{
"session_id": "20260601_112741_926867",
"model": "kimi-k2.6",
"base_url": "https://ollama.com/v1",
"platform": "curator",
"session_start": "2026-06-01T11:27:41.585722",
"last_updated": "2026-06-01T11:50:31.807406",
"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. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n## 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 - kanban-orchestrator: Decomposition playbook + specialist-roster conventions + ...\n - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n - zimaos-camofox-browser: Camofox-Browser als persistenten Docker-Dienst auf ZimaOS...\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 maker-electronics:\n - esp32-desk-dashboard: ESP32-basierte Desk-Dashboards mit AMOLED, LVGL und BLE. ...\n mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n - gif-search: Search/download GIFs from Tenor via curl + jq.\n - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n - 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 - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\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 - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n software-development:\n - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n - spike: Throwaway experiments to validate an idea before build.\n - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n - 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: Monday, June 01, 2026 11:27 AM\nModel: kimi-k2.6\nProvider: custom",
"tools": [
{
"type": "function",
"function": {
"name": "clarify",
"description": "Ask the user a question when you need clarification, feedback, or a decision before proceeding. Supports two modes:\n\n1. **Multiple choice** — provide up to 4 choices. The user picks one or types their own answer via a 5th 'Other' option.\n2. **Open-ended** — omit choices entirely. The user types a free-form response.\n\nUse this tool when:\n- The task is ambiguous and you need the user to choose an approach\n- You want post-task feedback ('How did that work out?')\n- You want to offer to save a skill or update memory\n- A decision has meaningful trade-offs the user should weigh in on\n\nDo NOT use this tool for simple yes/no confirmation of dangerous commands (the terminal tool handles that). Prefer making a reasonable default choice yourself when the decision is low-stakes.",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "The question to present to the user."
},
"choices": {
"type": "array",
"items": {
"type": "string"
},
"maxItems": 4,
"description": "Up to 4 answer choices. Omit this parameter entirely to ask an open-ended question. When provided, the UI automatically appends an 'Other (type your answer)' option."
}
},
"required": [
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "cronjob",
"description": "Manage scheduled cron jobs with a single compressed tool.\n\nUse action='create' to schedule a new job from a prompt or one or more skills.\nUse action='list' to inspect jobs.\nUse action='update', 'pause', 'resume', 'remove', or 'run' to manage an existing job.\n\nTo stop a job the user no longer wants: first action='list' to find the job_id, then action='remove' with that job_id. Never guess job IDs — always list first.\n\nJobs run in a fresh session with no current-chat context, so prompts must be self-contained.\nIf skills are provided on create, the future cron run loads those skills in order, then follows the prompt as the task instruction.\nOn update, passing skills=[] clears attached skills.\n\nNOTE: The agent's final response is auto-delivered to the target. Put the primary\nuser-facing content in the final response. Cron jobs run autonomously with no user\npresent — they cannot ask questions or request clarification.\n\nImportant safety rule: cron-run sessions should not recursively schedule more cron jobs.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"description": "One of: create, list, update, pause, resume, remove, run"
},
"job_id": {
"type": "string",
"description": "Required for update/pause/resume/remove/run"
},
"prompt": {
"type": "string",
"description": "For create: the full self-contained prompt. If skills are also provided, this becomes the task instruction paired with those skills."
},
"schedule": {
"type": "string",
"description": "For create/update: '30m', 'every 2h', '0 9 * * *', or ISO timestamp"
},
"name": {
"type": "string",
"description": "Optional human-friendly name"
},
"repeat": {
"type": "integer",
"description": "Optional repeat count. Omit for defaults (once for one-shot, forever for recurring)."
},
"deliver": {
"type": "string",
"description": "Omit this parameter to auto-deliver back to the current chat and topic (recommended). Auto-detection preserves thread/topic context. Only set explicitly when the user asks to deliver somewhere OTHER than the current conversation. Values: 'origin' (same as omitting), 'local' (no delivery, save only), or platform:chat_id:thread_id for a specific destination. Examples: 'telegram:-1001234567890:17585', 'discord:#engineering', 'sms:+15551234567'. WARNING: 'platform:chat_id' without :thread_id loses topic targeting."
},
"skills": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional ordered list of skill names to load before executing the cron prompt. On update, pass an empty array to clear attached skills."
},
"model": {
"type": "object",
"description": "Optional per-job model override. If provider is omitted, the current main provider is pinned at creation time so the job stays stable.",
"properties": {
"provider": {
"type": "string",
"description": "Provider name (e.g. 'openrouter', 'anthropic', or 'custom:' for a provider defined in custom_providers config — always include the ':' suffix, never pass the bare 'custom'). Omit to use and pin the current provider."
},
"model": {
"type": "string",
"description": "Model name (e.g. 'anthropic/claude-sonnet-4', 'claude-sonnet-4')"
}
},
"required": [
"model"
]
},
"script": {
"type": "string",
"description": "Optional path to a script that runs each tick. In the default mode its stdout is injected into the agent's prompt as context (data-collection / change-detection pattern). With no_agent=True, the script IS the job and its stdout is delivered verbatim (classic watchdog pattern). Relative paths resolve under ~/.hermes/scripts/. ``.sh``/``.bash`` extensions run via bash, everything else via Python. On update, pass empty string to clear."
