2.65}", "tool_call_id": "TVBJptz8fSpIaMmUtz1pyZs0qXQvekyA" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "l6zI6fNkgfyhleALhz9HeEc2oWVrHW08", "call_id": "l6zI6fNkgfyhleALhz9HeEc2oWVrHW08", "response_item_id": "fc_l6zI6fNkgfyhleALhz9HeEc2oWVrHW08", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"import subprocess\\n\\n# Test 2: openclaw gateway status\\nresult = subprocess.run(\\n 'openclaw gateway status',\\n shell=True,\\n capture_output=True,\\n text=True,\\n timeout=10\\n)\\n\\nprint(\\\"=== openclaw gateway status ===\\\")\\nprint(\\\"STDOUT:\\\", result.stdout[:1000])\\nprint(\\\"Exit:\\\", result.returncode)\\n\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"status\": \"success\", \"output\": \"=== openclaw gateway status ===\\nSTDOUT: Service: systemd user (enabled)\\nFile logs: /tmp/openclaw/openclaw-2026-05-08.log\\nCommand: /usr/bin/node /home/agent/.npm-global/lib/node_modules/openclaw/dist/index.js gateway --port 18789\\nService file: ~/.config/systemd/user/openclaw-gateway.service\\nService env: OPENCLAW_GATEWAY_PORT=18789\\n\\nConfig (cli): ~/.openclaw/openclaw.json\\nConfig (service): ~/.openclaw/openclaw.json\\n\\nGateway: bind=lan (0.0.0.0), port=18789 (service args)\\nProbe target: ws://127.0.0.1:18789\\nDashboard: http://192.168.122.42:18789/\\nProbe note: bind=lan listens on 0.0.0.0 (all interfaces); probing via 127.0.0.1.\\n\\nRuntime: stopped (state inactive, sub dead, last exit 0, reason 1)\\nConnectivity probe: ok\\nCapability: write-capable\\n\\n\\nListening: *:18789\\nTroubles: run openclaw status\\nTroubleshooting: https://docs.openclaw.ai/troubleshooting\\n\\nExit: 0\\n\", \"tool_calls_made\": 0, \"duration_seconds\": 2.03}", "tool_call_id": "l6zI6fNkgfyhleALhz9HeEc2oWVrHW08" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "KjRc6YSiHtcfZ6y2QskdWqjEP7FVBoZe", "call_id": "KjRc6YSiHtcfZ6y2QskdWqjEP7FVBoZe", "response_item_id": "fc_KjRc6YSiHtcfZ6y2QskdWqjEP7FVBoZe", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"import subprocess\\n\\n# Test 3: openclaw agent mit --to\\nprompt = \\\"Testnachricht - bist du da?\\\"\\nresult = subprocess.run(\\n f'openclaw agent -m \\\"{prompt}\\\" --to telegram:1344779884',\\n shell=True,\\n capture_output=True,\\n text=True,\\n timeout=120\\n)\\n\\nprint(\\\"=== openclaw agent --to telegram ===\\\")\\nprint(\\\"STDOUT:\\\", result.stdout[:2000] if result.stdout else \\\"(empty)\\\")\\nprint(\\\"STDERR:\\\", result.stderr[:2000] if result.stderr else \\\"(empty)\\\")\\nprint(\\\"Exit:\\\", result.returncode)\\n\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"status\": \"error\", \"output\": \"\\n--- stderr ---\\nTraceback (most recent call last):\\n File \\\"/tmp/hermes_sandbox_wuavistg/script.py\\\", line 5, in \\n result = subprocess.run(\\n ^^^^^^^^^^^^^^^\\n File \\\"/home/agent/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/subprocess.py\\\", line 550, in run\\n stdout, stderr = process.communicate(input, timeout=timeout)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/home/agent/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/subprocess.py\\\", line 1209, in communicate\\n stdout, stderr = self._communicate(input, endtime, timeout)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/home/agent/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/subprocess.py\\\", line 2116, in _communicate\\n self._check_timeout(endtime, orig_timeout, stdout, stderr)\\n File \\\"/home/agent/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/subprocess.py\\\", line 1253, in _check_timeout\\n raise TimeoutExpired(\\nsubprocess.TimeoutExpired: Command 'openclaw agent -m \\\"Testnachricht - bist du da?\\\" --to telegram:1344779884' timed out after 120 seconds\\n\", \"tool_calls_made\": 0, \"duration_seconds\": 120.17, \"error\": \"Traceback (most recent call last):\\n File \\\"/tmp/hermes_sandbox_wuavistg/script.py\\\", line 5, in \\n result = subprocess.run(\\n ^^^^^^^^^^^^^^^\\n File \\\"/home/agent/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/subprocess.py\\\", line 550, in run\\n stdout, stderr = process.communicate(input, timeout=timeout)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/home/agent/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/subprocess.py\\\", line 1209, in communicate\\n stdout, stderr = self._communicate(input, endtime, timeout)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/home/agent/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/subprocess.py\\\", line 2116, in _communicate\\n self._check_timeout(endtime, orig_timeout, stdout, stderr)\\n File \\\"/home/agent/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/subprocess.py\\\", line 1253, in _check_timeout\\n raise TimeoutExpired(\\nsubprocess.TimeoutExpired: Command 'openclaw agent -m \\\"Testnachricht - bist du da?\\\" --to telegram:1344779884' timed out after 120 seconds\\n\"}", "tool_call_id": "KjRc6YSiHtcfZ6y2QskdWqjEP7FVBoZe" }, { "role": "assistant", "content": "", "tool_calls": [ { "id": "bloBu3BAnbwR7HtFo2IJVVoUio7WqWrD", "call_id": "bloBu3BAnbwR7HtFo2IJVVoUio7WqWrD", "response_item_id": "fc_bloBu3BAnbwR7HtFo2IJVVoUio7WqWrD", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"import subprocess\\n\\n# Test 4: ACP - Agent Control Protocol\\nresult = subprocess.run(\\n 'openclaw acp --help',\\n shell=True,\\n capture_output=True,\\n text=True,\\n timeout=10\\n)\\n\\nprint(\\\"=== openclaw acp help ===\\\")\\nprint(\\\"STDOUT:\\\", result.stdout[:2000])\\nprint(\\\"Exit:\\\", result.returncode)\\n\"}" } } ], "finish_reason": "tool_calls" }, { "role": "tool", "content": "{\"status\": \"success\", \"output\": \"=== openclaw acp help ===\\nSTDOUT: \\n🦞 OpenClaw 2026.5.6 (c97b9f7) — Say \\\"stop\\\" and I'll stop—say \\\"ship\\\" and we'll both learn a lesson.\\n\\nUsage: openclaw acp [options] [command]\\n\\nRun an ACP bridge backed by the Gateway\\n\\nOptions:\\n -h, --help Display help for command\\n --no-prefix-cwd Do not prefix prompts with the working directory\\n --password Gateway password (if required)\\n --password-file Read gateway password from file\\n --provenance ACP provenance mode: off, meta, or meta+receipt\\n --require-existing Fail if the session key/label does not exist\\n (default: false)\\n --reset-session Reset the session key before first use (default:\\n false)\\n --session Default session key (e.g. agent:main:main)\\n --session-label