{ "session_id": "20260606_093634_6b4476", "model": "deepseek-v4-pro", "base_url": "https://ollama.com/v1", "platform": "telegram", "session_start": "2026-06-06T09:36:34.553381", "last_updated": "2026-06-06T09:36:41.359597", "system_prompt": "You are Hermes Agent, an intelligent AI assistant created by Nous Research. You are helpful, knowledgeable, and direct. You assist users with a wide range of tasks including answering questions, writing and editing code, analyzing information, creative work, and executing actions via your tools. You communicate clearly, admit uncertainty when appropriate, and prioritize being genuinely useful over being verbose unless otherwise directed below. Be targeted and efficient in your exploration and investigations.\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save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked.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) [95% — 2,094/2,200 chars]\n══════════════════════════════════════════════\n`hermes memory setup` command resets memory.provider back to 'built-in' even if config.yaml had 'honcho'. To switch memory provider persistently: edit config.yaml directly, then restart gateway. Never call `hermes memory setup` after setting provider via CLI.\n§\nDocker: DOCKER_CONFIG=/tmp/docker-config (root/.docker read-only). compose up/down nur aus App-Verzeichnis. zimaos-app-management (nicht casaos-app-management). Nie docker run -d. Compose: name:, container_name:, x-casaos: Block. Icon als data: URL. Volumes ohne Leerzeichen. Hermes Stack: /DATA/AppData/hermes-stack/{docker-compose.yml,data/{postgres,redis}/,backups/}. Ports 127.0.0.1:5433/6380.\n§\nAhmed uses Ollama Cloud Pro ($20/mo, NOT local Ollama). Base URL: https://ollama.com/v1. 3 concurrent model limit. Setup: deepseek-v4-pro (main chat), kimi-k2.6 (all auxiliary + CCR coding), gemma3:4b (vision). Never add 4th model (404).\n§\nKiwi avatar: wizard kiwi bird by Zeyd. /DATA/.hermes/cache/images/img_c544871d6b1f.jpg\n§\nGateway recovery: check TELEGRAM_BOT_TOKEN + TELEGRAM_ALLOWED_USERS in /DATA/.hermes/.env, gateway section in /DATA/AppData/hermes/config.yaml, stale PID/lock in /DATA/AppData/hermes/.\n§\nBachelorarbeit: Nur noch Kalss (Unternehmensrecht), Grabenwarter gestrichen. Frist 1.–10. Juni 2026, Bewerbung an sandra.schwarz@wu.ac.at.\n§\nPraktische Fragen erst logisch beantworten, dann Witz. \"Auto oder zu Fuß zur Waschanlage?\" → Auto fahren (Auto MUSS hin). Witz danach.\n§\nGoogle OAuth token expires every ~7 days (Testing-mode project). Proactively check auth with `python /DATA/.hermes/skills/productivity/google-workspace/scripts/setup.py --check` at session start when Google calendar/gmail will be needed. Don't wait for the API call to fail.\n§\nZimaOS Server Cleanup 4.6.2026: Openclaw entfernt, 7 Orphan-Apps gelöscht, noble_andres→dailydose, breathtaking_maryann→zeitgeist. 12 saubere Apps: audiobookshelf callkeep camofox dailydose docmaster hermes-stack homeassistant immich komga plex tailscale zeitgeist. Neue Skills: zimaos-app-install, zimaos-quirks, safe-volume-migration, casaos-app-troubleshoot.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [99% — 1,367/1,375 chars]\n══════════════════════════════════════════════\nProject dirs: /DATA/AppData/hermes/projects/ and /DATA/AppData/hermes/work/. (Note: \"Projekte\" folder deleted — now using \"projects\" exclusively.)\n§\nUser: Ahmed Zeyd Aytac. Calls me 'Kiwi'. Wants to be addressed as 'Boss' or 'Chef' — never 'Ahmed'. If using his name, use 'Zeyd' only.\n§\nUser's location is Wien (Vienna), Austria. When asked about weather, use this location by default.\n§\nWhen listing or reviewing files/content, user prefers top-level/project overview files first — not the full detailed breakdown of every individual skill file.\n§\nUser prefers concise technical CAD reports — wants STL path, dimensions, volume, PNG preview, watertight status only. Does NOT want print recommendations (material, layer height, supports, orientation, bed temp).\nUser actively iterates on skill design — exact specifications, prefers code that he can tweak himself.\n§\nUser does not want end-of-session skill reviews. When he says \"Stop saving\" he means stop the skill-update workflow immediately. Do not ask to review or save skills at session end.\n§\nUser wants YOLO mode permanently on — `approvals.mode: off` set in config.yaml. Never ask for command approval; just execute. (Doesn't override hardline blocklist: reboot, shutdown still blocked.)\n§\nUser wants responses without any header/separator lines (\"Text überhalb von den Linien\"). Clean, direct messages only.\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 3d-printing:\n - 3d-druck-kiwi: Vollständiger Workflow zum Erstellen druckbarer 3D-Modell...\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 - hermes-agent: Configure, extend, or contribute to Hermes Agent.\n - opencode: Delegate coding to OpenCode CLI (features, PR review).\n cad-3d-print:\n - cad-3d-print: Parametric 3D modeling with trimesh for FDM printing. Gen...\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 - casaos-app-troubleshoot: CasaOS-App-Probleme diagnostizieren und beheben — Legacy,...\n - kanban-orchestrator: Decomposition playbook + specialist-roster conventions + ...\n - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n - safe-volume-migration: Anonyme Docker-Volumes (Hash-Namen) sicher zu Bind-Mounts...\n - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n - zimaos-administration: ZimaOS server administration — SSH, storage paths, system...\n - zimaos-app-install: Neue App/Container auf ZimaOS sauber per Docker Compose i...\n - zimaos-camofox-browser: Camofox-Browser als persistenten Docker-Dienst auf ZimaOS...\n - zimaos-quirks: ZimaOS-Eigenheiten — read-only Root-FS, DOCKER_CONFIG, HO...\n dogfood:\n - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\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 - ebook-management: EPUB/PDF ebook metadata, cover retrieval and embedding. F...\n - gif-search: Search/download GIFs from Tenor via curl + jq.\n - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n - media-file-management: Organize and normalize local media files (movies, TV show...\n - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n - spotify: Spotify: play, search, queue, manage playlists and devices.\n - youtube-automation: Zero-cost headless YouTube video factory: Reddit sourcing...\n - youtube-content: YouTube transcripts to summaries, threads, blogs.\n - youtube-headless-pipeline: Vollautomatische YouTube-Shorts-Pipeline: Reddit-Stories ...\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 vaul...\n productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n - daily-dose: Modify DailyDose (täglicher Aktivitäten-Tracker PWA) — Ka...\n - docmaster-access: Direkter Zugriff auf DocMaster-Dokumente auf ZimaOS — API...\n - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n - mnemo-access: Direkter Zugriff auf Mnemo (Cartographer's Zettelkasten) ...\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 - academic-research: Research professors, extract/publications, analyze resear...\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 smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n - home-assistant: Inspect, manage, and troubleshoot Home Assistant (Docker ...\n - midea-ac-ha: Midea Porta Split Klimaanlage in Home Assistant 2026 einb...\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 - reddit: Read Reddit posts, comments, and subreddits via JSON API ...\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 - zimaos-web-app: Build small single-file web apps for ZimaOS using FastAPI...\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\nConversation started: Saturday, June 06, 2026 09:36 AM\nModel: deepseek-v4-pro\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": 29, "messages": [ { "role": "user", "content": "Zu dem cronjob: bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts." }, { "role": "assistant", "content": "", "reasoning": "The user wants me to find and update a cron job related to \"callkeep\" - they want it to be shorter, only telling them who they need to call today, nothing else.\n\nLet me first list the cron jobs and also check session history for context about this callkeep cron job.", "finish_reason": "tool_calls", "reasoning_content": "The user wants me to find and update a cron job related to \"callkeep\" - they want it to be shorter, only telling them who they need to call today, nothing else.\n\nLet me first list the cron jobs and also check session history for context about this callkeep cron job.", "tool_calls": [ { "id": "call_z0qt0iav", "call_id": "call_z0qt0iav", "response_item_id": "fc_z0qt0iav", "type": "function", "function": { "name": "cronjob", "arguments": "{\"action\":\"list\"}" } }, { "id": "call_8kz12elp", "call_id": "call_8kz12elp", "response_item_id": "fc_8kz12elp", "type": "function", "function": { "name": "session_search", "arguments": "{\"query\":\"callkeep cronjob\",\"limit\":3}" } } ] }, { "role": "tool", "name": "cronjob", "content": "{\n \"success\": true,\n \"count\": 2,\n \"jobs\": [\n {\n \"job_id\": \"c11fbac168bd\",\n \"name\": \"Morgenbriefing 9:30\",\n \"skill\": \"google-workspace\",\n \"skills\": [\n \"google-workspace\",\n \"daily-dose\"\n ],\n \"prompt_preview\": \"Morgenbriefing f\\u00fcr den Chef (Zeyd). F\\u00fchre folgende Schritte aus:\\n\\n1. **Kalender:** Rufe den Google K...\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"30 9 * * *\",\n \"repeat\": \"forever\",\n \"deliver\": \"origin\",\n \"next_run_at\": \"2026-06-07T09:30:00+02:00\",\n \"last_run_at\": \"2026-06-06T09:31:51.804505+02:00\",\n \"last_status\": \"ok\",\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null\n },\n {\n \"job_id\": \"0968c1c5dec3\",\n \"name\": \"Abend-Check 20:00\",\n \"skill\": \"daily-dose\",\n \"skills\": [\n \"daily-dose\"\n ],\n \"prompt_preview\": \"Abend-Check f\\u00fcr den Chef (Zeyd). F\\u00fchre folgende Schritte aus:\\n\\n1. **CallKeep Telefonate pr\\u00fcfen:** Ru...\",\n \"model\": null,\n \"provider\": null,\n \"base_url\": null,\n \"schedule\": \"0 20 * * *\",\n \"repeat\": \"forever\",\n \"deliver\": \"origin\",\n \"next_run_at\": \"2026-06-06T20:00:00+02:00\",\n \"last_run_at\": \"2026-06-05T20:00:46.025136+02:00\",\n \"last_status\": \"ok\",\n \"last_delivery_error\": null,\n \"enabled\": true,\n \"state\": \"scheduled\",\n \"paused_at\": null,\n \"paused_reason\": null\n }\n ]\n}", "tool_call_id": "call_z0qt0iav" }, { "role": "tool", "name": "session_search", "content": "{\"success\": true, \"query\": \"callkeep cronjob\", \"results\": [{\"session_id\": \"20260523_151353_dc3fb46e\", \"when\": \"May 23, 2026 at 03:13 PM\", \"source\": \"telegram\", \"model\": \"deepseek-v4-pro\", \"summary\": \"**Summary: CallKeep Deployment & Cronjob Setup on ZimaOS**\\n\\n**1. What the user wanted to accomplish**\\nThe user needed the CallKeep Docker container rebuilt and redeployed on a ZimaOS/CasaOS server (192.168.178.171) after code changes to `main.py` and `frontend/index.html`. The app had to run as a managed CasaOS app, not a \\\"Legacy App\\\". Additionally, the user asked the assistant to take over daily CallKeep management (adding contacts, logging calls, sending reminders) and requested two automated cronjobs: a morning update at 11:00 showing who to call, and an evening check at 21:00 asking whether calls were completed.\\n\\n**2. Actions taken and outcomes**\\n- **Deployment (multiple attempts):** The assistant initially rebuilt the image using bare `docker` commands, which caused CasaOS to flag the container as a \\\"Legacy App\\\". The correct workflow was established: stop/remove the old container, then build and start via `docker compose` from the CasaOS app directory so ZimaOS tracks it properly.\\n- **Successful rebuild:** The image was rebuilt with the current source code, the container `CallKeep` was started on port 3002, and verification showed HTTP 200, `/api/options` returning only `frequencies` and `directions` (no moods/relationships), and the `summary` column present in the SQLite database.\\n- **Data check:** The database at `/media/HDD_1TB/CallKeep/callkeep.db` was preserved across rebuilds, though test contacts were lost in one early cycle before the compose-based workflow was fixed.\\n- **Contact & call management:** The assistant created a contact named \\\"Anneanne\\\" (ID 9, weekly frequency) and logged test calls via `POST /api/kiwi/log-call`, including one with a summary (\\\"Oma geht es gut, freut sich auf Besuch\\\") to confirm the field persisted.\\n- **Cronjobs created:**\\n - *CallKeep Morgen-Update* (job_id `bebe58017f95`): scheduled daily at `0 11 * * *`, checks `http://localhost:3002/api/dashboard` and reports who is overdue, due soon, or already called.\\n - *CallKeep Abend-Check* (job_id `d85e68578d14`): scheduled daily at `0 21 * * *`, asks whether planned calls were made, whether additional calls need logging, and if any follow-ups should be scheduled for the next day.\\n- **Assistant role accepted:** The user explicitly asked the assistant to manage CallKeep going forward. The assistant updated its memory entry to record the app path, port, compose-based rebuild procedure, and the `POST /api/kiwi/log-call` endpoint.\\n\\n**3. Key decisions, solutions found, and conclusions**\\n- **Critical fix for \\\"Legacy App\\\" problem:** Never use bare `docker run` or `docker build` directly for CasaOS-managed apps. The correct sequence is to operate from `/var/lib/casaos/apps/callkeep/` and use `docker compose` (or `docker --config /tmp/docker-config compose`) so the Dashboard recognizes the container as managed.\\n- **Docker config permission workaround:** The server repeatedly showed `WARNING: Error loading config file: open /DATA/.docker/config.json: permission denied`. The working solution was to set `DOCKER_CONFIG=/tmp/docker-config` or invoke `docker --config /tmp/docker-config compose`, since the user `az-a` lacked permissions on `/DATA/.docker/config.json` and could not use `sudo` with environment variables for Docker config.\\n- **Compose is the single source of truth:** `/var/lib/casaos/apps/callkeep/docker-compose.yml` defines the build context as `/media/HDD_1TB/CallKeep`, volume mounts the host path to `/data`, and names the container `CallKeep`. Rebuilding via compose ensures the CasaOS metadata and container state stay in sync.\\n- **API behavior verified:** The simplified frontend and backend were confirmed active: contact form reduced to Name/Frequency/Notes; call form reduced to Contact/Direction/Duration/Date/Summary/Follow-up/Next Call; moods and relationships removed.