},
"no_agent": {
"type": "boolean",
"default": false,
"description": "Default: False (LLM-driven job — the agent runs the prompt each tick). Set True to skip the LLM entirely: the scheduler just runs ``script`` on schedule and delivers its stdout verbatim. No tokens, no agent loop, no model override honoured. \n\nREQUIREMENTS when True: ``script`` MUST be set (``prompt`` and ``skills`` are ignored). \n\nDELIVERY SEMANTICS when True: (a) non-empty stdout is sent verbatim as the message; (b) EMPTY stdout means SILENT — nothing is sent to the user and they won't see anything happened, so design your script to stay quiet when there's nothing to report (the watchdog pattern); (c) non-zero exit / timeout sends an error alert so a broken watchdog can't fail silently. \n\nWHEN TO USE True: recurring script-only pings where the script itself produces the exact message text (memory/disk/GPU watchdogs, threshold alerts, heartbeats, CI notifications, API pollers with a fixed output shape). WHEN TO USE False (default): anything that needs reasoning — summarize a feed, draft a daily briefing, pick interesting items, rephrase data for a human, follow conditional logic based on content."
},
"context_from": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional job ID or list of job IDs whose most recent completed output is injected into the prompt as context before each run. Use this to chain cron jobs: job A collects data, job B processes it. Each entry must be a valid job ID (from cronjob action='list'). Note: injects the most recent completed output — does not wait for upstream jobs running in the same tick. On update, pass an empty array to clear."
},
"enabled_toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Optional list of toolset names to restrict the job's agent to (e.g. [\"web\", \"terminal\", \"file\", \"delegation\"]). When set, only tools from these toolsets are loaded, significantly reducing input token overhead. When omitted, all default tools are loaded. Infer from the job's prompt — e.g. use \"web\" if it calls web_search, \"terminal\" if it runs scripts, \"file\" if it reads files, \"delegation\" if it calls delegate_task. On update, pass an empty array to clear."
},
"workdir": {
"type": "string",
"description": "Optional absolute path to run the job from. When set, AGENTS.md / CLAUDE.md / .cursorrules from that directory are injected into the system prompt, and the terminal/file/code_exec tools use it as their working directory — useful for running a job inside a specific project repo. Must be an absolute path that exists. When unset (default), preserves the original behaviour: no project context files, tools use the scheduler's cwd. On update, pass an empty string to clear. Jobs with workdir run sequentially (not parallel) to keep per-job directories isolated."
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "delegate_task",
"description": "Spawn one or more subagents to work on tasks in isolated contexts. Each subagent gets its own conversation, terminal session, and toolset. Only the final summary is returned -- intermediate tool results never enter your context window.\n\nTWO MODES (one of 'goal' or 'tasks' is required):\n1. Single task: provide 'goal' (+ optional context, toolsets)\n2. Batch (parallel): provide 'tasks' array with up to delegation.max_concurrent_children items (default 3, configurable via config.yaml, no hard ceiling). All run concurrently and results are returned together. Nested delegation requires role='orchestrator' and delegation.max_spawn_depth >= 2.\n\nWHEN TO USE delegate_task:\n- Reasoning-heavy subtasks (debugging, code review, research synthesis)\n- Tasks that would flood your context with intermediate data\n- Parallel independent workstreams (research A and B simultaneously)\n\nWHEN NOT TO USE (use these instead):\n- Mechanical multi-step work with no reasoning needed -> use execute_code\n- Single tool call -> just call the tool directly\n- Tasks needing user interaction -> subagents cannot use clarify\n- Durable long-running work that must outlive the current turn -> use cronjob (action='create') or terminal(background=True, notify_on_complete=True) instead. delegate_task runs SYNCHRONOUSLY inside the parent turn: if the parent is interrupted (user sends a new message, /stop, /new) the child is cancelled with status='interrupted' and its work is discarded. Children cannot continue in the background.\n\nIMPORTANT:\n- Subagents have NO memory of your conversation. Pass all relevant info (file paths, error messages, constraints) via the 'context' field.\n- If the user is writing in a non-English language, or asked for output in a specific language / tone / style, say so in 'context' (e.g. \"respond in Chinese\", \"return output in Japanese\"). Otherwise subagents default to English and their summaries will contaminate your final reply with the wrong language.\n- Subagent summaries are SELF-REPORTS, not verified facts. A subagent that claims \"uploaded successfully\" or \"file written\" may be wrong. For operations with external side-effects (HTTP POST/PUT, remote writes, file creation at shared paths, publishing), require the subagent to return a verifiable handle (URL, ID, absolute path, HTTP status) and verify it yourself — fetch the URL, stat the file, read back the content — before telling the user the operation succeeded.\n- Leaf subagents (role='leaf', the default) CANNOT call: delegate_task, clarify, memory, send_message, execute_code.\n- Orchestrator subagents (role='orchestrator') retain delegate_task so they can spawn their own workers, but still cannot use clarify, memory, send_message, or execute_code. Orchestrators are bounded by delegation.max_spawn_depth (default 2) and can be disabled globally via delegation.orchestrator_enabled=false.\n- Each subagent gets its own terminal session (separate working directory and state).\n- Results are always returned as an array, one entry per task.",
"parameters": {
"type": "object",
"properties": {
"goal": {
"type": "string",
"description": "What the subagent should accomplish. Be specific and self-contained -- the subagent knows nothing about your conversation history."
},
"context": {
"type": "string",
"description": "Background information the subagent needs: file paths, error messages, project structure, constraints. The more specific you are, the better the subagent performs."
},
"toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Toolsets to enable for this subagent. Default: inherits your enabled toolsets. Available toolsets: 'browser', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', 'yuanbao'. Common patterns: ['terminal', 'file'] for code work, ['web'] for research, ['browser'] for web interaction, ['terminal', 'file', 'web'] for full-stack tasks."
},
"tasks": {
"type": "array",
"items": {
"type": "object",
"properties": {
"goal": {
"type": "string",
"description": "Task goal"
},
"context": {
"type": "string",
"description": "Task-specific context"
},
"toolsets": {
"type": "array",
"items": {
"type": "string"
},
"description": "Toolsets for this specific task. Available: 'browser', 'cronjob', 'discord', 'discord_admin', 'feishu_doc', 'feishu_drive', 'file', 'homeassistant', 'image_gen', 'kanban', 'search', 'session_search', 'skills', 'spotify', 'terminal', 'todo', 'tts', 'video', 'vision', 'web', 'yuanbao'. Use 'web' for network access, 'terminal' for shell, 'browser' for web interaction."
},
"acp_command": {
"type": "string",
"description": "Per-task ACP command override (e.g. 'claude'). Overrides the top-level acp_command for this task only."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Per-task ACP args override."
},
"role": {
"type": "string",
"enum": [
"leaf",
"orchestrator"
],
"description": "Per-task role override. See top-level 'role' for semantics."
}
},
"required": [
"goal"
]
},
"description": "Batch mode: tasks to run in parallel (limit configurable via delegation.max_concurrent_children, default 3). Each gets its own subagent with isolated context and terminal session. When provided, top-level goal/context/toolsets are ignored."
},
"role": {
"type": "string",
"enum": [
"leaf",
"orchestrator"
],
"description": "Role of the child agent. 'leaf' (default) = focused worker, cannot delegate further. 'orchestrator' = can use delegate_task to spawn its own workers. Requires delegation.max_spawn_depth >= 2 in config; ignored (treated as 'leaf') when the child would exceed max_spawn_depth or when delegation.orchestrator_enabled=false."
},
"acp_command": {
"type": "string",
"description": "Override ACP command for child agents (e.g. 'claude', 'copilot'). When set, children use ACP subprocess transport instead of inheriting the parent's transport. Enables spawning Claude Code (claude --acp --stdio) or other ACP-capable agents from any parent, including Discord/Telegram/CLI."
},
"acp_args": {
"type": "array",
"items": {
"type": "string"
},
"description": "Arguments for the ACP command (default: ['--acp', '--stdio']). Only used when acp_command is set. Example: ['--acp', '--stdio', '--model', 'claude-opus-4-6']"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "execute_code",
"description": "Run a Python script that can call Hermes tools programmatically. Use this when you need 3+ tool calls with processing logic between them, need to filter/reduce large tool outputs before they enter your context, need conditional branching (if X then Y else Z), or need to loop (fetch N pages, process N files, retry on failure).\n\nUse normal tool calls instead when: single tool call with no processing, you need to see the full result and apply complex reasoning, or the task requires interactive user input.\n\nAvailable via `from hermes_tools import ...`:\n\n read_file(path: str, offset: int = 1, limit: int = 500) -> dict\n Lines are 1-indexed. Returns {\"content\": \"...\", \"total_lines\": N}\n write_file(path: str, content: str) -> dict\n Always overwrites the entire file.\n search_files(pattern: str, target=\"content\", path=\".\", file_glob=None, limit=50) -> dict\n target: \"content\" (search inside files) or \"files\" (find files by name). Returns {\"matches\": [...]}\n patch(path: str, old_string: str, new_string: str, replace_all: bool = False) -> dict\n Replaces old_string with new_string in the file.\n terminal(command: str, timeout=None, workdir=None) -> dict\n Foreground only (no background/pty). Returns {\"output\": \"...\", \"exit_code\": N}\n\nLimits: 5-minute timeout, 50KB stdout cap, max 50 tool calls per script. terminal() is foreground-only (no background or pty).\n\nScripts run in the session's working directory with the active venv's python, so project deps (pandas, etc.) and relative paths work like in terminal().\n\nPrint your final result to stdout. Use Python stdlib (json, re, math, csv, datetime, collections, etc.) for processing between tool calls.\n\nAlso available (no import needed — built into hermes_tools):\n json_parse(text: str) — json.loads with strict=False; use for terminal() output with control chars\n shell_quote(s: str) — shlex.quote(); use when interpolating dynamic strings into shell commands\n retry(fn, max_attempts=3, delay=2) — retry with exponential backoff for transient failures",
"parameters": {
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "Python code to execute. Import tools with `from hermes_tools import terminal, ...` and print your final result to stdout."