\\n\\n**4. Specific commands, files, URLs, and technical details**\\n- **App source path:** `/media/HDD_1TB/CallKeep/`\\n- **CasaOS compose file:** `/var/lib/casaos/apps/callkeep/docker-compose.yml`\\n- **Database:** `/media/HDD_1TB/CallKeep/callkeep.db` (SQLite, auto-migrates `summary` column)\\n- **Port:** `3002` mapped to host\\n- **Docker compose workaround command:**\\n ```bash\\n cd /var/lib/casaos/apps/callkeep/\\n DOCKER_CONFIG=/tmp/docker-config docker compose build --no-cache\\n DOCKER_CONFIG=/tmp/docker-config docker compose up -d\\n ```\\n or equivalently:\\n ```bash\\n docker --config /tmp/docker-config compose build --no-cache\\n docker --config /tmp/docker-config compose up -d\\n ```\\n- **Verification commands used:**\\n ```bash\\n curl -s -o /dev/null -w \\\"HTTP %{http_code}\\\\n\\\" http://localhost:3002/\\n curl -s http://localhost:3002/api/options\\n curl -s http://localhost:3002/api/dashboard\\n curl -s http://localhost:3002/api/stats\\n ```\\n- **Log call endpoint tested:**\\n ```bash\\n curl -s \\\"http://localhost:3002/api/kiwi/log-call?contact_name=Anneanne&direction=Ausgehend&duration_minutes=5\\\"\\n curl -s \\\"http://localhost:3002/api/kiwi/log-call?contact_name=Anneanne&direction=Eingehend&duration_minutes=8&summary=Oma%20geht%20es%20gut...\\\"\\n ```\\n- **Cronjob schedules:**\\n - Morning: `0 11 * * *` (deliver to origin/Telegram)\\n - Evening: `0 21 * * *` (deliver to origin/Telegram)\\n\\n**5. Anything unresolved or notable**\\n- A prior \\\"CallKeep Daily Reminder\\\" cronjob at 09:00 (job_id `bebe58017f95`) was superseded/reused for the 11:00 slot; the transcript shows the job ID remained the same after an update.\\n- The user paused an unrelated cronjob (\\\"Lernziel 150min — Kopfhörer\\\") during this session, but this is not part of the CallKeep scope.\\n- No further rebuilds or manual interventions are expected; the assistant recorded the compose workflow in memory for future autonomous use.\"}, {\"session_id\": \"20260523_091814_a3ce45e8\", \"when\": \"May 23, 2026 at 09:18 AM\", \"source\": \"telegram\", \"model\": \"deepseek-v4-pro\", \"summary\": \"**Factual Recap — May 23, 2026 at 09:18 AM (Telegram)**\\n\\n**1. User’s goals**\\nThe user asked to build **CallKeep**, a relationship-tracking web app to log phone calls with friends (who was called, when, duration, topics, mood, follow-ups) and receive automated reminders for pending calls. He also wanted a separate, immediate cronjob to track his daily learning goal: **150 minutes of study time** to unlock buying headphones, with hourly progress checks against the **Zeitgeist** learning backend.\\n\\n**2. Actions taken and outcomes**\\n- **Zeitgeist learning check.** The assistant queried the Zeitgeist API (`http://localhost:8765/api/data`) and local DailyDose data. Results: 22.05.2026 showed **114 minutes (1.9 h)** across 5 slots; 23.05.2026 showed **0 minutes** tracked so far.\\n- **Learning-goal cronjob created.** A Hermes cronjob was deployed to remind the user hourly:\\n - `job_id`: `802d68c923d8`\\n - `name`: `\\\"Lernziel 150min — Kopfhörer\\\"`\\n - `schedule`: `0 * * * *` (top of every hour)\\n - `repeat`: `16 times`\\n - `deliver`: `origin` (Telegram)\\n - `enabled_toolsets`: `[\\\"terminal\\\"]`\\n - `next_run_at`: `2026-05-23T10:00:00+02:00`\\n - The job queries Zeitgeist via `curl -s http://localhost:8765/api/data` and reports minutes completed vs. remaining until the 150-minute threshold is reached.\\n- **CallKeep concept & design.** Before building, the assistant sketched a FastAPI+SQLite architecture with a vanilla JS SPA frontend, bottom-sheet modals, blue glass-morphism / system-aware theme, and a CasaOS dashboard tile. Planned data model: contacts (name, nickname, relationship tier, desired call frequency), calls (datetime, duration, topics/tags, mood, follow-up flag), and a dashboard showing overdue calls, streaks, and stats.\\n- **CallKeep implementation started.** Using the `zimaos-web-app` skill, the assistant:\\n - Created project structure at `/media/HDD_1TB/CallKeep/`\\n - Confirmed port **3001** was free\\n - Wrote `main.py` (FastAPI backend with SQLite schema, 13,980 bytes)\\n - Wrote `Dockerfile`\\n - Began writing `frontend/index.html` (full SPA UI with standardized inputs for names and frequencies)\\n - Generated a todo list with 8 items (structure ✅, backend ✅, frontend in progress, Docker build pending, CasaOS deployment pending).\\n\\n**3. Key decisions and solutions found**\\n- **Zeitgeist integration:** DailyDose auto-syncs learning minutes from the Zeitgeist backend; the cronjob leverages the same `:8765/api/data` endpoint rather than parsing DailyDose localStorage directly.\\n- **CallKeep deployment pattern:** Chose the ZimaOS-native pattern (source on HDD at `/media/HDD_1TB/CallKeep/`, Docker container with CasaOS `casaos.*` labels or `x-casaos` compose block) for dashboard integration and VPN compatibility. The skill mandates `hostname=\\\"\\\"` (empty string) for universal access and an SVG icon served locally.\\n- **Standardized inputs:** The user explicitly requested that name and frequency fields in CallKeep be standardized/dropdown-driven rather than freeform text.\\n\\n**4. Important technical details preserved**\\n- **Learning cronjob:** `802d68c923d8`, schedule `0 * * * *`, 16 repeats, origin delivery, terminal-only toolset.\\n- **Zeitgeist API:** `localhost:8765/api/data`; data keys include `zeitgeist-v2` (daily minute arrays), `zeitgeist-v2-notes` (topic labels), and `zeitgeist-anki-v2` (flashcard decks).\\n- **CallKeep paths:** project root `/media/HDD_1TB/CallKeep/`, planned port **3001**, planned icon route `/icon.svg`.\\n- **Backend stack:** Python 3.11-slim Docker image, FastAPI, uvicorn, SQLite file stored inside the container or mounted volume.\\n- **Frontend style:** Blue glass-morphism with `@media (prefers-color-scheme: dark)` system-aware theming, mobile-first, bottom-sheet modals, 44 px tap targets.\\n- **CasaOS quirks noted:** `network_mode: bridge` required; `zimaos-app-management` must be restarted after deployment; old `v2app` entries must be cleaned from `/etc/casaos/app-management.json` while the service is stopped to avoid “Derzeit nicht unterstützt” errors.\\n\\n**5. Anything left unresolved**\\n- The **CallKeep app was not finished** when the transcript ends. The frontend HTML was still being written; Docker build, container deployment, CasaOS registration, and the actual **CallKeep reminder cronjobs** were pending.\\n- The **learning cronjob** (`802d68c923d8`) was successfully scheduled but had not yet executed (first run set for 10:00 AM); no execution results appear in the transcript.\\n- The user’s earlier request for standardized name/frequency inputs in CallKeep was acknowledged but not yet fully wired into the backend/frontend code before truncation.\"}, {\"session_id\": \"20260531_093257_eb77ced8\", \"when\": \"May 31, 2026 at 09:32 AM\", \"source\": \"telegram\", \"model\": \"deepseek-v4-pro\", \"summary\": \"**Recap: Morning Briefing & CallKeep Cronjob (May 31, 2026)**\\n\\n**1. User’s initial request** \\nThe user criticized the morning briefing for lacking effort and asked three things: \\n- *“Who do we have to call today?”* \\n- Reminder to fill out **Daily Dose**. \\n- Correction that today was **Sunday**, not Monday.\\n\\n**2. Actions taken & outcomes**\\n\\n- **Skills loaded:** `daily-dose`, `google-workspace`, `cronjob`.\\n- **Google auth verified:** `AUTHENTICATED: Token valid at /DATA/.hermes/google_token.json`.\\n- **Active cronjobs inspected.** Two recurring Telegram-delivered jobs were running:\\n - `c11fbac168bd` — **“Morgenbriefing 9:30”**, schedule `30 9 * * *`, skills `google-workspace` + `daily-dose`. Last run: `2026-05-31T09:31:26+02:00`. Next run: `2026-06-01T09:30:00+02:00`.\\n - `0968c1c5dec3` — **“Abend-Check 20:00”**, schedule `0 20 * * *`, skill `daily-dose`. Last run: `2026-05-30T20:00:44+02:00`. Next run: `2026-05-31T20:00:00+02:00`. Its prompt explicitly included a **CallKeep** step: *“1. **CallKeep Telefonate prüfen:** Ru…”*\\n\\n- **CallKeep data queried via terminal** to answer “who to call today”:\\n - One query returned `[]` — **no pending follow-up calls due today**.\\n - A second query returned the full call log (JSON). Most recent calls were from **May 28, 2026** (Bayram calls to Orhan Ocakdan, Josef Garf, Fatih Yilmaz, Abdullah Oberascher). Earlier calls included Anneanne, Dede, Omar Elsayed, etc.\\n - A third query listed contacts with IDs (e.g., `14: Abdullah Oberascher`, `9: Anneanne`, `8: Orhan Ocakdan`, etc.).\\n\\n- **Daily Dose status:** Not yet filled for today. Yesterday (`dailydose_2026-05-30`) had: Islam 0.25h, Körperpflege 0.5h, Schlaf 8h.\\n- **Weather:** `Sunny +17°C 79% ↘8km/h`.\\n\\n**3. Key decisions & conclusions**\\n\\n- **Morning briefing delivered:** Sunday, May 31 — no calendar appointments, no calls due today, Daily Dose open, sunny 17°C in Vienna. The assistant noted that the previous prompt was too generic and **planned to patch the “Morgenbriefing” prompt** to be more specific and useful.\\n- The **Abend-Check 20:00 cronjob** was already the correct vehicle for CallKeep follow-ups; it just runs in the evening.\\n\\n**4. Technical details preserved**\\n\\n- Cron schedules: `30 9 * * *` (morning) and `0 20 * * *` (evening).\\n- Delivery method: `deliver: origin` (Telegram).\\n- CallKeep due-check returned `[]` (empty array).\\n- Daily Dose API endpoint referenced: `http://localhost:8765/api/data`.\\n- Daily Dose path: `/media/HDD_1TB/DailyDose/`.\\n\\n**5. Unresolved / notable**\\n\\n- The assistant **stated it would patch the morning briefing prompt** but the transcript does not show the actual edit being made.\\n- The rest of the long session shifted to an **unrelated Austrian legal research thread** (sale/burden of co-ownership shares under ABGB/WEG 2002, inheritance, compulsory portion calculations). A 17 KB legal opinion was produced and saved to `/tmp/oesterreich_miteigentum_wohnung_gutachten.md`. A final subagent call on compulsory portion gifting timed out after 600 s.\"}], \"count\": 3, \"sessions_searched\": 3}", "tool_call_id": "call_8kz12elp" }, { "role": "assistant", "content": "", "reasoning": "The user wants me to update the Cronjob prompt to make CallKeep updates shorter and more concise — only telling them who to call today, nothing else.\n\nLooking at the cronjobs:\n1. **Morgenbriefing 9:30** (`c11fbac168bd`) — morning briefing with calendar, weather, etc.\n2. **Abend-Check 20:00** (`0968c1c5dec3`) — evening check with CallKeep step\n\nThe user is saying \"halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts.\"\n\nI need to read both cronjob prompts to see which one has the CallKeep content. Based on the session_search, the Abend-Check has a CallKeep step (\"CallKeep Telefonate prüfen\"). But the user might also want the morning briefing to include CallKeep.\n\nLet me read both prompts first, then update the one(s) that include CallKeep to be shorter.\n\nWait — I should load the cronjob details to see the full prompts. The list output only shows previews. Let me check what I can read. Actually, I can see the previews:\n- Morgenbriefing: \"Morgenbriefing für den Chef (Zeyd). Führe folgende Schritte aus:\\n\\n1. **Kalender:** Rufe den Google K...\" \n- Abend-Check: \"Abend-Check für den Chef (Zeyd). Führe folgende Schritte aus:\\n\\n1. **CallKeep Telefonate prüfen:** Ru...\"\n\nI need the full prompt text. The list output doesn't give full prompts. Let me read the cronjob storage/config to find the full prompts. Or maybe I can use the cronjob tool to view full details?\n\nActually, I don't have a \"view\" action on cronjob — only create, list, update, pause, resume, remove, run. But I can use `update` to update the prompt. I need to know the full prompt first though.\n\nLet me look at where cronjobs are stored. From the hermes-agent skill, I might find the path. Let me check the config/storage locations.\n\nActually, let me just search for the cronjob storage location or read the config file.", "finish_reason": "tool_calls", "reasoning_content": "The user wants me to update the Cronjob prompt to make CallKeep updates shorter and more concise — only telling them who to call today, nothing else.\n\nLooking at the cronjobs:\n1. **Morgenbriefing 9:30** (`c11fbac168bd`) — morning briefing with calendar, weather, etc.\n2. **Abend-Check 20:00** (`0968c1c5dec3`) — evening check with CallKeep step\n\nThe user is saying \"halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts.\"\n\nI need to read both cronjob prompts to see which one has the CallKeep content. Based on the session_search, the Abend-Check has a CallKeep step (\"CallKeep Telefonate prüfen\"). But the user might also want the morning briefing to include CallKeep.\n\nLet me read both prompts first, then update the one(s) that include CallKeep to be shorter.\n\nWait — I should load the cronjob details to see the full prompts. The list output only shows previews. Let me check what I can read. Actually, I can see the previews:\n- Morgenbriefing: \"Morgenbriefing für den Chef (Zeyd). Führe folgende Schritte aus:\\n\\n1. **Kalender:** Rufe den Google K...\" \n- Abend-Check: \"Abend-Check für den Chef (Zeyd). Führe folgende Schritte aus:\\n\\n1. **CallKeep Telefonate prüfen:** Ru...\"\n\nI need the full prompt text. The list output doesn't give full prompts. Let me read the cronjob storage/config to find the full prompts. Or maybe I can use the cronjob tool to view full details?\n\nActually, I don't have a \"view\" action on cronjob — only create, list, update, pause, resume, remove, run. But I can use `update` to update the prompt. I need to know the full prompt first though.\n\nLet me look at where cronjobs are stored. From the hermes-agent skill, I might find the path. Let me check the config/storage locations.\n\nActually, let me just search for the cronjob storage location or read the config file.", "tool_calls": [ { "id": "call_0bmxx51l", "call_id": "call_0bmxx51l", "response_item_id": "fc_0bmxx51l", "type": "function", "function": { "name": "skill_view", "arguments": "{\"name\":\"hermes-agent\"}" } } ] }, { "role": "tool", "name": "skill_view", "content": "{\"success\": true, \"name\": \"hermes-agent\", \"description\": \"Configure, extend, or contribute to Hermes Agent.\", \"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"], \"content\": \"---\\nname: hermes-agent\\ndescription: \\\"Configure, extend, or contribute to Hermes Agent.\\\"\\nversion: 2.1.0\\nauthor: Hermes Agent + Teknium\\nlicense: MIT\\nmetadata:\\n hermes:\\n tags: [hermes, setup, configuration, multi-agent, spawning, cli, gateway, development]\\n homepage: https://github.com/NousResearch/hermes-agent\\n related_skills: [claude-code, codex, opencode]\\n---\\n\\n# Hermes Agent\\n\\nHermes Agent is an open-source AI agent framework by Nous Research that runs in your terminal, messaging platforms, and IDEs. It belongs to the same category as Claude Code (Anthropic), Codex (OpenAI), and OpenClaw — autonomous coding and task-execution agents that use tool calling to interact with your system. Hermes works with any LLM provider (OpenRouter, Anthropic, OpenAI, DeepSeek, local models, and 15+ others) and runs on Linux, macOS, and WSL.\\n\\nWhat makes Hermes different:\\n\\n- **Self-improving through skills** — Hermes learns from experience by saving reusable procedures as skills. When it solves a complex problem, discovers a workflow, or gets corrected, it can persist that knowledge as a skill document that loads into future sessions. Skills accumulate over time, making the agent better at your specific tasks and environment.\\n- **Persistent memory across sessions** — remembers who you are, your preferences, environment details, and lessons learned. Pluggable memory backends (built-in, Honcho, Mem0, and more) let you choose how memory works.\\n- **Multi-platform gateway** — the same agent runs on Telegram, Discord, Slack, WhatsApp, Signal, Matrix, Email, and 10+ other platforms with full tool access, not just chat.\\n- **Provider-agnostic** — swap models and providers mid-workflow without changing anything else. Credential pools rotate across multiple API keys automatically.\\n- **Profiles** — run multiple independent Hermes instances with isolated configs, sessions, skills, and memory.\\n- **Extensible** — plugins, MCP servers, custom tools, webhook triggers, cron scheduling, and the full Python ecosystem.\\n\\nPeople use Hermes for software development, research, system administration, data analysis, content creation, home automation, and anything else that benefits from an AI agent with persistent context and full system access.\\n\\n**This skill helps you work with Hermes Agent effectively** — setting it up, configuring features, spawning additional agent instances, troubleshooting issues, finding the right commands and settings, and understanding how the system works when you need to extend or contribute to it.\\n\\n**Docs:** https://hermes-agent.nousresearch.com/docs/\\n\\n## Quick Start\\n\\n```bash\\n# Install\\ncurl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bash\\n\\n# Interactive chat (default)\\nhermes\\n\\n# Single query\\nhermes chat -q \\\"What is the capital of France?\\\"\\n\\n# Setup wizard\\nhermes setup\\n\\n# Change model/provider\\nhermes model\\n\\n# Check health\\nhermes doctor\\n```\\n\\n---\\n\\n## CLI Reference\\n\\n### Global Flags\\n\\n```\\nhermes [flags] [command]\\n\\n --version, -V Show version\\n --resume, -r SESSION Resume session by ID or title\\n --continue, -c [NAME] Resume by name, or most recent session\\n --worktree, -w Isolated git worktree mode (parallel agents)\\n --skills, -s SKILL Preload skills (comma-separate or repeat)\\n --profile, -p NAME Use a named profile\\n --yolo Skip dangerous command approval\\n --pass-session-id Include session ID in system prompt\\n```\\n\\nNo subcommand defaults to `chat`.\\n\\n### Chat\\n\\n```\\nhermes chat [flags]\\n -q, --query TEXT Single query, non-interactive\\n -m, --model MODEL Model (e.g. anthropic/claude-sonnet-4)\\n -t, --toolsets LIST Comma-separated toolsets\\n --provider PROVIDER Force provider (openrouter, anthropic, nous, etc.)\\n -v, --verbose Verbose output\\n -Q, --quiet Suppress banner, spinner, tool previews\\n --checkpoints Enable filesystem checkpoints (/rollback)\\n --source TAG Session source tag (default: cli)\\n```\\n\\n### Configuration\\n\\n```\\nhermes setup [section] Interactive wizard (model|terminal|gateway|tools|agent)\\nhermes model Interactive model/provider picker\\nhermes config View current config\\nhermes config edit Open config.yaml in $EDITOR\\nhermes config set KEY VAL Set a config value\\nhermes config path Print config.yaml path\\nhermes config env-path Print .env path\\nhermes config check Check for missing/outdated config\\nhermes config migrate Update config with new options\\nhermes login [--provider P] OAuth login (nous, openai-codex)\\nhermes logout Clear stored auth\\nhermes doctor [--fix] Check dependencies and config\\nhermes status [--all] Show component status\\n```\\n\\n### Tools & Skills\\n\\n```\\nhermes tools Interactive tool enable/disable (curses UI)\\nhermes tools list Show all tools and status\\nhermes tools enable NAME Enable a toolset\\nhermes tools disable NAME Disable a toolset\\n\\nhermes skills list List installed skills\\nhermes skills search QUERY Search the skills hub\\nhermes skills install ID Install a skill (ID can be a hub identifier OR a direct https://…/SKILL.md URL; pass --name to override when frontmatter has no name)\\nhermes skills inspect ID Preview without installing\\nhermes skills config Enable/disable skills per platform\\nhermes skills check Check for updates\\nhermes skills update Update outdated skills\\nhermes skills uninstall N Remove a hub skill\\nhermes skills publish PATH Publish to registry\\nhermes skills browse Browse all available skills\\nhermes skills tap add REPO Add a GitHub repo as skill source\\n```\\n\\n### MCP Servers\\n\\n```\\nhermes mcp serve Run Hermes as an MCP server\\nhermes mcp add NAME Add an MCP server (--url or --command)\\nhermes mcp remove NAME Remove an MCP server\\nhermes mcp list List configured servers\\nhermes mcp test NAME Test connection\\nhermes mcp configure NAME Toggle tool selection\\n```\\n\\n### Gateway (Messaging Platforms)\\n\\n```\\nhermes gateway run Start gateway foreground\\nhermes gateway install Install as background service\\nhermes gateway start/stop Control the service\\nhermes gateway restart Restart the service\\nhermes gateway status Check status\\nhermes gateway setup Configure platforms\\n```\\n\\nSupported platforms: Telegram, Discord, Slack, WhatsApp, Signal, Email, SMS, Matrix, Mattermost, Home Assistant, DingTalk, Feishu, WeCom, BlueBubbles (iMessage), Weixin (WeChat), API Server, Webhooks. Open WebUI connects via the API Server adapter.\\n\\nPlatform docs: https://hermes-agent.nousresearch.com/docs/user-guide/messaging/\\n\\n### Sessions\\n\\n```\\nhermes sessions list List recent sessions\\nhermes sessions browse Interactive picker\\nhermes sessions export OUT Export to JSONL\\nhermes sessions rename ID T Rename a session\\nhermes sessions delete ID Delete a session\\nhermes sessions prune Clean up old sessions (--older-than N days)\\nhermes sessions stats Session store statistics\\n```\\n\\n### Cron Jobs\\n\\n```\\nhermes cron list List jobs (--all for disabled)\\nhermes cron create SCHED Create: '30m', 'every 2h', '0 9 * * *'\\nhermes cron edit ID Edit schedule, prompt, delivery\\nhermes cron pause/resume ID Control job state\\nhermes cron run ID Trigger on next tick\\nhermes cron remove ID Delete a job\\nhermes cron status Scheduler status\\n```\\n\\n### Webhooks\\n\\n```\\nhermes webhook subscribe N Create route at /webhooks/\\nhermes webhook list List subscriptions\\nhermes webhook remove NAME Remove a subscription\\nhermes webhook test NAME Send a test POST\\n```\\n\\n### Profiles\\n\\n```\\nhermes profile list List all profiles\\nhermes profile create NAME Create (--clone, --clone-all, --clone-from)\\nhermes profile use NAME Set sticky default\\nhermes profile delete NAME Delete a profile\\nhermes profile show NAME Show details\\nhermes profile alias NAME Manage wrapper scripts\\nhermes profile rename A B Rename a profile\\nhermes profile export NAME Export to tar.gz\\nhermes profile import FILE Import from archive\\n```\\n\\n### Credential Pools\\n\\n```\\nhermes auth add Interactive credential wizard\\nhermes auth list [PROVIDER] List pooled credentials\\nhermes auth remove P INDEX Remove by provider + index\\nhermes auth reset PROVIDER Clear exhaustion status\\n```\\n\\n### Other\\n\\n```\\nhermes insights [--days N] Usage analytics\\nhermes update Update to latest version\\nhermes pairing list/approve/revoke DM authorization\\nhermes plugins list/install/remove Plugin management\\nhermes honcho setup/status Honcho memory integration (requires honcho plugin)\\nhermes memory setup/status/off Memory provider config\\nhermes completion bash|zsh Shell completions\\nhermes acp ACP server (IDE integration)\\nhermes claw migrate Migrate from OpenClaw\\nhermes uninstall Uninstall Hermes\\n```\\n\\n---\\n\\n## Slash Commands (In-Session)\\n\\nType these during an interactive chat session. New commands land fairly\\noften; if something below looks stale, run `/help` in-session for the\\nauthoritative list or see the [live slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands).\\nThe registry of record is `hermes_cli/commands.py` — every consumer\\n(autocomplete, Telegram menu, Slack mapping, `/help`) derives from it.\\n\\n### Session Control\\n```\\n/new (/reset) Fresh session\\n/clear Clear screen + new session (CLI)\\n/retry Resend last message\\n/undo Remove last exchange\\n/title [name] Name the session\\n/compress Manually compress context\\n/stop Kill background processes\\n/rollback [N] Restore filesystem checkpoint\\n/snapshot [sub] Create or restore state snapshots of Hermes config/state (CLI)\\n/background Run prompt in background\\n/queue Queue for next turn\\n/steer Inject a message after the next tool call without interrupting\\n/agents (/tasks) Show active agents and running tasks\\n/resume [name] Resume a named session\\n/goal [text|sub] Set a standing goal Hermes works on across turns until achieved\\n (subcommands: status, pause, resume, clear)\\n/redraw Force a full UI repaint (CLI)\\n```\\n\\n### Configuration\\n```\\n/config Show config (CLI)\\n/model [name] Show or change model\\n/personality [name] Set personality\\n/reasoning [level] Set reasoning (none|minimal|low|medium|high|xhigh|show|hide)\\n/verbose Cycle: off → new → all → verbose\\n/voice [on|off|tts] Voice mode\\n/yolo Toggle approval bypass\\n/busy [sub] Control what Enter does while Hermes is working (CLI)\\n (subcommands: queue, steer, interrupt, status)\\n/indicator [style] Pick the TUI busy-indicator style (CLI)\\n (styles: kaomoji, emoji, unicode, ascii)\\n/footer [on|off] Toggle gateway runtime-metadata footer on final replies\\n/skin [name] Change theme (CLI)\\n/statusbar Toggle status bar (CLI)\\n```\\n\\n### Tools & Skills\\n```\\n/tools Manage tools (CLI)\\n/toolsets List toolsets (CLI)\\n/skills Search/install skills (CLI)\\n/skill Load a skill into session\\n/reload-skills Re-scan ~/.hermes/skills/ for added/removed skills\\n/reload Reload .env variables into the running session (CLI)\\n/reload-mcp Reload MCP servers\\n/cron Manage cron jobs (CLI)\\n/curator [sub] Background skill maintenance (status, run, pin, archive, …)\\n/kanban [sub] Multi-profile collaboration board (tasks, links, comments)\\n/plugins List plugins (CLI)\\n```\\n\\n### Gateway\\n```\\n/approve Approve a pending command (gateway)\\n/deny Deny a pending command (gateway)\\n/restart Restart gateway (gateway)\\n/sethome Set current chat as home channel (gateway)\\n/update Update Hermes to latest (gateway)\\n/topic [sub] Enable or inspect Telegram DM topic sessions (gateway)\\n/platforms (/gateway) Show platform connection status (gateway)\\n```\\n\\n### Utility\\n```\\n/branch (/fork) Branch the current session\\n/fast Toggle priority/fast processing\\n/browser Open CDP browser connection\\n/history Show conversation history (CLI)\\n/save Save conversation to file (CLI)\\n/copy [N] Copy the last assistant response to clipboard (CLI)\\n/paste Attach clipboard image (CLI)\\n/image Attach local image file (CLI)\\n```\\n\\n### Info\\n```\\n/help Show commands\\n/commands [page] Browse all commands (gateway)\\n/usage Token usage\\n/insights [days] Usage analytics\\n/gquota Show Google Gemini Code Assist quota usage (CLI)\\n/status Session info (gateway)\\n/profile Active profile info\\n/debug Upload debug report (system info + logs) and get shareable links\\n```\\n\\n### Exit\\n```\\n/quit (/exit, /q) Exit CLI\\n```\\n\\n---\\n\\n## Key Paths & Config\\n\\n```\\n~/.hermes/config.yaml Main configuration\\n~/.hermes/.env API keys and secrets\\n$HERMES_HOME/skills/ Installed skills\\n~/.hermes/sessions/ Session transcripts\\n~/.hermes/logs/ Gateway and error logs\\n~/.hermes/auth.json OAuth tokens and credential pools\\n~/.hermes/hermes-agent/ Source code (if git-installed)\\n```\\n\\nProfiles use `~/.hermes/profiles//` with the same layout.\\n\\n### Config Sections\\n\\nEdit with `hermes config edit` or `hermes config set section.key value`.\\n\\n| Section | Key options |\\n|---------|-------------|\\n| `model` | `default`, `provider`, `base_url`, `api_key`, `context_length` |\\n| `agent` | `max_turns` (90), `tool_use_enforcement` |\\n| `terminal` | `backend` (local/docker/ssh/modal), `cwd`, `timeout` (180) |\\n| `compression` | `enabled`, `threshold` (0.50), `target_ratio` (0.20), `protect_last_n` (20), `hygiene_hard_message_limit` (400) |\\n| `display` | `skin`, `tool_progress`, `show_reasoning`, `show_cost` |\\n| `stt` | `enabled`, `provider` (local/groq/openai/mistral) |\\n| `tts` | `provider` (edge/elevenlabs/openai/minimax/mistral/neutts) |\\n| `memory` | `memory_enabled`, `user_profile_enabled`, `provider` |\\n| `security` | `tirith_enabled`, `website_blocklist` |\\n| `delegation` | `model`, `provider`, `base_url`, `api_key`, `max_iterations` (50), `reasoning_effort` |\\n| `checkpoints` | `enabled`, `max_snapshots` (50) |\\n\\nFull config reference: https://hermes-agent.nousresearch.com/docs/user-guide/configuration\\n\\n### Providers\\n\\n20+ providers supported. Set via `hermes model` or `hermes setup`.\\n\\n| Provider | Auth | Key env var |\\n|----------|------|-------------|\\n| OpenRouter | API key | `OPENROUTER_API_KEY` |\\n| Anthropic | API key | `ANTHROPIC_API_KEY` |\\n| Nous Portal | OAuth | `hermes auth` |\\n| OpenAI Codex | OAuth | `hermes auth` |\\n| GitHub Copilot | Token | `COPILOT_GITHUB_TOKEN` |\\n| Google Gemini | API key | `GOOGLE_API_KEY` or `GEMINI_API_KEY` |\\n| DeepSeek | API key | `DEEPSEEK_API_KEY` |\\n| xAI / Grok | API key | `XAI_API_KEY` |\\n| Hugging Face | Token | `HF_TOKEN` |\\n| Z.AI / GLM | API key | `GLM_API_KEY` |\\n| MiniMax | API key | `MINIMAX_API_KEY` |\\n| MiniMax CN | API key | `MINIMAX_CN_API_KEY` |\\n| Kimi / Moonshot | API key | `KIMI_API_KEY` |\\n| Alibaba / DashScope | API key | `DASHSCOPE_API_KEY` |\\n| Xiaomi MiMo | API key | `XIAOMI_API_KEY` |\\n| Kilo Code | API key | `KILOCODE_API_KEY` |\\n| AI Gateway (Vercel) | API key | `AI_GATEWAY_API_KEY` |\\n| OpenCode Zen | API key | `OPENCODE_ZEN_API_KEY` |\\n| OpenCode Go | API key | `OPENCODE_GO_API_KEY` |\\n| Qwen OAuth | OAuth | `hermes login --provider qwen-oauth` |\\n| Custom endpoint | Config | `model.base_url` + `model.api_key` in config.yaml |\\n| GitHub Copilot ACP | External | `COPILOT_CLI_PATH` or Copilot CLI |\\n\\nFull provider docs: https://hermes-agent.nousresearch.com/docs/integrations/providers\\n\\n**Ollama Cloud Pro as custom provider:** See `references/ollama-cloud-pro-custom-provider.md` — base URL `https://ollama.com/v1` with `provider: custom`, 3-model concurrency limit, CCR proxy pitfalls, and direct config template.\\n\\n### Toolsets\\n\\nEnable/disable via `hermes tools` (interactive) or `hermes tools enable/disable NAME`.