}
},
"required": [
"code"
]
}
}
},
{
"type": "function",
"function": {
"name": "feishu_doc_read",
"description": "Read the full content of a Feishu/Lark document as plain text. Useful when you need more context beyond the quoted text in a comment.",
"parameters": {
"type": "object",
"properties": {
"doc_token": {
"type": "string",
"description": "The document token (from the document URL or comment context)."
}
},
"required": [
"doc_token"
]
}
}
},
{
"type": "function",
"function": {
"name": "feishu_drive_add_comment",
"description": "Add a new whole-document comment on a Feishu document. Use this for whole-document comments or as a fallback when reply_comment fails with code 1069302.",
"parameters": {
"type": "object",
"properties": {
"file_token": {
"type": "string",
"description": "The document file token."
},
"content": {
"type": "string",
"description": "The comment text content (plain text only, no markdown)."
},
"file_type": {
"type": "string",
"description": "File type (default: docx).",
"default": "docx"
}
},
"required": [
"file_token",
"content"
]
}
}
},
{
"type": "function",
"function": {
"name": "feishu_drive_list_comment_replies",
"description": "List all replies in a comment thread on a Feishu document.",
"parameters": {
"type": "object",
"properties": {
"file_token": {
"type": "string",
"description": "The document file token."
},
"comment_id": {
"type": "string",
"description": "The comment ID to list replies for."
},
"file_type": {
"type": "string",
"description": "File type (default: docx).",
"default": "docx"
},
"page_size": {
"type": "integer",
"description": "Number of replies per page (max 100).",
"default": 100
},
"page_token": {
"type": "string",
"description": "Pagination token for next page."
}
},
"required": [
"file_token",
"comment_id"
]
}
}
},
{
"type": "function",
"function": {
"name": "feishu_drive_list_comments",
"description": "List comments on a Feishu document. Use is_whole=true to list whole-document comments only.",
"parameters": {
"type": "object",
"properties": {
"file_token": {
"type": "string",
"description": "The document file token."
},
"file_type": {
"type": "string",
"description": "File type (default: docx).",
"default": "docx"
},
"is_whole": {
"type": "boolean",
"description": "If true, only return whole-document comments.",
"default": false
},
"page_size": {
"type": "integer",
"description": "Number of comments per page (max 100).",
"default": 100
},
"page_token": {
"type": "string",
"description": "Pagination token for next page."
}
},
"required": [
"file_token"
]
}
}
},
{
"type": "function",
"function": {
"name": "feishu_drive_reply_comment",
"description": "Reply to a local comment thread on a Feishu document. Use this for local (quoted-text) comments. For whole-document comments, use feishu_drive_add_comment instead.",
"parameters": {
"type": "object",
"properties": {
"file_token": {
"type": "string",
"description": "The document file token."
},
"comment_id": {
"type": "string",
"description": "The comment ID to reply to."
},
"content": {
"type": "string",
"description": "The reply text content (plain text only, no markdown)."
},
"file_type": {
"type": "string",
"description": "File type (default: docx).",
"default": "docx"
}
},
"required": [
"file_token",
"comment_id",
"content"
]
}
}
},
{
"type": "function",
"function": {
"name": "memory",
"description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"add",
"replace",
"remove"
],
"description": "The action to perform."
},
"target": {
"type": "string",
"enum": [
"memory",
"user"
],
"description": "Which memory store: 'memory' for personal notes, 'user' for user profile."
},
"content": {
"type": "string",
"description": "The entry content. Required for 'add' and 'replace'."
},
"old_text": {
"type": "string",
"description": "Short unique substring identifying the entry to replace or remove."
}
},
"required": [
"action",
"target"
]
}
}
},
{
"type": "function",
"function": {
"name": "patch",
"description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nReplace mode (default): find a unique string and replace it.\nPatch mode: apply V4A multi-file patches for bulk changes.",
"parameters": {
"type": "object",
"properties": {
"mode": {
"type": "string",
"enum": [
"replace",
"patch"
],
"description": "Edit mode: 'replace' for targeted find-and-replace, 'patch' for V4A multi-file patches",
"default": "replace"
},
"path": {
"type": "string",
"description": "File path to edit (required for 'replace' mode)"
},
"old_string": {
"type": "string",
"description": "Text to find in the file (required for 'replace' mode). Must be unique in the file unless replace_all=true. Include enough surrounding context to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "Replacement text (required for 'replace' mode). Can be empty string to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "Replace all occurrences instead of requiring a unique match (default: false)",
"default": false
},
"patch": {
"type": "string",
"description": "V4A format patch content (required for 'patch' mode). Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch"
}
},
"required": [
"mode"
]
}
}
},
{
"type": "function",
"function": {
"name": "process",
"description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"list",
"poll",
"log",
"wait",
"kill",
"write",
"submit",
"close"
],
"description": "Action to perform on background processes"
},
"session_id": {
"type": "string",
"description": "Process session ID (from terminal background output). Required for all actions except 'list'."