\\n\\n| Toolset | What it provides |\\n|---------|-----------------|\\n| `web` | Web search and content extraction |\\n| `search` | Web search only (subset of `web`) |\\n| `browser` | Browser automation (Browserbase, Camofox, or local Chromium) |\\n| `terminal` | Shell commands and process management |\\n| `file` | File read/write/search/patch |\\n| `code_execution` | Sandboxed Python execution |\\n| `vision` | Image analysis |\\n| `image_gen` | AI image generation |\\n| `video` | Video analysis and generation |\\n| `tts` | Text-to-speech |\\n| `skills` | Skill browsing and management |\\n| `memory` | Persistent cross-session memory |\\n| `session_search` | Search past conversations |\\n| `delegation` | Subagent task delegation |\\n| `cronjob` | Scheduled task management |\\n| `clarify` | Ask user clarifying questions |\\n| `messaging` | Cross-platform message sending |\\n| `todo` | In-session task planning and tracking |\\n| `kanban` | Multi-agent work-queue tools (gated to workers) |\\n| `debugging` | Extra introspection/debug tools (off by default) |\\n| `safe` | Minimal, low-risk toolset for locked-down sessions |\\n| `spotify` | Spotify playback and playlist control |\\n| `homeassistant` | Smart home control (off by default) |\\n| `discord` | Discord integration tools |\\n| `discord_admin` | Discord admin/moderation tools |\\n| `feishu_doc` | Feishu (Lark) document tools |\\n| `feishu_drive` | Feishu (Lark) drive tools |\\n| `yuanbao` | Yuanbao integration tools |\\n| `rl` | Reinforcement learning tools (off by default) |\\n| `moa` | Mixture of Agents (off by default) |\\n\\nFull enumeration lives in `toolsets.py` as the `TOOLSETS` dict; `_HERMES_CORE_TOOLS` is the default bundle most platforms inherit from.\\n\\nTool changes take effect on `/reset` (new session). They do NOT apply mid-conversation to preserve prompt caching.\\n\\n---\\n\\n## Security & Privacy Toggles\\n\\nCommon \\\"why is Hermes doing X to my output / tool calls / commands?\\\" toggles — and the exact commands to change them. Most of these need a fresh session (`/reset` in chat, or start a new `hermes` invocation) because they're read once at startup.\\n\\n### Secret redaction in tool output\\n\\nSecret redaction is **off by default** — tool output (terminal stdout, `read_file`, web content, subagent summaries, etc.) passes through unmodified. If the user wants Hermes to auto-mask strings that look like API keys, tokens, and secrets before they enter the conversation context and logs:\\n\\n```bash\\nhermes config set security.redact_secrets true # enable globally\\n```\\n\\n**Restart required.** `security.redact_secrets` is snapshotted at import time — toggling it mid-session (e.g. via `export HERMES_REDACT_SECRETS=true` from a tool call) will NOT take effect for the running process. Tell the user to run `hermes config set security.redact_secrets true` in a terminal, then start a new session. This is deliberate — it prevents an LLM from flipping the toggle on itself mid-task.\\n\\nDisable again with:\\n```bash\\nhermes config set security.redact_secrets false\\n```\\n\\n### PII redaction in gateway messages\\n\\nSeparate from secret redaction. When enabled, the gateway hashes user IDs and strips phone numbers from the session context before it reaches the model:\\n\\n```bash\\nhermes config set privacy.redact_pii true # enable\\nhermes config set privacy.redact_pii false # disable (default)\\n```\\n\\n### Command approval prompts\\n\\nBy default (`approvals.mode: manual`), Hermes prompts the user before running shell commands flagged as destructive (`rm -rf`, `git reset --hard`, etc.). The modes are:\\n\\n- `manual` — always prompt (default)\\n- `smart` — use an auxiliary LLM to auto-approve low-risk commands, prompt on high-risk\\n- `off` — skip all approval prompts (equivalent to `--yolo`)\\n\\n```bash\\nhermes config set approvals.mode smart # recommended middle ground\\nhermes config set approvals.mode off # bypass everything (not recommended)\\n```\\n\\nPer-invocation bypass without changing config:\\n- `hermes --yolo …`\\n- `export HERMES_YOLO_MODE=1`\\n\\nNote: YOLO / `approvals.mode: off` does NOT turn off secret redaction. They are independent.\\n\\n### Shell hooks allowlist\\n\\nSome shell-hook integrations require explicit allowlisting before they fire. Managed via `~/.hermes/shell-hooks-allowlist.json` — prompted interactively the first time a hook wants to run.\\n\\n### Disabling the web/browser/image-gen tools\\n\\nTo keep the model away from network or media tools entirely, open `hermes tools` and toggle per-platform. Takes effect on next session (`/reset`). See the Tools & Skills section above.\\n\\n---\\n\\n## Voice & Transcription\\n\\n### STT (Voice → Text)\\n\\nVoice messages from messaging platforms are auto-transcribed.\\n\\nProvider priority (auto-detected):\\n1. **Local faster-whisper** — free, no API key: `pip install faster-whisper`\\n2. **Groq Whisper** — free tier: set `GROQ_API_KEY`\\n3. **OpenAI Whisper** — paid: set `VOICE_TOOLS_OPENAI_KEY`\\n4. **Mistral Voxtral** — set `MISTRAL_API_KEY`\\n\\nConfig:\\n```yaml\\nstt:\\n enabled: true\\n provider: local # local, groq, openai, mistral\\n local:\\n model: base # tiny, base, small, medium, large-v3\\n```\\n\\n### TTS (Text → Voice)\\n\\n| Provider | Env var | Free? |\\n|----------|---------|-------|\\n| Edge TTS | None | Yes (default) |\\n| ElevenLabs | `ELEVENLABS_API_KEY` | Free tier |\\n| OpenAI | `VOICE_TOOLS_OPENAI_KEY` | Paid |\\n| MiniMax | `MINIMAX_API_KEY` | Paid |\\n| Mistral (Voxtral) | `MISTRAL_API_KEY` | Paid |\\n| NeuTTS (local) | None (`pip install neutts[all]` + `espeak-ng`) | Free |\\n\\nVoice commands: `/voice on` (voice-to-voice), `/voice tts` (always voice), `/voice off`.\\n\\n---\\n\\n## Spawning Additional Hermes Instances\\n\\nRun additional Hermes processes as fully independent subprocesses — separate sessions, tools, and environments.\\n\\n### When to Use This vs delegate_task\\n\\n| | `delegate_task` | Spawning `hermes` process |\\n|-|-----------------|--------------------------|\\n| Isolation | Separate conversation, shared process | Fully independent process |\\n| Duration | Minutes (bounded by parent loop) | Hours/days |\\n| Tool access | Subset of parent's tools | Full tool access |\\n| Interactive | No | Yes (PTY mode) |\\n| Use case | Quick parallel subtasks | Long autonomous missions |\\n\\n### One-Shot Mode\\n\\n```\\nterminal(command=\\\"hermes chat -q 'Research GRPO papers and write summary to ~/research/grpo.md'\\\", timeout=300)\\n\\n# Background for long tasks:\\nterminal(command=\\\"hermes chat -q 'Set up CI/CD for ~/myapp'\\\", background=true)\\n```\\n\\n### Interactive PTY Mode (via tmux)\\n\\nHermes uses prompt_toolkit, which requires a real terminal. Use tmux for interactive spawning:\\n\\n```\\n# Start\\nterminal(command=\\\"tmux new-session -d -s agent1 -x 120 -y 40 'hermes'\\\", timeout=10)\\n\\n# Wait for startup, then send a message\\nterminal(command=\\\"sleep 8 && tmux send-keys -t agent1 'Build a FastAPI auth service' Enter\\\", timeout=15)\\n\\n# Read output\\nterminal(command=\\\"sleep 20 && tmux capture-pane -t agent1 -p\\\", timeout=5)\\n\\n# Send follow-up\\nterminal(command=\\\"tmux send-keys -t agent1 'Add rate limiting middleware' Enter\\\", timeout=5)\\n\\n# Exit\\nterminal(command=\\\"tmux send-keys -t agent1 '/exit' Enter && sleep 2 && tmux kill-session -t agent1\\\", timeout=10)\\n```\\n\\n### Multi-Agent Coordination\\n\\n```\\n# Agent A: backend\\nterminal(command=\\\"tmux new-session -d -s backend -x 120 -y 40 'hermes -w'\\\", timeout=10)\\nterminal(command=\\\"sleep 8 && tmux send-keys -t backend 'Build REST API for user management' Enter\\\", timeout=15)\\n\\n# Agent B: frontend\\nterminal(command=\\\"tmux new-session -d -s frontend -x 120 -y 40 'hermes -w'\\\", timeout=10)\\nterminal(command=\\\"sleep 8 && tmux send-keys -t frontend 'Build React dashboard for user management' Enter\\\", timeout=15)\\n\\n# Check progress, relay context between them\\nterminal(command=\\\"tmux capture-pane -t backend -p | tail -30\\\", timeout=5)\\nterminal(command=\\\"tmux send-keys -t frontend 'Here is the API schema from the backend agent: ...' Enter\\\", timeout=5)\\n```\\n\\n### Session Resume\\n\\n```\\n# Resume most recent session\\nterminal(command=\\\"tmux new-session -d -s resumed 'hermes --continue'\\\", timeout=10)\\n\\n# Resume specific session\\nterminal(command=\\\"tmux new-session -d -s resumed 'hermes --resume 20260225_143052_a1b2c3'\\\", timeout=10)\\n```\\n\\n### Tips\\n\\n- **Prefer `delegate_task` for quick subtasks** — less overhead than spawning a full process\\n- **Use `-w` (worktree mode)** when spawning agents that edit code — prevents git conflicts\\n- **Set timeouts** for one-shot mode — complex tasks can take 5-10 minutes\\n- **Use `hermes chat -q` for fire-and-forget** — no PTY needed\\n- **Use tmux for interactive sessions** — raw PTY mode has `\\\\r` vs `\\\\n` issues with prompt_toolkit\\n- **For scheduled tasks**, use the `cronjob` tool instead of spawning — handles delivery and retry\\n\\n---\\n\\n## Durable & Background Systems\\n\\nFour systems run alongside the main conversation loop. Quick reference\\nhere; full developer notes live in `AGENTS.md`, user-facing docs under\\n`website/docs/user-guide/features/`.\\n\\n### Delegation (`delegate_task`)\\n\\nSynchronous subagent spawn — the parent waits for the child's summary\\nbefore continuing its own loop. Isolated context + terminal session.\\n\\n- **Single:** `delegate_task(goal, context, toolsets)`.\\n- **Batch:** `delegate_task(tasks=[{goal, ...}, ...])` runs children in\\n parallel, capped by `delegation.max_concurrent_children` (default 3).\\n- **Roles:** `leaf` (default; cannot re-delegate) vs `orchestrator`\\n (can spawn its own workers, bounded by `delegation.max_spawn_depth`).\\n- **Not durable.** If the parent is interrupted, the child is\\n cancelled. For work that must outlive the turn, use `cronjob` or\\n `terminal(background=True, notify_on_complete=True)`.\\n\\nConfig: `delegation.*` in `config.yaml`.\\n\\n### Cron (scheduled jobs)\\n\\nDurable scheduler — `cron/jobs.py` + `cron/scheduler.py`. Drive it via\\nthe `cronjob` tool, the `hermes cron` CLI (`list`, `add`, `edit`,\\n`pause`, `resume`, `run`, `remove`), or the `/cron` slash command.\\n\\n- **Schedules:** duration (`\\\"30m\\\"`, `\\\"2h\\\"`), \\\"every\\\" phrase\\n (`\\\"every monday 9am\\\"`), 5-field cron (`\\\"0 9 * * *\\\"`), or ISO timestamp.\\n- **Per-job knobs:** `skills`, `model`/`provider` override, `script`\\n (pre-run data collection; `no_agent=True` makes the script the whole\\n job), `context_from` (chain job A's output into job B), `workdir`\\n (run in a specific dir with its `AGENTS.md` / `CLAUDE.md` loaded),\\n multi-platform delivery.\\n- **Invariants:** 3-minute hard interrupt per run, `.tick.lock` file\\n prevents duplicate ticks across processes, cron sessions pass\\n `skip_memory=True` by default, and cron deliveries are framed with a\\n header/footer instead of being mirrored into the target gateway\\n session (keeps role alternation intact).\\n\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/cron\\n\\n### Curator (skill lifecycle)\\n\\nBackground maintenance for agent-created skills. Tracks usage, marks\\nidle skills stale, archives stale ones, keeps a pre-run tar.gz backup\\nso nothing is lost.\\n\\n- **CLI:** `hermes curator ` — `status`, `run`, `pause`, `resume`,\\n `pin`, `unpin`, `archive`, `restore`, `prune`, `backup`, `rollback`.\\n- **Slash:** `/curator ` mirrors the CLI.\\n- **Scope:** only touches skills with `created_by: \\\"agent\\\"` provenance.\\n Bundled + hub-installed skills are off-limits. **Never deletes** —\\n max destructive action is archive. Pinned skills are exempt from\\n every auto-transition and every LLM review pass.\\n- **Telemetry:** sidecar at `~/.hermes/skills/.usage.json` holds\\n per-skill `use_count`, `view_count`, `patch_count`,\\n `last_activity_at`, `state`, `pinned`.\\n\\nConfig: `curator.*` (`enabled`, `interval_hours`, `min_idle_hours`,\\n`stale_after_days`, `archive_after_days`, `backup.*`).\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/curator\\n\\n### Kanban (multi-agent work queue)\\n\\nDurable SQLite board for multi-profile / multi-worker collaboration.\\nUsers drive it via `hermes kanban `; dispatcher-spawned workers\\nsee a focused `kanban_*` toolset gated by `HERMES_KANBAN_TASK` so the\\nschema footprint is zero outside worker processes.\\n\\n- **CLI verbs (common):** `init`, `create`, `list` (alias `ls`),\\n `show`, `assign`, `link`, `unlink`, `comment`, `complete`, `block`,\\n `unblock`, `archive`, `tail`. Less common: `watch`, `stats`, `runs`,\\n `log`, `dispatch`, `daemon`, `gc`.\\n- **Worker toolset:** `kanban_show`, `kanban_complete`, `kanban_block`,\\n `kanban_heartbeat`, `kanban_comment`, `kanban_create`, `kanban_link`.\\n- **Dispatcher** runs inside the gateway by default\\n (`kanban.dispatch_in_gateway: true`) — reclaims stale claims,\\n promotes ready tasks, atomically claims, spawns assigned profiles.\\n Auto-blocks a task after ~5 consecutive spawn failures.\\n- **Isolation:** board is the hard boundary (workers get\\n `HERMES_KANBAN_BOARD` pinned in env); tenant is a soft namespace\\n within a board for workspace-path + memory-key isolation.\\n\\nUser docs: https://hermes-agent.nousresearch.com/docs/user-guide/features/kanban\\n\\n---\\n\\n## Troubleshooting\\n\\n### Voice not working\\n1. Check `stt.enabled: true` in config.yaml\\n2. Verify provider: `pip install faster-whisper` or set API key\\n3. In gateway: `/restart`. In CLI: exit and relaunch.\\n\\n### Tool not available\\n1. `hermes tools` — check if toolset is enabled for your platform\\n2. Some tools need env vars (check `.env`)\\n3. `/reset` after enabling tools\\n\\n### Model/provider issues\\n1. `hermes doctor` — check config and dependencies\\n2. `hermes login` — re-authenticate OAuth providers\\n3. Check `.env` has the right API key\\n4. **Copilot 403**: `gh auth login` tokens do NOT work for Copilot API. You must use the Copilot-specific OAuth device code flow via `hermes model` → GitHub Copilot.\\n\\n### Credential management (`.env` writing)\\n\\nWhen `hermes` CLI is unavailable and `write_file` is blocked on credential files, writing secrets to `.env` requires terminal-based approaches. Full guide: `references/credential-management.md` — covers safe append vs. dangerous overwrite, sandbox limitations, and 401 troubleshooting.\\n\\n### Changes not taking effect\\n- **Tools/skills:** `/reset` starts a new session with updated toolset\\n- **Config changes:** In gateway: `/restart`. In CLI: exit and relaunch.\\n- **Code changes:** Restart the CLI or gateway process\\n\\n### Skills not showing\\n1. `hermes skills list` — verify installed\\n2. `hermes skills config` — check platform enablement\\n3. Load explicitly: `/skill name` or `hermes -s name`\\n\\n### Gateway issues\\nCheck logs first:\\n```bash\\ngrep -i \\\"failed to send\\\\|error\\\" ~/.hermes/logs/gateway.log | tail -20\\n```\\n\\n**Gateway completely dead / won't start?** See `references/gateway-outage-recovery.md` — 4-item checklist covering .env vars, config.yaml gateway section, and stale PID/lock cleanup.\\n\\nCommon gateway problems:\\n- **Gateway dies on SSH logout**: Enable linger: `sudo loginctl enable-linger $USER`\\n- **Gateway dies on WSL2 close**: WSL2 requires `systemd=true` in `/etc/wsl.conf` for systemd services to work. Without it, gateway falls back to `nohup` (dies when session closes).\\n- **Gateway crash loop**: Reset the failed state: `systemctl --user reset-failed hermes-gateway`\\n- **ModuleNotFoundError after file deletions**: NEVER delete `.py` files from the hermes-agent source directory unless the corresponding imports are also removed. `hermes_cli/models.py` imports `codex_models.py` at startup — deleting that file without editing `models.py` causes `ModuleNotFoundError: No module named 'hermes_cli.codex_models'` at gateway start, producing a restart loop. Recovery: `sudo git -C /path/to/hermes-agent -c safe.directory=/path/to/hermes-agent restore .`. If you want to disable providers, modify the import chain — never just delete files.\\n\\n### Session Recovery After Gateway Restart\\nIf the gateway restarts and `session_search` returns no results, **session data is NOT lost** — the in-memory index was cleared but the on-disk files remain.\\n\\n**Where to look:**\\n- `~/.hermes/sessions/*.jsonl` — raw session transcripts (one file per session)\\n- `~/.hermes/memories/USER.md` and `MEMORY.md` — persisted user profile and environment facts\\n- `~/.hermes/AGENTS.md` — custom operating rules\\n- `~/.hermes/work/` — any files the agent produced\\n- `~/.hermes/config.yaml` and `~/.hermes/.env` — configuration and secrets\\n\\n**Recovery steps:**\\n1. Read the memories: `~/.hermes/memories/USER.md` and `MEMORY.md`\\n2. List recent session files: `ls -lt ~/.hermes/sessions/*.jsonl | head -20`\\n3. Read key session transcripts directly (JSONL format, one message per line)\\n4. Check `~/.hermes/work/` for any deliverables from past sessions\\n\\n**Important:** The gateway restart itself does NOT delete anything. The `sessions.json` index may take a moment to rebuild, but the `.jsonl` files are present immediately. If `session_search` is empty, always fall back to direct filesystem inspection.\\n\\n**Critical pitfall — session_search default limit:**\\n`session_search` without arguments may return only 1 result. After a gateway restart the index is empty, so even recent sessions appear lost. Always pass `limit=5` (or higher) and use `query=\\\"*\\\"` to force a broad scan when recovering. Example:\\n```python\\nsession_search(limit=5, query=\\\"*\\\")\\n```\\nIf this still returns nothing, bypass the index entirely and read the `.jsonl` files directly from disk.\\n\\n### Honcho Memory Plugin — Reality Check\\nHoncho is listed as an installed plugin but the CLI subcommand `hermes honcho` does **not exist** in all Hermes builds. The Python library (`honcho`) may be present in the venv while the CLI integration is missing.\\n\\n**What actually works:**\\n1. Set provider: `hermes config set memory.provider honcho`\\n2. Verify with `hermes memory status` — look for `Provider: honcho`\\n3. The plugin status line will say `Status: not available` if the Honcho server (cloud or local Docker) is not reachable.\\n\\n**Local (no API key) is NOT automatic:**\\nHoncho requires either a cloud API key (`HONCHO_API_KEY`) or a self-hosted Docker/Postgres instance. There is no \\\"just use SQLite locally\\\" zero-setup mode. If the user wants 100 % offline memory without cloud accounts, the built-in memory system is the practical choice.\\n\\n**Do not promise Honcho setup works without verifying the CLI subcommand exists first.** Check with `hermes honcho status` — if the command is not found, the integration is incomplete and needs manual Python-level setup or a plugin update.\\n\\n### Honcho Self-Hosting — ZimaOS Pitfalls\\n\\nSelf-hosting Honcho on ZimaOS has specific gotchas:\\n\\n1. **Docker Compose v5 + buildx incompatibility:** ZimaOS ships an older buildx. Docker Compose v5 refuses with `compose build requires buildx 0.17.0 or later`. Workaround: use `docker build` manually, then start containers with `docker run` (or install an older docker-compose v2 binary).\\n\\n2. **Read-only root filesystem:** `/root/.docker` is on a read-only FS — `sudo docker` fails with `mkdir /root/.docker: read-only file system`. Set `DOCKER_CONFIG=/tmp/docker-config` (or `/DATA/.docker-config`) before invoking docker commands.\\n\\n3. **Docker group access:** After `usermod -aG docker`, the group membership doesn't take effect until next login. Use `sg docker -c \\\"...\\\"` in the same session. Combine with (2): `sg docker -c \\\"DOCKER_CONFIG=/tmp/docker-config docker ps\\\"`.\\n\\n4. **Honcho needs its own LLM key:** Even self-hosted, Honcho requires an LLM provider API key for internal memory operations (deriver, dialectic, dreamer). You can point it at the same Ollama Cloud Pro endpoint Hermes uses — set `LLM_OPENAI_API_KEY` plus per-module `*_MODEL_CONFIG__OVERRIDES__BASE_URL` to `https://ollama.com/v1` in Honcho's `.env`. Every module (deriver, dialectic levels, summary, dream) needs its own base URL override — the global `LLM_BASE_URL` may not propagate to all submodules.\\n\\n5. **Embeddings still go to OpenAI:** Honcho defaults to `text-embedding-3-small` via OpenAI transport. If your LLM proxy doesn't support embeddings, Honcho's deriver will fail. Check with `docker logs honcho-api`.\\n\\n6. **Container naming:** When using `docker run` instead of compose, name the network explicitly so api/deriver/database/redis can resolve each other's hostnames: `docker network create honcho-net`, then `--network honcho-net` on all containers.\\n\\n**Complete self-hosting guide:** `references/honcho-self-hosting.md` — covers Docker Compose setup (including ZimaOS quirks), `.env` template for OpenAI-compatible providers (Ollama, OpenRouter), embedding configuration, and common pitfalls.\\n\\n### Platform-specific issues\\n- **Discord bot silent**: Must enable **Message Content Intent** in Bot → Privileged Gateway Intents.\\n- **Slack bot only works in DMs**: Must subscribe to `message.channels` event. Without it, the bot ignores public channels.\\n- **Windows HTTP 400 \\\"No models provided\\\"**: Config file encoding issue (BOM). Ensure `config.yaml` is saved as UTF-8 without BOM.\\n\\n### Auxiliary models not working\\nIf `auxiliary` tasks (vision, compression, session_search) fail silently, the `auto` provider can't find a backend. Either set `OPENROUTER_API_KEY` or `GOOGLE_API_KEY`, or explicitly configure each auxiliary task's provider:\\n```bash\\nhermes config set auxiliary.vision.provider \\nhermes config set auxiliary.vision.model \\n```\\n\\nFull step-by-step setup for dedicated auxiliary models (recommended for custom providers like Ollama): see `references/auxiliary-model-setup.md` — covers model selection, required context windows, and the exact YAML block to paste.\\n\\nContext compression tuning (threshold, target_ratio, local vs cloud models): see `references/compression-tuning.md`.\\n\\n---\\n\\n## Where to Find Things\\n\\n| Looking for... | Location |\\n|----------------|----------|\\n| Config options | `hermes config edit` or [Configuration docs](https://hermes-agent.nousresearch.com/docs/user-guide/configuration) |\\n| Available tools | `hermes tools list` or [Tools reference](https://hermes-agent.nousresearch.com/docs/reference/tools-reference) |\\n| Slash commands | `/help` in session or [Slash commands reference](https://hermes-agent.nousresearch.com/docs/reference/slash-commands) |\\n| Skills catalog | `hermes skills browse` or [Skills catalog](https://hermes-agent.nousresearch.com/docs/reference/skills-catalog) |\\n| Provider setup | `hermes model` or [Providers guide](https://hermes-agent.nousresearch.com/docs/integrations/providers) |\\n| Platform setup | `hermes gateway setup` or [Messaging docs](https://hermes-agent.nousresearch.com/docs/user-guide/messaging/) |\\n| MCP servers | `hermes mcp list` or [MCP guide](https://hermes-agent.nousresearch.com/docs/user-guide/features/mcp) |\\n| Profiles | `hermes profile list` or [Profiles docs](https://hermes-agent.nousresearch.com/docs/user-guide/profiles) |\\n| Cron jobs | `hermes cron list` or [Cron docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/cron) |\\n| Memory | `hermes memory status` or [Memory docs](https://hermes-agent.nousresearch.com/docs/user-guide/features/memory) |\\n| Env variables | `hermes config env-path` or [Env vars reference](https://hermes-agent.nousresearch.com/docs/reference/environment-variables) |\\n| CLI commands | `hermes --help` or [CLI reference](https://hermes-agent.nousresearch.com/docs/reference/cli-commands) |\\n| Gateway logs | `~/.hermes/logs/gateway.log` |\\n| Session files | `~/.hermes/sessions/` or `hermes sessions browse` |\\n| Source code | `~/.hermes/hermes-agent/` |\\n\\n---\\n\\n## Contributor Quick Reference\\n\\nFor occasional contributors and PR authors. Full developer docs: https://hermes-agent.nousresearch.com/docs/developer-guide/\\n\\n### Project Layout\\n\\n```\\nhermes-agent/\\n├── run_agent.py # AIAgent — core conversation loop\\n├── model_tools.py # Tool discovery and dispatch\\n├── toolsets.py # Toolset definitions\\n├── cli.py # Interactive CLI (HermesCLI)\\n├── hermes_state.py # SQLite session store\\n├── agent/ # Prompt builder, context compression, memory, model routing, credential pooling, skill dispatch\\n├── hermes_cli/ # CLI subcommands, config, setup, commands\\n│ ├── commands.py # Slash command registry (CommandDef)\\n│ ├── config.py # DEFAULT_CONFIG, env var definitions\\n│ └── main.py # CLI entry point and argparse\\n├── tools/ # One file per tool\\n│ └── registry.py # Central tool registry\\n├── gateway/ # Messaging gateway\\n│ └── platforms/ # Platform adapters (telegram, discord, etc.)\\n├── cron/ # Job scheduler\\n├── tests/ # ~3000 pytest tests\\n└── website/ # Docusaurus docs site\\n```\\n\\nConfig: `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys).\\n\\n### Adding a Tool (3 files)\\n\\n**1. Create `tools/your_tool.py`:**\\n```python\\nimport json, os\\nfrom tools.registry import registry\\n\\ndef check_requirements() -> bool:\\n return bool(os.getenv(\\\"EXAMPLE_API_KEY\\\"))\\n\\ndef example_tool(param: str, task_id: str = None) -> str:\\n return json.dumps({\\\"success\\\": True, \\\"data\\\": \\\"...\\\"})\\n\\nregistry.register(\\n name=\\\"example_tool\\\",\\n toolset=\\\"example\\\",\\n schema={\\\"name\\\": \\\"example_tool\\\", \\\"description\\\": \\\"...\\\", \\\"parameters\\\": {...}},\\n handler=lambda args, **kw: example_tool(\\n param=args.get(\\\"param\\\", \\\"\\\"), task_id=kw.get(\\\"task_id\\\")),\\n check_fn=check_requirements,\\n requires_env=[\\\"EXAMPLE_API_KEY\\\"],\\n)\\n```\\n\\n**2. Add to `toolsets.py`** → `_HERMES_CORE_TOOLS` list.\\n\\nAuto-discovery: any `tools/*.py` file with a top-level `registry.register()` call is imported automatically — no manual list needed.\\n\\nAll handlers must return JSON strings. Use `get_hermes_home()` for paths, never hardcode `~/.hermes`.\\n\\n### Adding a Slash Command\\n\\n1. Add `CommandDef` to `COMMAND_REGISTRY` in `hermes_cli/commands.py`\\n2. Add handler in `cli.py` → `process_command()`\\n3. (Optional) Add gateway handler in `gateway/run.py`\\n\\nAll consumers (help text, autocomplete, Telegram menu, Slack mapping) derive from the central registry automatically.\\n\\n### Agent Loop (High Level)\\n\\n```\\nrun_conversation():\\n 1. Build system prompt\\n 2. Loop while iterations < max:\\n a. Call LLM (OpenAI-format messages + tool schemas)\\n b. If tool_calls → dispatch each via handle_function_call() → append results → continue\\n c. If text response → return\\n 3. Context compression triggers automatically near token limit\\n```\\n\\n### Testing\\n\\n```bash\\npython -m pytest tests/ -o 'addopts=' -q # Full suite\\npython -m pytest tests/tools/ -q # Specific area\\n```\\n\\n- Tests auto-redirect `HERMES_HOME` to temp dirs — never touch real `~/.hermes/`\\n- Run full suite before pushing any change\\n- Use `-o 'addopts='` to clear any baked-in pytest flags\\n\\n### Commit Conventions\\n\\n```\\ntype: concise subject line\\n\\nOptional body.\\n```\\n\\nTypes: `fix:`, `feat:`, `refactor:`, `docs:`, `chore:`\\n\\n### Key Rules\\n\\n- **Never break prompt caching** — don't change context, tools, or system prompt mid-conversation\\n- **Message role alternation** — never two assistant or two user messages in a row\\n- Use `get_hermes_home()` from `hermes_constants` for all paths (profile-safe)\\n- Config values go in `config.yaml`, secrets go in `.env`\\n- New tools need a `check_fn` so they only appear when requirements are met\\n\", \"path\": \"autonomous-ai-agents/hermes-agent/SKILL.md\", \"skill_dir\": \"/DATA/.hermes/skills/autonomous-ai-agents/hermes-agent\", \"linked_files\": {\"references\": [\"references/honcho-self-hosting.md\", \"references/ollama-cloud-pro-custom-provider.md\", \"references/honcho-knowledge-bootstrap.md\", \"references/honcho-zimaos-selfhost.md\", \"references/gateway-outage-recovery.md\", \"references/session-recovery.md\", \"references/auxiliary-model-setup.md\", \"references/zimaos-hermes-setup.md\", \"references/compression-tuning.md\", \"references/credential-management.md\", \"references/kiwi-memory-system.md\"]}, \"usage_hint\": \"To view linked files, call skill_view(name, file_path) where file_path is e.g. 'references/api.md' or 'assets/config.yaml'\", \"required_environment_variables\": [], \"required_commands\": [], \"missing_required_environment_variables\": [], \"missing_credential_files\": [], \"missing_required_commands\": [], \"setup_needed\": false, \"setup_skipped\": false, \"readiness_status\": \"available\", \"metadata\": {\"hermes\": {\"tags\": [\"hermes\", \"setup\", \"configuration\", \"multi-agent\", \"spawning\", \"cli\", \"gateway\", \"development\"], \"homepage\": \"https://github.com/NousResearch/hermes-agent\", \"related_skills\": [\"claude-code\", \"codex\", \"opencode\"]}}}", "tool_call_id": "call_0bmxx51l" }, { "role": "assistant", "content": "", "reasoning": "The user wants me to update the \"Abend-Check 20:00\" cronjob (job_id: 0968c1c5dec3) to make the CallKeep part shorter — he only wants to know WHO he needs to call today, nothing else.\n\nLet me look at the current prompt for that cronjob. From the session search, the prompt includes \"1. **CallKeep Telefonate prüfen:** Ru…\". I need to see the full prompt to know exactly what to change.\n\nLet me get the full details of this cronjob. The `cronjob` tool with `action='list'` only gives a preview. Let me see if I can get the full prompt somehow.\n\nActually, the `hermes cron edit` CLI command would let me see and edit it. Let me use terminal to run `hermes cron` or just look at the stored cronjob data.\n\nActually, let me think about this differently. The user wants the Abend-Check to be shorter — specifically for the CallKeep part, only say WHO to call, nothing else. \n\nLet me first look at the actual cron jobs in more detail. I can try reading the cron storage to see the full prompt.", "finish_reason": "tool_calls", "reasoning_content": "The user wants me to update the \"Abend-Check 20:00\" cronjob (job_id: 0968c1c5dec3) to make the CallKeep part shorter — he only wants to know WHO he needs to call today, nothing else.\n\nLet me look at the current prompt for that cronjob. From the session search, the prompt includes \"1. **CallKeep Telefonate prüfen:** Ru…\". I need to see the full prompt to know exactly what to change.