},
"data": {
"type": "string",
"description": "Text to send to process stdin (for 'write' and 'submit' actions)"
},
"timeout": {
"type": "integer",
"description": "Max seconds to block for 'wait' action. Returns partial output on timeout.",
"minimum": 1
},
"offset": {
"type": "integer",
"description": "Line offset for 'log' action (default: last 200 lines)"
},
"limit": {
"type": "integer",
"description": "Max lines to return for 'log' action",
"minimum": 1
}
},
"required": [
"action"
]
}
}
},
{
"type": "function",
"function": {
"name": "read_file",
"description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to read (absolute, relative, or ~/path)"
},
"offset": {
"type": "integer",
"description": "Line number to start reading from (1-indexed, default: 1)",
"default": 1,
"minimum": 1
},
"limit": {
"type": "integer",
"description": "Maximum number of lines to read (default: 500, max: 2000)",
"default": 500,
"maximum": 2000
}
},
"required": [
"path"
]
}
}
},
{
"type": "function",
"function": {
"name": "search_files",
"description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.",
"parameters": {
"type": "object",
"properties": {
"pattern": {
"type": "string",
"description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search"
},
"target": {
"type": "string",
"enum": [
"content",
"files"
],
"description": "'content' searches inside file contents, 'files' searches for files by name",
"default": "content"
},
"path": {
"type": "string",
"description": "Directory or file to search in (default: current working directory)",
"default": "."
},
"file_glob": {
"type": "string",
"description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)"
},
"limit": {
"type": "integer",
"description": "Maximum number of results to return (default: 50)",
"default": 50
},
"offset": {
"type": "integer",
"description": "Skip first N results for pagination (default: 0)",
"default": 0
},
"output_mode": {
"type": "string",
"enum": [
"content",
"files_only",
"count"
],
"description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file",
"default": "content"
},
"context": {
"type": "integer",
"description": "Number of context lines before and after each match (grep mode only)",
"default": 0
}
},
"required": [
"pattern"
]
}
}
},
{
"type": "function",
"function": {
"name": "send_message",
"description": "Send a message to a connected messaging platform, or list available targets.\n\nIMPORTANT: When the user asks to send to a specific channel or person (not just a bare platform name), call send_message(action='list') FIRST to see available targets, then send to the correct one.\nIf the user just says a platform name like 'send to telegram', send directly to the home channel without listing first.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"send",
"list"
],
"description": "Action to perform. 'send' (default) sends a message. 'list' returns all available channels/contacts across connected platforms."
},
"target": {
"type": "string",
"description": "Delivery target. Format: 'platform' (uses home channel), 'platform:#channel-name', 'platform:chat_id', or 'platform:chat_id:thread_id' for Telegram topics and Discord threads. Examples: 'telegram', 'telegram:-1001234567890:17585', 'discord:999888777:555444333', 'discord:#bot-home', 'slack:#engineering', 'signal:+155****4567', 'matrix:!roomid:server.org', 'matrix:@user:server.org', 'yuanbao:direct:' (DM), 'yuanbao:group:' (group chat)"
},
"message": {
"type": "string",
"description": "The message text to send. To send an image or file, include MEDIA: (e.g. 'MEDIA:/tmp/hermes/cache/img_xxx.jpg') in the message — the platform will deliver it as a native media attachment."
}
}
}
}
},
{
"type": "function",
"function": {
"name": "session_search",
"description": "Search your long-term memory of past conversations, or browse recent sessions. This is your recall -- every past session is searchable, and this tool summarizes what happened.\n\nTWO MODES:\n1. Recent sessions (no query): Call with no arguments to see what was worked on recently. Returns titles, previews, and timestamps. Zero LLM cost, instant. Start here when the user asks what were we working on or what did we do recently.\n2. Keyword search (with query): Search for specific topics across all past sessions. Returns LLM-generated summaries of matching sessions.\n\nUSE THIS PROACTIVELY when:\n- The user says 'we did this before', 'remember when', 'last time', 'as I mentioned'\n- The user asks about a topic you worked on before but don't have in current context\n- The user references a project, person, or concept that seems familiar but isn't in memory\n- You want to check if you've solved a similar problem before\n- The user asks 'what did we do about X?' or 'how did we fix Y?'\n\nDon't hesitate to search when it is actually cross-session -- it's fast and cheap. Better to search and confirm than to guess or ask the user to repeat themselves.\n\nSearch syntax: keywords joined with OR for broad recall (elevenlabs OR baseten OR funding), phrases for exact match (\"docker networking\"), boolean (python NOT java), prefix (deploy*). IMPORTANT: Use OR between keywords for best results — FTS5 defaults to AND which misses sessions that only mention some terms. If a broad OR query returns nothing, try individual keyword searches in parallel. Returns summaries of the top matching sessions.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query — keywords, phrases, or boolean expressions to find in past sessions. Omit this parameter entirely to browse recent sessions instead (returns titles, previews, timestamps with no LLM cost)."
},
"role_filter": {
"type": "string",
"description": "Optional: only search messages from specific roles (comma-separated). E.g. 'user,assistant' to skip tool outputs."
},
"limit": {
"type": "integer",
"description": "Max sessions to summarize (default: 3, max: 5).",
"default": 3
}
}
}
}
},
{
"type": "function",
"function": {
"name": "skill_manage",
"description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nOn delete, pass `absorbed_into=` when you're merging this skill's content into another one, or `absorbed_into=\"\"` when you're pruning it with no forwarding target. This lets the curator tell consolidation from pruning without guessing, so downstream consumers (cron jobs that reference the old skill name, etc.) get updated correctly. The target you name in `absorbed_into` must already exist — create/patch the umbrella first, then delete.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.\n\nPinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin `. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.",
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": [
"create",
"patch",
"edit",
"delete",
"write_file",
"remove_file"
],
"description": "The action to perform."
},
"name": {
"type": "string",
"description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file."
},
"content": {
"type": "string",
"description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text."
},
"old_string": {
"type": "string",
"description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness."
},
"new_string": {
"type": "string",
"description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text."
},
"replace_all": {
"type": "boolean",
"description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)."
},
"category": {
"type": "string",
"description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'."
},
"file_path": {
"type": "string",
"description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted."
},
"file_content": {
"type": "string",
"description": "Content for the file. Required for 'write_file'."
},
"absorbed_into": {
"type": "string",
"description": "For 'delete' only — declares intent so the curator can tell consolidation from pruning without guessing. Pass the umbrella skill name when this skill's content was merged into another (the target must already exist). Pass an empty string when the skill is truly stale and being pruned with no forwarding target. Omitting the arg on delete is supported for backward compatibility but downstream tooling (e.g. cron-job skill reference rewriting) will have to guess at intent."
}
},
"required": [
"action",
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skill_view",
"description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "The skill name (use skills_list to see available skills). For plugin-provided skills, use the qualified form 'plugin:skill' (e.g. 'superpowers:writing-plans')."
},
"file_path": {
"type": "string",
"description": "OPTIONAL: Path to a linked file within the skill (e.g., 'references/api.md', 'templates/config.yaml', 'scripts/validate.py'). Omit to get the main SKILL.md content."
}
},
"required": [
"name"
]
}
}
},
{
"type": "function",
"function": {
"name": "skills_list",
"description": "List available skills (name + description). Use skill_view(name) to load full content.",
"parameters": {
"type": "object",
"properties": {
"category": {
"type": "string",
"description": "Optional category filter to narrow results"
}
}
}
}
},
{
"type": "function",
"function": {
"name": "terminal",
"description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n",
"parameters": {
"type": "object",
"properties": {
"command": {
"type": "string",
"description": "The command to execute on the VM"
},
"background": {
"type": "boolean",
"description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.",
"default": false
},
"timeout": {
"type": "integer",
"description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.",
"minimum": 1
},
"workdir": {
"type": "string",
"description": "Working directory for this command (absolute path). Defaults to the session working directory."
},
"pty": {
"type": "boolean",
"description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.",
"default": false
},
"notify_on_complete": {
"type": "boolean",
"description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.",
"default": false
},
"watch_patterns": {
"type": "array",
"items": {
"type": "string"
},
"description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both."
}
},
"required": [
"command"
]
}
}
},
{
"type": "function",
"function": {
"name": "text_to_speech",
"description": "Convert text to speech audio. Returns a MEDIA: path that the platform delivers as native audio. Compatible providers render as a voice bubble on Telegram; otherwise audio is sent as a regular attachment. In CLI mode, saves to ~/voice-memos/. Voice and provider are user-configured (built-in providers like edge/openai or custom command providers under tts.providers.), not model-selected.",
"parameters": {
"type": "object",
"properties": {
"text": {
"type": "string",
"description": "The text to convert to speech. Provider-specific character caps apply and are enforced automatically (OpenAI 4096, xAI 15000, MiniMax 10000, ElevenLabs 5k-40k depending on model); over-long input is truncated."
},
"output_path": {
"type": "string",
"description": "Optional custom file path to save the audio. Defaults to ~/.hermes/audio_cache/.mp3"
}
},
"required": [
"text"
]
}
}
},
{
"type": "function",
"function": {
"name": "todo",
"description": "Manage your task list for the current session. Use for complex tasks with 3+ steps or when the user provides multiple tasks. Call with no parameters to read the current list.\n\nWriting:\n- Provide 'todos' array to create/update items\n- merge=false (default): replace the entire list with a fresh plan\n- merge=true: update existing items by id, add any new ones\n\nEach item: {id: string, content: string, status: pending|in_progress|completed|cancelled}\nList order is priority. Only ONE item in_progress at a time.\nMark items completed immediately when done. If something fails, cancel it and add a revised item.\n\nAlways returns the full current list.",
"parameters": {
"type": "object",
"properties": {
"todos": {
"type": "array",
"description": "Task items to write. Omit to read current list.",
"items": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique item identifier"
},
"content": {
"type": "string",
"description": "Task description"
},
"status": {
"type": "string",
"enum": [
"pending",
"in_progress",
"completed",
"cancelled"
],
"description": "Current status"
}
},
"required": [
"id",
"content",
"status"
]
}
},
"merge": {
"type": "boolean",
"description": "true: update existing items by id, add new ones. false (default): replace the entire list.",
"default": false
}
}
}
}
},
{
"type": "function",
"function": {
"name": "video_analyze",
"description": "Analyze a video from a URL or local file path using a multimodal AI model. Sends the video to a video-capable model (e.g. Gemini) for understanding. Use this for video files — for images, use vision_analyze instead. Supports mp4, webm, mov, avi, mkv, mpeg formats. Note: large videos (>20 MB) may be slow; max ~50 MB.",
"parameters": {
"type": "object",
"properties": {
"video_url": {
"type": "string",
"description": "Video URL (http/https) or local file path to analyze."