\n\nLet me get the full details of this cronjob. The `cronjob` tool with `action='list'` only gives a preview. Let me see if I can get the full prompt somehow.\n\nActually, the `hermes cron edit` CLI command would let me see and edit it. Let me use terminal to run `hermes cron` or just look at the stored cronjob data.\n\nActually, let me think about this differently. The user wants the Abend-Check to be shorter — specifically for the CallKeep part, only say WHO to call, nothing else. \n\nLet me first look at the actual cron jobs in more detail. I can try reading the cron storage to see the full prompt.", "tool_calls": [ { "id": "call_fvorks00", "call_id": "call_fvorks00", "response_item_id": "fc_fvorks00", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"\\nfrom hermes_tools import terminal\\n\\n# Get full cronjob details\\nresult = terminal(\\\"hermes cron list 2\\u003e\\u00261\\\", timeout=10)\\nprint(result[\\\"output\\\"])\\n\"}" } } ] }, { "role": "tool", "name": "execute_code", "content": "{\"status\": \"success\", \"output\": \"/usr/bin/bash: line 3: hermes: command not found\\n\", \"tool_calls_made\": 1, \"duration_seconds\": 0.47}", "tool_call_id": "call_fvorks00" }, { "role": "assistant", "content": "", "reasoning": "The user wants to know which CallKeep cronjob they're referring to. Looking at the cronjob list, there are two jobs:\n\n1. `c11fbac168bd` - \"Morgenbriefing 9:30\" - runs at 9:30 daily, uses google-workspace + daily-dose\n2. `0968c1c5dec3` - \"Abend-Check 20:00\" - runs at 20:00 daily, uses daily-dose\n\nThe Abend-Check has CallKeep in its prompt. Let me look at the session search results - it says the Abend-Check prompt includes \"**CallKeep Telefonate prüfen:** Ru…\"\n\nThe user says \"bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts\" - they want the CallKeep section to be shorter and only tell them who to call today, nothing else.\n\nThe user didn't specify which cronjob - but the \"Morgenbriefing\" at 9:30 seems most likely since that's when they'd want to know who to call today. But actually, looking at the Abend-Check (20:00) - it also has CallKeep. Let me look more carefully.\n\nThe user said \"Zu dem cronjob\" - \"regarding the cronjob\". But which one? The user might be referring to the one that just ran (Morgenbriefing at 9:30) since it's now 9:32 and the last run was 9:31.\n\nActually wait - I need to get the full prompt of both to understand what to change. Let me try with the proper cron tool.\n\nActually, let me re-read: the user is saying \"Zu dem cronjob: bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts.\" - \"Regarding the cronjob: please keep callkeep shorter and really only tell me who I have to call today, nothing else.\"\n\nThis is probably about the morning briefing. But I should clarify which one. Actually, since it's the morning and the user just got the morning briefing at 9:31, that's almost certainly what they're referring to. They want the CallKeep part of the morning briefing to be shorter.\n\nBut actually, looking more carefully - it could also be the Abend-Check which explicitly has CallKeep in its prompt. But the user says \"heute\" (today) - so it's probably the morning briefing telling them who to call today.\n\nLet me look at the cron prompts more carefully. I need to see the actual prompt content. Let me just ask the user which cronjob they mean, or I can look at the prompt preview. It's the Morgenbriefing at 9:30 since it says \"Kalender: Rufe den Google K...\" and it would make sense to include CallKeep there.\n\nWait - looking at the session search result from May 31: \"The assistant stated it would patch the morning briefing prompt but the transcript does not show the actual edit being made.\" So the morning briefing was supposed to be patched but wasn't.\n\nThe Abend-Check has CallKeep as step 1 in its prompt. The user probably wants me to update the Abend-Check's CallKeep section to be shorter. But they could also want the morning briefing to have a shorter CallKeep section.\n\nGiven that the user just received the morning briefing at 9:31 (it ran at 9:31:51), and they're responding now at 9:32, they're likely reacting to the morning briefing that just came in. They want the CallKeep part of it to be shorter.\n\nBut I need to see the actual prompt content. Let me try to get it.\n\nActually, I can use `hermes cron edit` or just look at the state. But `hermes` isn't available as a command. Let me try another approach.\n\nLet me just look at the cron data directory.", "finish_reason": "tool_calls", "reasoning_content": "The user wants to know which CallKeep cronjob they're referring to. Looking at the cronjob list, there are two jobs:\n\n1. `c11fbac168bd` - \"Morgenbriefing 9:30\" - runs at 9:30 daily, uses google-workspace + daily-dose\n2. `0968c1c5dec3` - \"Abend-Check 20:00\" - runs at 20:00 daily, uses daily-dose\n\nThe Abend-Check has CallKeep in its prompt. Let me look at the session search results - it says the Abend-Check prompt includes \"**CallKeep Telefonate prüfen:** Ru…\"\n\nThe user says \"bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts\" - they want the CallKeep section to be shorter and only tell them who to call today, nothing else.\n\nThe user didn't specify which cronjob - but the \"Morgenbriefing\" at 9:30 seems most likely since that's when they'd want to know who to call today. But actually, looking at the Abend-Check (20:00) - it also has CallKeep. Let me look more carefully.\n\nThe user said \"Zu dem cronjob\" - \"regarding the cronjob\". But which one? The user might be referring to the one that just ran (Morgenbriefing at 9:30) since it's now 9:32 and the last run was 9:31.\n\nActually wait - I need to get the full prompt of both to understand what to change. Let me try with the proper cron tool.\n\nActually, let me re-read: the user is saying \"Zu dem cronjob: bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts.\" - \"Regarding the cronjob: please keep callkeep shorter and really only tell me who I have to call today, nothing else.\"\n\nThis is probably about the morning briefing. But I should clarify which one. Actually, since it's the morning and the user just got the morning briefing at 9:31, that's almost certainly what they're referring to. They want the CallKeep part of the morning briefing to be shorter.\n\nBut actually, looking more carefully - it could also be the Abend-Check which explicitly has CallKeep in its prompt. But the user says \"heute\" (today) - so it's probably the morning briefing telling them who to call today.\n\nLet me look at the cron prompts more carefully. I need to see the actual prompt content. Let me just ask the user which cronjob they mean, or I can look at the prompt preview. It's the Morgenbriefing at 9:30 since it says \"Kalender: Rufe den Google K...\" and it would make sense to include CallKeep there.\n\nWait - looking at the session search result from May 31: \"The assistant stated it would patch the morning briefing prompt but the transcript does not show the actual edit being made.\" So the morning briefing was supposed to be patched but wasn't.\n\nThe Abend-Check has CallKeep as step 1 in its prompt. The user probably wants me to update the Abend-Check's CallKeep section to be shorter. But they could also want the morning briefing to have a shorter CallKeep section.\n\nGiven that the user just received the morning briefing at 9:31 (it ran at 9:31:51), and they're responding now at 9:32, they're likely reacting to the morning briefing that just came in. They want the CallKeep part of it to be shorter.\n\nBut I need to see the actual prompt content. Let me try to get it.\n\nActually, I can use `hermes cron edit` or just look at the state. But `hermes` isn't available as a command. Let me try another approach.\n\nLet me just look at the cron data directory.", "tool_calls": [ { "id": "call_7tolp7j3", "call_id": "call_7tolp7j3", "response_item_id": "fc_7tolp7j3", "type": "function", "function": { "name": "search_files", "arguments": "{\"pattern\":\"*.json\",\"target\":\"files\",\"path\":\"/DATA/.hermes/cron\"}" } } ] }, { "role": "tool", "name": "search_files", "content": "{\"total_count\": 1, \"files\": [\"/DATA/.hermes/cron/jobs.json\"]}", "tool_call_id": "call_7tolp7j3" }, { "role": "assistant", "content": "", "reasoning": "Let me read the cron jobs JSON file to see the full details of both jobs.", "finish_reason": "tool_calls", "reasoning_content": "Let me read the cron jobs JSON file to see the full details of both jobs.", "tool_calls": [ { "id": "call_ejk0bhqy", "call_id": "call_ejk0bhqy", "response_item_id": "fc_ejk0bhqy", "type": "function", "function": { "name": "read_file", "arguments": "{\"path\":\"/DATA/.hermes/cron/jobs.json\"}" } } ] }, { "role": "tool", "name": "read_file", "content": "{\"content\": \" 1|{\\n 2| \\\"jobs\\\": [\\n 3| {\\n 4| \\\"id\\\": \\\"c11fbac168bd\\\",\\n 5| \\\"name\\\": \\\"Morgenbriefing 9:30\\\",\\n 6| \\\"prompt\\\": \\\"Morgenbriefing f\\\\u00fcr den Chef (Zeyd). F\\\\u00fchre folgende Schritte aus:\\\\n\\\\n1. **Kalender:** Rufe den Google Kalender f\\\\u00fcr HEUTE ab mit:\\\\n GAPI=\\\\\\\"python /DATA/.hermes/skills/productivity/google-workspace/scripts/google_api.py\\\\\\\"\\\\n $GAPI calendar list --all-calendars\\\\n So werden ALLE Kalender erfasst (primary, Ahmed & Talla, Arbeit, Uni).\\\\n Fasse die heutigen Termine kurz zusammen. Formatiere: \\\\\\\"\\\\ud83d\\\\udcc5 **Heute im Kalender:**\\\\\\\" mit Bullet-Liste aus Summary + Zeit + Kalender. Falls nichts: \\\\\\\"Heute steht nichts im Kalender.\\\\\\\"\\\\n\\\\n2. **Wetter:** Rufe das Wetter f\\\\u00fcr Wien ab mit: `curl -s \\\\\\\"wttr.in/Wien?format=%C+%t+%h+%w\\\\\\\"` und \\\\u00fcbersetze ins Deutsche (z.B. \\\\\\\"Sonnig, 22\\\\u00b0C, Luftfeuchtigkeit 45%, Wind 15km/h\\\\\\\"). Formatiere: \\\\\\\"\\\\ud83c\\\\udf24 **Wetter in Wien:** ...\\\\\\\"\\\\n\\\\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \\\\\\\"\\\\ud83d\\\\udcde **Heutige Anrufe:**\\\\\\\" mit Liste. Falls niemand dran ist: \\\\\\\"Heute steht niemand auf der Anrufliste.\\\\\\\"\\\\n\\\\n4. **DailyDose:** Erinnere den Chef freundlich, seine DailyDose auszuf\\\\u00fcllen. Kurz, motivierend, auf Deutsch. Variiere die Formulierung jedes Mal.\\\\n\\\\n**Ton:** Freundlich, professionell, auf Deutsch. Kurz und \\\\u00fcbersichtlich. Sprich Zeyd mit \\\\\\\"Chef\\\\\\\" an.\\\",\\n 7| \\\"skills\\\": [\\n 8| \\\"google-workspace\\\",\\n 9| \\\"daily-dose\\\"\\n 10| ],\\n 11| \\\"skill\\\": \\\"google-workspace\\\",\\n 12| \\\"model\\\": null,\\n 13| \\\"provider\\\": null,\\n 14| \\\"base_url\\\": null,\\n 15| \\\"script\\\": null,\\n 16| \\\"no_agent\\\": false,\\n 17| \\\"context_from\\\": null,\\n 18| \\\"schedule\\\": {\\n 19| \\\"kind\\\": \\\"cron\\\",\\n 20| \\\"expr\\\": \\\"30 9 * * *\\\",\\n 21| \\\"display\\\": \\\"30 9 * * *\\\"\\n 22| },\\n 23| \\\"schedule_display\\\": \\\"30 9 * * *\\\",\\n 24| \\\"repeat\\\": {\\n 25| \\\"times\\\": null,\\n 26| \\\"completed\\\": 8\\n 27| },\\n 28| \\\"enabled\\\": true,\\n 29| \\\"state\\\": \\\"scheduled\\\",\\n 30| \\\"paused_at\\\": null,\\n 31| \\\"paused_reason\\\": null,\\n 32| \\\"created_at\\\": \\\"2026-05-29T14:00:53.134871+02:00\\\",\\n 33| \\\"next_run_at\\\": \\\"2026-06-07T09:30:00+02:00\\\",\\n 34| \\\"last_run_at\\\": \\\"2026-06-06T09:31:51.804505+02:00\\\",\\n 35| \\\"last_status\\\": \\\"ok\\\",\\n 36| \\\"last_error\\\": null,\\n 37| \\\"last_delivery_error\\\": null,\\n 38| \\\"deliver\\\": \\\"origin\\\",\\n 39| \\\"origin\\\": {\\n 40| \\\"platform\\\": \\\"telegram\\\",\\n 41| \\\"chat_id\\\": \\\"8744435286\\\",\\n 42| \\\"chat_name\\\": \\\"Ahmed Zeyd Aytac\\\",\\n 43| \\\"thread_id\\\": null\\n 44| },\\n 45| \\\"enabled_toolsets\\\": null,\\n 46| \\\"workdir\\\": null\\n 47| },\\n 48| {\\n 49| \\\"id\\\": \\\"0968c1c5dec3\\\",\\n 50| \\\"name\\\": \\\"Abend-Check 20:00\\\",\\n 51| \\\"prompt\\\": \\\"Abend-Check f\\\\u00fcr den Chef (Zeyd). F\\\\u00fchre folgende Schritte aus:\\\\n\\\\n1. **CallKeep Telefonate pr\\\\u00fcfen:** Rufe curl -s http://localhost:3002/api/calls ab. Pr\\\\u00fcfe, ob HEUTE Anrufe verbucht wurden (Feld called_at enth\\\\u00e4lt heutiges Datum 2026-05-29). \\\\n - Falls KEINE Anrufe f\\\\u00fcr heute verbucht sind: Frage den Chef freundlich, ob er heute telefoniert hat und ob er die Anrufe noch in CallKeep eintragen m\\\\u00f6chte.\\\\n - Falls Anrufe verbucht sind: Sage kurz \\\\\\\"Heute wurden X Anrufe verbucht, sehr gut!\\\\\\\" und liste sie kurz (mit wem, wie lange).\\\\n\\\\n2. **DailyDose:** Erinnere den Chef nochmal freundlich, seine DailyDose f\\\\u00fcr heute auszuf\\\\u00fcllen. Kurz, entspannt, auf Deutsch. Variiere die Formulierung jedes Mal.\\\\n\\\\n**Ton:** Entspannt, freundlich, auf Deutsch. Sprich Zeyd mit \\\\\\\"Chef\\\\\\\" an.\\\",\\n 52| \\\"skills\\\": [\\n 53| \\\"daily-dose\\\"\\n 54| ],\\n 55| \\\"skill\\\": \\\"daily-dose\\\",\\n 56| \\\"model\\\": null,\\n 57| \\\"provider\\\": null,\\n 58| \\\"base_url\\\": null,\\n 59| \\\"script\\\": null,\\n 60| \\\"no_agent\\\": false,\\n 61| \\\"context_from\\\": null,\\n 62| \\\"schedule\\\": {\\n 63| \\\"kind\\\": \\\"cron\\\",\\n 64| \\\"expr\\\": \\\"0 20 * * *\\\",\\n 65| \\\"display\\\": \\\"0 20 * * *\\\"\\n 66| },\\n 67| \\\"schedule_display\\\": \\\"0 20 * * *\\\",\\n 68| \\\"repeat\\\": {\\n 69| \\\"times\\\": null,\\n 70| \\\"completed\\\": 8\\n 71| },\\n 72| \\\"enabled\\\": true,\\n 73| \\\"state\\\": \\\"scheduled\\\",\\n 74| \\\"paused_at\\\": null,\\n 75| \\\"paused_reason\\\": null,\\n 76| \\\"created_at\\\": \\\"2026-05-29T14:00:54.140808+02:00\\\",\\n 77| \\\"next_run_at\\\": \\\"2026-06-06T20:00:00+02:00\\\",\\n 78| \\\"last_run_at\\\": \\\"2026-06-05T20:00:46.025136+02:00\\\",\\n 79| \\\"last_status\\\": \\\"ok\\\",\\n 80| \\\"last_error\\\": null,\\n 81| \\\"last_delivery_error\\\": null,\\n 82| \\\"deliver\\\": \\\"origin\\\",\\n 83| \\\"origin\\\": {\\n 84| \\\"platform\\\": \\\"telegram\\\",\\n 85| \\\"chat_id\\\": \\\"8744435286\\\",\\n 86| \\\"chat_name\\\": \\\"Ahmed Zeyd Aytac\\\",\\n 87| \\\"thread_id\\\": null\\n 88| },\\n 89| \\\"enabled_toolsets\\\": null,\\n 90| \\\"workdir\\\": null\\n 91| }\\n 92| ],\\n 93| \\\"updated_at\\\": \\\"2026-06-06T09:31:51.806352+02:00\\\"\\n 94|}\\n 95|\", \"total_lines\": 93, \"file_size\": 4673, \"truncated\": false, \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_ejk0bhqy" }, { "role": "assistant", "content": "Du willst den CallKeep-Teil im Morgenbriefing straffen — nur noch die Namen, keine Floskeln. Ich passe das an.", "reasoning": "Der Chef will den CallKeep-Teil des Morgenbriefings kürzer haben. Nur wen er heute anrufen muss, sonst nichts. Ich muss das komplette prompt des Morgenbriefing-Cronjobs patchen, speziell den CallKeep-Abschnitt (Punkt 3).\n\nAktuell ist der Prompt:\n```\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \"📞 **Heutige Anrufe:**\" mit Liste. Falls niemand dran ist: \"Heute steht niemand auf der Anrufliste.\"\n```\n\nSoll gekürzt werden auf: Nur Liste der Personen, die heute angerufen werden müssen. Kein \"Heute steht niemand auf der Anrufliste\" oder ähnliche Floskeln. Einfach die Namen.\n\nIch patch das prompt in der jobs.json.", "finish_reason": "tool_calls", "reasoning_content": "Der Chef will den CallKeep-Teil des Morgenbriefings kürzer haben. Nur wen er heute anrufen muss, sonst nichts. Ich muss das komplette prompt des Morgenbriefing-Cronjobs patchen, speziell den CallKeep-Abschnitt (Punkt 3).\n\nAktuell ist der Prompt:\n```\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \"📞 **Heutige Anrufe:**\" mit Liste. Falls niemand dran ist: \"Heute steht niemand auf der Anrufliste.\"\n```\n\nSoll gekürzt werden auf: Nur Liste der Personen, die heute angerufen werden müssen. Kein \"Heute steht niemand auf der Anrufliste\" oder ähnliche Floskeln. Einfach die Namen.\n\nIch patch das prompt in der jobs.json.", "tool_calls": [ { "id": "call_h4ste5rd", "call_id": "call_h4ste5rd", "response_item_id": "fc_h4ste5rd", "type": "function", "function": { "name": "patch", "arguments": "{\"mode\":\"replace\",\"path\":\"/DATA/.hermes/cron/jobs.json\",\"old_string\":\"3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \\\\\\\"📞 **Heutige Anrufe:**\\\\\\\" mit Liste. Falls niemand dran ist: \\\\\\\"Heute steht niemand auf der Anrufliste.\\\\\\\"\",\"new_string\":\"3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts und curl -s http://localhost:3002/api/calls ab. Ermittle, WEN Chef heute anrufen muss (Frequenz + letztes Anrufdatum). Ausgabe NUR: \\\\\\\"📞 **Anrufen heute:** Name1, Name2\\\\\\\" — nur die Namen, keine Anmerkungen. Falls niemand: \\\\\\\"📞 **Anrufen heute:** Keine.\\\\\\\"\"}" } } ] }, { "role": "tool", "name": "patch", "content": "{\"success\": false, \"error\": \"Could not find a match for old_string in the file\\n\\nDid you mean one of these sections?\\n 4| \\\"id\\\": \\\"c11fbac168bd\\\",\\n 5| \\\"name\\\": \\\"Morgenbriefing 9:30\\\",\\n 6| \\\"prompt\\\": \\\"Morgenbriefing f\\\\u00fcr den Chef (Zeyd). F\\\\u00fchre folgende Schritte aus:\\\\n\\\\n1. **Kalender:** Rufe den Google Kalender f\\\\u00fcr HEUTE ab mit:\\\\n GAPI=\\\\\\\"python /DATA/.hermes/skills/productivity/google-workspace/scripts/google_api.py\\\\\\\"\\\\n $GAPI calendar list --all-calendars\\\\n So werden ALLE Kalender erfasst (primary, Ahmed & Talla, Arbeit, Uni).\\\\n Fasse die heutigen Termine kurz zusammen. Formatiere: \\\\\\\"\\\\ud83d\\\\udcc5 **Heute im Kalender:**\\\\\\\" mit Bullet-Liste aus Summary + Zeit + Kalender. Falls nichts: \\\\\\\"Heute steht nichts im Kalender.\\\\\\\"\\\\n\\\\n2. **Wetter:** Rufe das Wetter f\\\\u00fcr Wien ab mit: `curl -s \\\\\\\"wttr.in/Wien?format=%C+%t+%h+%w\\\\\\\"` und \\\\u00fcbersetze ins Deutsche (z.B. \\\\\\\"Sonnig, 22\\\\u00b0C, Luftfeuchtigkeit 45%, Wind 15km/h\\\\\\\"). Formatiere: \\\\\\\"\\\\ud83c\\\\udf24 **Wetter in Wien:** ...\\\\\\\"\\\\n\\\\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \\\\\\\"\\\\ud83d\\\\udcde **Heutige Anrufe:**\\\\\\\" mit Liste. Falls niemand dran ist: \\\\\\\"Heute steht niemand auf der Anrufliste.\\\\\\\"\\\\n\\\\n4. **DailyDose:** Erinnere den Chef freundlich, seine DailyDose auszuf\\\\u00fcllen. Kurz, motivierend, auf Deutsch. Variiere die Formulierung jedes Mal.\\\\n\\\\n**Ton:** Freundlich, professionell, auf Deutsch. Kurz und \\\\u00fcbersichtlich. Sprich Zeyd mit \\\\\\\"Chef\\\\\\\" an.\\\",\\n 7| \\\"skills\\\": [\\n 8| \\\"google-workspace\\\",\"}", "tool_call_id": "call_h4ste5rd" }, { "role": "assistant", "content": "The JSON has escaped Unicode. Let me use Python to do this cleanly.", "reasoning": "The old_string didn't match because the JSON file has escaped Unicode characters (like `\\ud83d\\udcde` for 📞). I need to use the exact escaped string from the file. Let me construct the exact old_string from the file content.\n\nFrom the file, line 6 contains the prompt with escaped characters. The relevant part is:\n\n```\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \\\"\\\\ud83d\\\\udcde **Heutige Anrufe:**\\\" mit Liste. Falls niemand dran ist: \\\"Heute steht niemand auf der Anrufliste.\\\"\n```\n\nWait, the issue is that the JSON file stores `\\ud83d\\udcde` which is the JSON-escaped version of `📞`. But when I read the file with `read_file`, it shows `\\ud83d\\udcde` in the raw text shown to me. But the actual file content on disk has `\\ud83d\\udcde` as literal text... Actually, this is tricky. The JSON file stores strings with `\\uXXXX` escape sequences. When the file is loaded by Python's json module, those get decoded to the actual emoji. But on disk, they're stored as the escape sequences.\n\nSo the old_string I need to match against is the raw file content with `\\\\ud83d\\\\udcde` (double-escaped in the `read_file` output, but actually single-escaped on disk: `\\ud83d\\udcde`).\n\nWait, let me re-read: the `read_file` output shows `\\\\ud83d\\\\udcde` — with double backslashes. That means on disk it's `\\ud83d\\udcde` (single backslash-u). When I use `patch`, I'm matching against the raw file bytes. So my old_string needs to contain `\\ud83d\\udcde` (the literal 6 characters: backslash, u, d, 8, 3, d, etc.).\n\nBut I'm using `patch` which does fuzzy matching. Let me try a more targeted approach — use `execute_code` to read the file, modify the JSON, and write it back.", "finish_reason": "tool_calls", "reasoning_content": "The old_string didn't match because the JSON file has escaped Unicode characters (like `\\ud83d\\udcde` for 📞). I need to use the exact escaped string from the file. Let me construct the exact old_string from the file content.\n\nFrom the file, line 6 contains the prompt with escaped characters. The relevant part is:\n\n```\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \\\"\\\\ud83d\\\\udcde **Heutige Anrufe:**\\\" mit Liste. Falls niemand dran ist: \\\"Heute steht niemand auf der Anrufliste.\\\"\n```\n\nWait, the issue is that the JSON file stores `\\ud83d\\udcde` which is the JSON-escaped version of `📞`. But when I read the file with `read_file`, it shows `\\ud83d\\udcde` in the raw text shown to me. But the actual file content on disk has `\\ud83d\\udcde` as literal text... Actually, this is tricky. The JSON file stores strings with `\\uXXXX` escape sequences. When the file is loaded by Python's json module, those get decoded to the actual emoji. But on disk, they're stored as the escape sequences.\n\nSo the old_string I need to match against is the raw file content with `\\\\ud83d\\\\udcde` (double-escaped in the `read_file` output, but actually single-escaped on disk: `\\ud83d\\udcde`).\n\nWait, let me re-read: the `read_file` output shows `\\\\ud83d\\\\udcde` — with double backslashes. That means on disk it's `\\ud83d\\udcde` (single backslash-u). When I use `patch`, I'm matching against the raw file bytes. So my old_string needs to contain `\\ud83d\\udcde` (the literal 6 characters: backslash, u, d, 8, 3, d, etc.).\n\nBut I'm using `patch` which does fuzzy matching. Let me try a more targeted approach — use `execute_code` to read the file, modify the JSON, and write it back.", "tool_calls": [ { "id": "call_4dvvh55o", "call_id": "call_4dvvh55o", "response_item_id": "fc_4dvvh55o", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"\\nimport json\\nfrom hermes_tools import read_file, write_file\\n\\n# Read the jobs file\\nraw = read_file(\\\"/DATA/.hermes/cron/jobs.json\\\", limit=200)\\n\\n# Parse JSON\\ndata = json.loads(raw[\\\"content\\\"])\\n\\n# Update the CallKeep step in the morning briefing prompt\\nold_callkeep = '3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \\\"\\\\ud83d\\\\udcde **Heutige Anrufe:**\\\" mit Liste. Falls niemand dran ist: \\\"Heute steht niemand auf der Anrufliste.\\\"'\\n\\nnew_callkeep = '3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts und curl -s http://localhost:3002/api/calls ab. Ermittle, WEN Chef heute anrufen muss (Frequenz + letztes Anrufdatum). Ausgabe NUR: \\\"\\\\ud83d\\\\udcde **Anrufen heute:** Name1, Name2\\\" — nur die Namen, keine Anmerkungen. Falls niemand: \\\"\\\\ud83d\\\\udcde **Anrufen heute:** Keine.\\\"'\\n\\nfor job in data[\\\"jobs\\\"]:\\n if job[\\\"id\\\"] == \\\"c11fbac168bd\\\":\\n if old_callkeep in job[\\\"prompt\\\"]:\\n job[\\\"prompt\\\"] = job[\\\"prompt\\\"].replace(old_callkeep, new_callkeep)\\n print(\\\"MATCH: Replaced CallKeep step\\\")\\n else:\\n print(\\\"NO MATCH: old string not found in prompt\\\")\\n # Try to find what's actually there\\n if \\\"CallKeep\\\" in job[\\\"prompt\\\"]:\\n idx = job[\\\"prompt\\\"].index(\\\"CallKeep\\\")\\n print(\\\"Found CallKeep at position\\\", idx)\\n # Show surrounding text\\n snippet = job[\\\"prompt\\\"][idx-20:idx+200]\\n print(\\\"Surrounding:\\\", repr(snippet))\\n break\\n\\n# Write back\\nresult = write_file(\\\"/DATA/.hermes/cron/jobs.json\\\", json.dumps(data, indent=2, ensure_ascii=False))\\nprint(\\\"Write result:\\\", result)\\n\"}" } } ] }, { "role": "tool", "name": "execute_code", "content": "{\"status\": \"error\", \"output\": \"\\n--- stderr ---\\nTraceback (most recent call last):\\n File \\\"/tmp/hermes_sandbox_g4jutrsz/script.py\\\", line 9, in \\n data = json.loads(raw[\\\"content\\\"])\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/DATA/AppData/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/json/__init__.py\\\", line 346, in loads\\n return _default_decoder.decode(s)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/DATA/AppData/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/json/decoder.py\\\", line 340, in decode\\n raise JSONDecodeError(\\\"Extra data\\\", s, end)\\njson.decoder.JSONDecodeError: Extra data: line 1 column 7 (char 6)\\n\", \"tool_calls_made\": 1, \"duration_seconds\": 1.25, \"error\": \"Traceback (most recent call last):\\n File \\\"/tmp/hermes_sandbox_g4jutrsz/script.py\\\", line 9, in \\n data = json.loads(raw[\\\"content\\\"])\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/DATA/AppData/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/json/__init__.py\\\", line 346, in loads\\n return _default_decoder.decode(s)\\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\\n File \\\"/DATA/AppData/.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/json/decoder.py\\\", line 340, in decode\\n raise JSONDecodeError(\\\"Extra data\\\", s, end)\\njson.decoder.JSONDecodeError: Extra data: line 1 column 7 (char 6)\\n\"}", "tool_call_id": "call_4dvvh55o" }, { "role": "assistant", "content": "", "reasoning": "The read_file returns the content with line numbers. I need to strip those. Let me use `json_parse` or handle it differently. The `json_parse` function is available. Or I can just use the terminal to read the raw file.", "finish_reason": "tool_calls", "reasoning_content": "The read_file returns the content with line numbers. I need to strip those. Let me use `json_parse` or handle it differently. The `json_parse` function is available. Or I can just use the terminal to read the raw file.", "tool_calls": [ { "id": "call_vt2anbdj", "call_id": "call_vt2anbdj", "response_item_id": "fc_vt2anbdj", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"\\nimport json\\nfrom hermes_tools import terminal, write_file\\n\\n# Read raw file\\nresult = terminal(\\\"cat /DATA/.hermes/cron/jobs.json\\\", timeout=5)\\ndata = json.loads(result[\\\"output\\\"])\\n\\nold_callkeep = '3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \\\"\\\\ud83d\\\\udcde **Heutige Anrufe:**\\\" mit Liste. Falls niemand dran ist: \\\"Heute steht niemand auf der Anrufliste.\\\"'\\n\\nnew_callkeep = '3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts und curl -s http://localhost:3002/api/calls ab. Ermittle, WEN Chef heute anrufen muss (Frequenz + letztes Anrufdatum). Ausgabe NUR: \\\"\\\\ud83d\\\\udcde **Anrufen heute:** Name1, Name2\\\" — nur die Namen, keine Anmerkungen. Falls niemand: \\\"\\\\ud83d\\\\udcde **Anrufen heute:** Keine.\\\"'\\n\\nfound = False\\nfor job in data[\\\"jobs\\\"]:\\n if job[\\\"id\\\"] == \\\"c11fbac168bd\\\":\\n print(\\\"Job found:\\\", job[\\\"name\\\"])\\n if old_callkeep in job[\\\"prompt\\\"]:\\n job[\\\"prompt\\\"] = job[\\\"prompt\\\"].replace(old_callkeep, new_callkeep)\\n print(\\\"✓ Replaced CallKeep step\\\")\\n found = True\\n else:\\n print(\\\"✗ Old string not found\\\")\\n idx = job[\\\"prompt\\\"].find(\\\"CallKeep\\\")\\n if idx \\u003e= 0:\\n print(\\\"'CallKeep' found at index\\\", idx)\\n print(\\\"Snippet:\\\", repr(job[\\\"prompt\\\"][max(0,idx-10):idx+250]))\\n break\\n\\nif found:\\n new_json = json.dumps(data, indent=2, ensure_ascii=False)\\n result = write_file(\\\"/DATA/.hermes/cron/jobs.json\\\", new_json)\\n print(\\\"Write:\\\", result)\\nelse:\\n print(\\\"No changes written\\\")\\n\"}" } } ] }, { "role": "tool", "name": "execute_code", "content": "{\"status\": \"success\", \"output\": \"Job found: Morgenbriefing 9:30\\n✗ Old string not found\\n'CallKeep' found at index 733\\nSnippet: '..\\\"\\\\n\\\\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN Chef heute anrufen sollte (basierend auf Frequenz + letz'\\nNo changes written\\n\", \"tool_calls_made\": 1, \"duration_seconds\": 0.43}", "tool_call_id": "call_vt2anbdj" }, { "role": "assistant", "content": "The emoji encoding differs. Let me match it exactly.", "reasoning": "The issue is with the phone emoji \\ud83d\\udcde - in the JSON it's stored as \"\\ud83d\\udcde\" (the Unicode escape), but in my old_callkeep string I have the actual emoji character. Let me match what's actually in the JSON.", "finish_reason": "tool_calls", "reasoning_content": "The issue is with the phone emoji \\ud83d\\udcde - in the JSON it's stored as \"\\ud83d\\udcde\" (the Unicode escape), but in my old_callkeep string I have the actual emoji character. Let me match what's actually in the JSON.", "tool_calls": [ { "id": "call_icmnc15e", "call_id": "call_icmnc15e", "response_item_id": "fc_icmnc15e", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"\\nimport json\\nfrom hermes_tools import terminal, write_file\\n\\nresult = terminal(\\\"cat /DATA/.hermes/cron/jobs.json\\\", timeout=5)\\ndata = json.loads(result[\\\"output\\\"])\\n\\n# Extract the actual CallKeep section from the JSON to see exact encoding\\nfor job in data[\\\"jobs\\\"]:\\n if job[\\\"id\\\"] == \\\"c11fbac168bd\\\":\\n idx = job[\\\"prompt\\\"].find(\\\"CallKeep\\\")\\n # Find the start of line 3\\n line_start = job[\\\"prompt\\\"].rfind(\\\"3.\\\", 0, idx)\\n # Find the start of line 4\\n line4 = job[\\\"prompt\\\"].find(\\\"4.\\\", line_start + 1)\\n actual_callkeep = job[\\\"prompt\\\"][line_start:line4].rstrip()\\n print(\\\"Actual section:\\\")\\n print(repr(actual_callkeep[:200]))\\n print(\\\"---\\\")\\n print(repr(actual_callkeep[200:]))\\n \\n # Now build replacement using the same encoding\\n new_section = '3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts und curl -s http://localhost:3002/api/calls ab. Ermittle, WEN Chef heute anrufen muss (Frequenz + letztes Anrufdatum). Ausgabe NUR: \\\"' + '\\\\ud83d\\\\udcde' + ' **Anrufen heute:** Name1, Name2\\\" — nur die Namen, keine Anmerkungen. Falls niemand: \\\"' + '\\\\ud83d\\\\udcde' + ' **Anrufen heute:** Keine.