},
"question": {
"type": "string",
"description": "Your specific question about the video. The AI will describe what happens in the video and answer your question."
}
},
"required": [
"video_url",
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "vision_analyze",
"description": "Inspect an image from a URL, file path, or tool output when you need closer detail than what's visible in the conversation. If the user's image is already attached to the conversation and you can see it, just answer directly — only call this tool for images referenced by URL/path, images returned inside other tool results (browser screenshots, search thumbnails), or when you need a deeper look at a specific region the main model's vision may have missed.",
"parameters": {
"type": "object",
"properties": {
"image_url": {
"type": "string",
"description": "Image URL (http/https) or local file path to analyze."
},
"question": {
"type": "string",
"description": "Your specific question or request about the image to resolve. The AI will automatically provide a complete image description AND answer your specific question."
}
},
"required": [
"image_url",
"question"
]
}
}
},
{
"type": "function",
"function": {
"name": "write_file",
"description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits. Auto-runs syntax checks on .py/.json/.yaml/.toml and other linted languages; only NEW errors introduced by this write are surfaced (pre-existing errors are filtered out).",
"parameters": {
"type": "object",
"properties": {
"path": {
"type": "string",
"description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)"
},
"content": {
"type": "string",
"description": "Complete content to write to the file"
}
},
"required": [
"path",
"content"
]
}
}
}
],
"message_count": 58,
"messages": [
{
"role": "user",
"content": "You are running as Hermes' background skill CURATOR. This is an UMBRELLA-BUILDING consolidation pass, not a passive audit and not a duplicate-finder.\n\nThe goal of the skill collection is a LIBRARY OF CLASS-LEVEL INSTRUCTIONS AND EXPERIENTIAL KNOWLEDGE. A collection of hundreds of narrow skills where each one captures one session's specific bug is a FAILURE of the library — not a feature. An agent searching skills matches on descriptions, not on exact names; one broad umbrella skill with labeled subsections beats five narrow siblings for discoverability, not the other way around.\n\nThe right target shape is CLASS-LEVEL skills with rich SKILL.md bodies + `references/`, `templates/`, and `scripts/` subfiles for session-specific detail — not one-session-one-skill micro-entries.\n\nHard rules — do not violate:\n1. DO NOT touch bundled or hub-installed skills. The candidate list below is already filtered to agent-created skills only.\n2. DO NOT delete any skill. Archiving (moving the skill's directory into ~/.hermes/skills/.archive/) is the maximum destructive action. Archives are recoverable; deletion is not.\n3. DO NOT touch skills shown as pinned=yes. Skip them entirely.\n4. DO NOT use usage counters as a reason to skip consolidation. The counters are new and often mostly zero. Judge overlap on CONTENT, not on use_count. 'use=0' is not evidence a skill is valuable; it's absence of evidence either way.\n5. DO NOT reject consolidation on the grounds that 'each skill has a distinct trigger'. Pairwise distinctness is the wrong bar. The right bar is: 'would a human maintainer write this as N separate skills, or as one skill with N labeled subsections?' When the answer is the latter, merge.\n\nHow to work — not optional:\n1. Scan the full candidate list. Identify PREFIX CLUSTERS (skills sharing a first word or domain keyword). Examples you are likely to find: hermes-config-*, hermes-dashboard-*, gateway-*, codex-*, ollama-*, anthropic-*, gemini-*, mcp-*, salvage-*, pr-*, competitor-*, python-*, security-*, etc. Expect 10-25 clusters.\n2. For each cluster with 2+ members, do NOT ask 'are these pairs overlapping?' — ask 'what is the UMBRELLA CLASS these skills all serve? Would a maintainer name that class and write one skill for it?' If yes, pick (or create) the umbrella and absorb the siblings into it.\n3. Three ways to consolidate — use the right one per cluster:\n a. MERGE INTO EXISTING UMBRELLA — one skill in the cluster is already broad enough to be the umbrella (example: `pr-triage-salvage` for the PR review cluster). Patch it to add a labeled section for each sibling's unique insight, then archive the siblings.\n b. CREATE A NEW UMBRELLA SKILL.md — no existing member is broad enough. Use skill_manage action=create to write a new class-level skill whose SKILL.md covers the shared workflow and has short labeled subsections. Archive the now-absorbed narrow siblings.\n c. DEMOTE TO REFERENCES/TEMPLATES/SCRIPTS — a sibling has narrow-but-valuable session-specific content. Move it into the umbrella's appropriate support directory:\n • `references/.md` for session-specific detail OR condensed knowledge banks (quoted research, API docs excerpts, domain notes, provider quirks, reproduction recipes)\n • `templates/.` for starter files meant to be copied and modified\n • `scripts/.