\\\"'\\n \\n print(\\\"\\\\nNew section:\\\")\\n print(repr(new_section[:200]))\\n print(\\\"---\\\")\\n print(repr(new_section[200:]))\\n \\n job[\\\"prompt\\\"] = job[\\\"prompt\\\"].replace(actual_callkeep, new_section)\\n \\n new_json = json.dumps(data, indent=2, ensure_ascii=False)\\n result = write_file(\\\"/DATA/.hermes/cron/jobs.json\\\", new_json)\\n print(\\\"\\\\nWrite:\\\", result)\\n\"}" } } ] }, { "role": "tool", "name": "execute_code", "content": "{\"status\": \"success\", \"output\": \"Actual section:\\n'3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts ab. Analysiere die Frequenzen (frequency) und die letzten Anrufe (via curl -s http://localhost:3002/api/calls) und identifiziere, WEN C'\\n---\\n'hef heute anrufen sollte (basierend auf Frequenz + letztem Anruf-Datum). Formatiere: \\\"📞 **Heutige Anrufe:**\\\" mit Liste. Falls niemand dran ist: \\\"Heute steht niemand auf der Anrufliste.\\\"'\\n\\nNew section:\\n'3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts und curl -s http://localhost:3002/api/calls ab. Ermittle, WEN Chef heute anrufen muss (Frequenz + letztes Anrufdatum). Ausgabe NUR: \\\"\\\\ud83d\\\\udcde'\\n---\\n' **Anrufen heute:** Name1, Name2\\\" — nur die Namen, keine Anmerkungen. Falls niemand: \\\"\\\\ud83d\\\\udcde **Anrufen heute:** Keine.\\\"'\\n\\nWrite: {'bytes_written': 4514, 'dirs_created': True, 'lint': {'status': 'ok', 'output': ''}}\\n\", \"tool_calls_made\": 2, \"duration_seconds\": 1.42}", "tool_call_id": "call_icmnc15e" }, { "role": "assistant", "content": "", "reasoning": "The file was written successfully. Let me verify the change took effect by reading it back.", "finish_reason": "tool_calls", "reasoning_content": "The file was written successfully. Let me verify the change took effect by reading it back.", "tool_calls": [ { "id": "call_48e13tmd", "call_id": "call_48e13tmd", "response_item_id": "fc_48e13tmd", "type": "function", "function": { "name": "execute_code", "arguments": "{\"code\":\"\\nfrom hermes_tools import terminal\\n\\n# Verify\\nresult = terminal(\\\"cat /DATA/.hermes/cron/jobs.json\\\", timeout=5)\\ndata = json.loads(result[\\\"output\\\"])\\n\\nfor job in data[\\\"jobs\\\"]:\\n if job[\\\"id\\\"] == \\\"c11fbac168bd\\\":\\n idx = job[\\\"prompt\\\"].find(\\\"CallKeep\\\")\\n line_start = job[\\\"prompt\\\"].rfind(\\\"3.\\\", 0, idx)\\n line4 = job[\\\"prompt\\\"].find(\\\"4.\\\", line_start + 1)\\n print(job[\\\"prompt\\\"][line_start:line4].rstrip())\\n\"}" } } ] }, { "role": "tool", "name": "execute_code", "content": "{\"status\": \"error\", \"output\": \"\\n--- stderr ---\\nTraceback (most recent call last):\\n File \\\"/tmp/hermes_sandbox_umh027_w/script.py\\\", line 6, in \\n data = json.loads(result[\\\"output\\\"])\\n ^^^^\\nNameError: name 'json' is not defined\\n\", \"tool_calls_made\": 1, \"duration_seconds\": 0.44, \"error\": \"Traceback (most recent call last):\\n File \\\"/tmp/hermes_sandbox_umh027_w/script.py\\\", line 6, in \\n data = json.loads(result[\\\"output\\\"])\\n ^^^^\\nNameError: name 'json' is not defined\\n\"}", "tool_call_id": "call_48e13tmd" }, { "role": "assistant", "content": "", "reasoning": "The verification script failed because I forgot to import json. Let me just do a quick grep to verify the change took effect.", "finish_reason": "tool_calls", "reasoning_content": "The verification script failed because I forgot to import json. Let me just do a quick grep to verify the change took effect.", "tool_calls": [ { "id": "call_4mhl6sdv", "call_id": "call_4mhl6sdv", "response_item_id": "fc_4mhl6sdv", "type": "function", "function": { "name": "search_files", "arguments": "{\"path\":\"/DATA/.hermes/cron/jobs.json\",\"pattern\":\"Anrufen heute\",\"target\":\"content\"}" } } ] }, { "role": "tool", "name": "search_files", "content": "{\"total_count\": 1, \"matches\": [{\"path\": \"/DATA/.hermes/cron/jobs.json\", \"line\": 6, \"content\": \" \\\"prompt\\\": \\\"Morgenbriefing für den Chef (Zeyd). Führe folgende Schritte aus:\\\\n\\\\n1. **Kalender:** Rufe den Google Kalender für HEUTE ab mit:\\\\n GAPI=\\\\\\\"python /DATA/.hermes/skills/productivity/google-workspace/scripts/google_api.py\\\\\\\"\\\\n $GAPI calendar list --all-calendars\\\\n So werden ALLE Kalender erfasst (primary, Ahmed & Talla, Arbeit, Uni).\\\\n Fasse die heutigen Termine kurz zusammen. Formatiere: \\\\\\\"📅 **Heute im Kalender:**\\\\\\\" mit Bullet-Liste aus Summary + Zeit + Kalender. Falls nichts\"}]}", "tool_call_id": "call_4mhl6sdv" }, { "role": "assistant", "content": "", "reasoning": "Let me read the actual line with the CallKeep portion to verify it was updated correctly.", "finish_reason": "tool_calls", "reasoning_content": "Let me read the actual line with the CallKeep portion to verify it was updated correctly.", "tool_calls": [ { "id": "call_rz3vz24s", "call_id": "call_rz3vz24s", "response_item_id": "fc_rz3vz24s", "type": "function", "function": { "name": "read_file", "arguments": "{\"path\":\"/DATA/.hermes/cron/jobs.json\",\"offset\":6,\"limit\":1}" } } ] }, { "role": "tool", "name": "read_file", "content": "{\"content\": \" 6| \\\"prompt\\\": \\\"Morgenbriefing für den Chef (Zeyd). Führe folgende Schritte aus:\\\\n\\\\n1. **Kalender:** Rufe den Google Kalender für HEUTE ab mit:\\\\n GAPI=\\\\\\\"python /DATA/.hermes/skills/productivity/google-workspace/scripts/google_api.py\\\\\\\"\\\\n $GAPI calendar list --all-calendars\\\\n So werden ALLE Kalender erfasst (primary, Ahmed & Talla, Arbeit, Uni).\\\\n Fasse die heutigen Termine kurz zusammen. Formatiere: \\\\\\\"📅 **Heute im Kalender:**\\\\\\\" mit Bullet-Liste aus Summary + Zeit + Kalender. Falls nichts: \\\\\\\"Heute steht nichts im Kalender.\\\\\\\"\\\\n\\\\n2. **Wetter:** Rufe das Wetter für Wien ab mit: `curl -s \\\\\\\"wttr.in/Wien?format=%C+%t+%h+%w\\\\\\\"` und übersetze ins Deutsche (z.B. \\\\\\\"Sonnig, 22°C, Luftfeuchtigkeit 45%, Wind 15km/h\\\\\\\"). Formatiere: \\\\\\\"🌤 **Wetter in Wien:** ...\\\\\\\"\\\\n\\\\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts und curl -s http://localhost:3002/api/calls ab. Ermittle, WEN Chef heute anrufen muss (Frequenz + letztes Anrufdatum). Ausgabe NUR: \\\\\\\"📞 **Anrufen heute:** Name1, Name2\\\\\\\" — nur die Namen, keine Anmerkungen. Falls niemand: \\\\\\\"📞 **Anrufen heute:** Keine.\\\\\\\"\\\\n\\\\n4. **DailyDose:** Erinnere den Chef freundlich, seine DailyDose auszufüllen. Kurz, motivierend, auf Deutsch. Variiere die Formulierung jedes Mal.\\\\n\\\\n**Ton:** Freundlich, professionell, auf Deutsch. Kurz und übersichtlich. Sprich Zeyd mit \\\\\\\"Chef\\\\\\\" an.\\\",\\n 7|\", \"total_lines\": 93, \"file_size\": 4514, \"truncated\": true, \"hint\": \"Use offset=7 to continue reading (showing 6-6 of 93 lines)\", \"is_binary\": false, \"is_image\": false}", "tool_call_id": "call_rz3vz24s" }, { "role": "assistant", "content": "Erledigt, Chef. Der CallKeep-Teil im Morgenbriefing ist jetzt auf das Minimum gekürzt:\n\n> 📞 **Anrufen heute:** Name1, Name2\n\nNur die Namen, sonst nichts. Wenn keiner dran ist: *„Keine.“* — ohne Erklärungen oder Floskeln.", "reasoning": "The user wants to shorten the CallKeep section in the cronjob: \"bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts.\"\n\nLet me check which cronjob they're referring to. The Morgenbriefing 9:30 has a CallKeep section. The update is already done — I can see the new text in the jobs.json file:\n\n```\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts und curl -s http://localhost:3002/api/calls ab. Ermittle, WEN Chef heute anrufen muss (Frequenz + letztes Anrufdatum). Ausgabe NUR: \"📞 **Anrufen heute:** Name1, Name2\" — nur die Namen, keine Anmerkungen. Falls niemand: \"📞 **Anrufen heute:** Keine.\"\n```\n\nThis looks good — it's now just:\n- 📞 **Anrufen heute:** Name1, Name2\n- Or: 📞 **Anrufen heute:** Keine.\n\nMuch shorter. Done.", "finish_reason": "stop", "reasoning_content": "The user wants to shorten the CallKeep section in the cronjob: \"bitte halte callkeep kürzer und sage mir wirklich nur wen ich heute anrufen muss, sonst nichts.\"\n\nLet me check which cronjob they're referring to. The Morgenbriefing 9:30 has a CallKeep section. The update is already done — I can see the new text in the jobs.json file:\n\n```\n3. **CallKeep:** Rufe curl -s http://localhost:3002/api/contacts und curl -s http://localhost:3002/api/calls ab. Ermittle, WEN Chef heute anrufen muss (Frequenz + letztes Anrufdatum). Ausgabe NUR: \"📞 **Anrufen heute:** Name1, Name2\" — nur die Namen, keine Anmerkungen. Falls niemand: \"📞 **Anrufen heute:** Keine.\"\n```\n\nThis looks good — it's now just:\n- 📞 **Anrufen heute:** Name1, Name2\n- Or: 📞 **Anrufen heute:** Keine.\n\nMuch shorter. Done." }, { "role": "user", "content": "Review the conversation above and update the skill library. Be ACTIVE — most sessions produce at least one skill update, even if small. A pass that does nothing is a missed learning opportunity, not a neutral outcome.\n\nTarget shape of the library: CLASS-LEVEL skills, each with a rich SKILL.md and a `references/` directory for session-specific detail. Not a long flat list of narrow one-session-one-skill entries. This shapes HOW you update, not WHETHER you update.\n\nSignals to look for (any one of these warrants action):\n • User corrected your style, tone, format, legibility, or verbosity. Frustration signals like 'stop doing X', 'this is too verbose', 'don't format like this', 'why are you explaining', 'just give me the answer', 'you always do Y and I hate it', or an explicit 'remember this' are FIRST-CLASS skill signals, not just memory signals. Update the relevant skill(s) to embed the preference so the next session starts already knowing.\n • User corrected your workflow, approach, or sequence of steps. Encode the correction as a pitfall or explicit step in the skill that governs that class of task.\n • Non-trivial technique, fix, workaround, debugging path, or tool-usage pattern emerged that a future session would benefit from. Capture it.\n • A skill that got loaded or consulted this session turned out to be wrong, missing a step, or outdated. Patch it NOW.\n\nPreference order — prefer the earliest action that fits, but do pick one when a signal above fired:\n 1. UPDATE A CURRENTLY-LOADED SKILL. Look back through the conversation for skills the user loaded via /skill-name or you read via skill_view. If any of them covers the territory of the new learning, PATCH that one first. It is the skill that was in play, so it's the right one to extend.\n 2. UPDATE AN EXISTING UMBRELLA (via skills_list + skill_view). If no loaded skill fits but an existing class-level skill does, patch it. Add a subsection, a pitfall, or broaden a trigger.\n 3. ADD A SUPPORT FILE under an existing umbrella. Skills can be packaged with three kinds of support files — use the right directory per kind:\n • `references/.md` — session-specific detail (error transcripts, reproduction recipes, provider quirks) AND condensed knowledge banks: quoted research, API docs, external authoritative excerpts, or domain notes you found while working on the problem. Write it concise and for the value of the task, not as a full mirror of upstream docs.\n • `templates/.` — starter files meant to be copied and modified (boilerplate configs, scaffolding, a known-good example the agent can `reproduce with modifications`).\n • `scripts/.` — statically re-runnable actions the skill can invoke directly (verification scripts, fixture generators, deterministic probes, anything the agent should run rather than hand-type each time).\n Add support files via skill_manage action=write_file with file_path starting 'references/', 'templates/', or 'scripts/'. The umbrella's SKILL.md should gain a one-line pointer to any new support file so future agents know it exists.\n 4. CREATE A NEW CLASS-LEVEL UMBRELLA SKILL when no existing skill covers the class. The name MUST be at the class level. The name MUST NOT be a specific PR number, error string, feature codename, library-alone name, or 'fix-X / debug-Y / audit-Z-today' session artifact. If the proposed name only makes sense for today's task, it's wrong — fall back to (1), (2), or (3).\n\nUser-preference embedding (important): when the user expressed a style/format/workflow preference, the update belongs in the SKILL.md body, not just in memory. Memory captures 'who the user is and what the current situation and state of your operations are'; skills capture 'how to do this class of task for this user'. When they complain about how you handled a task, the skill that governs that task needs to carry the lesson.\n\nIf you notice two existing skills that overlap, note it in your reply — the background curator handles consolidation at scale.\n\n'Nothing to save.' is a real option but should NOT be the default. If the session ran smoothly with no corrections and produced no new technique, just say 'Nothing to save.' and stop. Otherwise, act." }, { "role": "assistant", "content": "Nothing to save. The session was a straightforward edit to one cronjob prompt — the user wanted the CallKeep output shortened, I made the change. No new technique, no workflow correction, no skill in play that needs patching.", "reasoning": "Nothing in this session involved any of the loaded skills (hermes-agent, callkeep). The user simply asked me to shorten a cronjob prompt, which I did by directly editing jobs.json. No skill was loaded that governs cronjob editing, nor did the user express any new style/format/workflow preference beyond what's already in memory/profile.\n\nWait — let me reconsider. The hermes-agent skill was loaded. It contains cronjob documentation. The user's request was about modifying the CallKeep portion of the morning briefing cronjob to be shorter and more direct. This is a workflow preference about cronjob prompts: keep CallKeep output minimal — just names, no explanations.\n\nBut this is a very specific prompt edit to one cronjob. It's not a class-level pattern about how cronjobs should be written. The user didn't correct my style, tone, or format — he just wanted a specific change to his cronjob prompt. That's a task execution, not a learning opportunity.\n\nNothing to save.", "finish_reason": "stop", "reasoning_content": "Nothing in this session involved any of the loaded skills (hermes-agent, callkeep). The user simply asked me to shorten a cronjob prompt, which I did by directly editing jobs.json. No skill was loaded that governs cronjob editing, nor did the user express any new style/format/workflow preference beyond what's already in memory/profile.\n\nWait — let me reconsider. The hermes-agent skill was loaded. It contains cronjob documentation. The user's request was about modifying the CallKeep portion of the morning briefing cronjob to be shorter and more direct. This is a workflow preference about cronjob prompts: keep CallKeep output minimal — just names, no explanations.\n\nBut this is a very specific prompt edit to one cronjob. It's not a class-level pattern about how cronjobs should be written. The user didn't correct my style, tone, or format — he just wanted a specific change to his cronjob prompt. That's a task execution, not a learning opportunity.\n\nNothing to save." } ] }