` for statically re-runnable actions (verification scripts, fixture generators, probes)\n Then archive the old sibling. Use `terminal` with `mkdir -p ~/.hermes/skills//references/ && mv ... /references/.md` (or templates/ / scripts/).\n4. Also flag skills whose NAME is too narrow (contains a PR number, a feature codename, a specific error string, an 'audit' / 'diagnosis' / 'salvage' session artifact). These almost always belong as a subsection or support file under a class-level umbrella.\n5. Iterate. After one consolidation round, scan the remaining set and look for the NEXT umbrella opportunity. Don't stop after 3 merges.\n\nYour toolset:\n - skills_list, skill_view — read the current landscape\n - skill_manage action=patch — add sections to the umbrella\n - skill_manage action=create — create a new umbrella SKILL.md\n - skill_manage action=write_file — add a references/, templates/, or scripts/ file under an existing skill (the skill must already exist)\n - skill_manage action=delete — archive a skill. MUST pass `absorbed_into=` when you've merged its content into another skill, or `absorbed_into=\"\"` when you're truly pruning with no forwarding target. This drives cron-job skill-reference migration — guessing from your YAML summary after the fact is fragile.\n - terminal — mv a sibling into the archive OR move its content into a support subfile\n\n'keep' is a legitimate decision ONLY when the skill is already a class-level umbrella and none of the proposed merges would improve discoverability. 'This is narrow but distinct from its siblings' is NOT a reason to keep — it's a reason to move it under an umbrella as a subsection or support file.\n\nExpected output: real umbrella-ification. Process every obvious cluster. If you end the pass with fewer than 10 archives, you stopped too early — go back and look at the clusters you left alone.\n\nWhen done, write a human summary AND a structured machine-readable block so downstream tooling can distinguish consolidation from pruning. Format EXACTLY:\n\n## Structured summary (required)\n```yaml\nconsolidations:\n - from: \n into: \n reason: \nprunings:\n - name: \n reason: \n```\n\nEvery skill you moved to .archive/ MUST appear in exactly one of the two lists. If you consolidated X into umbrella Y (patched Y, wrote a references file to Y, or created Y with X's content absorbed), X goes under `consolidations` with `into: Y`. If you archived X with no absorption — truly stale, irrelevant, or obsolete — X goes under `prunings`. Leave a list empty (`consolidations: []`) if none. Do not omit the block. The block comes AFTER your human-readable summary of clusters processed, patches made, and decisions left alone.\n\nAgent-created skills (6):\n\n- academic-research state=active pinned=no activity=19 use=6 view=6 patches=7 last_activity=2026-06-01T05:44:52.761037+00:00\n- daily-dose state=active pinned=no activity=45 use=21 view=15 patches=9 last_activity=2026-06-01T07:30:58.713092+00:00\n- esp32-desk-dashboard state=active pinned=no activity=10 use=3 view=2 patches=5 last_activity=2026-05-18T09:17:26.117491+00:00\n- media-file-management state=active pinned=no activity=40 use=14 view=17 patches=9 last_activity=2026-05-30T19:51:51.490644+00:00\n- youtube-automation state=active pinned=no activity=8 use=4 view=3 patches=1 last_activity=2026-05-25T09:23:55.485025+00:00\n- zimaos-web-app state=active pinned=no activity=173 use=50 view=49 patches=74 last_activity=2026-05-25T11:31:23.797087+00:00"
},
{
"role": "assistant",
"content": "",
"reasoning": "The user wants me to act as Hermes' background skill CURATOR and perform an umbrella-building consolidation pass on agent-created skills. Let me first scan the full skills list to see all agent-created skills, then identify clusters and consolidate them.\n\nWait, the user has already provided a filtered list of 6 agent-created skills:\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nBut there might be more agent-created skills that I should see. Let me first call skills_list to get the full picture, including any hub/bundled skills that I should NOT touch.\n\nActually, the user said \"The candidate list below is already filtered to agent-created skills only\" and provided 6 skills. I should work with these 6.\n\nLet me identify clusters among these 6:\n- academic-research: standalone\n- daily-dose: standalone (productivity PWA)\n- esp32-desk-dashboard: standalone (maker electronics / ESP32)\n- media-file-management: standalone (media)\n- youtube-automation: standalone (media / youtube)\n- zimaos-web-app: standalone (web app for ZimaOS)\n\nHmm, only 6 skills and they seem quite distinct from each other. The user says \"Expect 10-25 clusters\" but with only 6 skills, that's not really possible. Let me look more carefully at the descriptions from the skills_list to see if there are overlapping domains.\n\nWait - I should first view the actual skills to understand their content. Maybe some of them overlap more than their names suggest. Let me view all 6.\n\nActually, let me first get the full skills list to confirm the candidate list is complete.",
"finish_reason": "tool_calls",
"reasoning_content": "The user wants me to act as Hermes' background skill CURATOR and perform an umbrella-building consolidation pass on agent-created skills. Let me first scan the full skills list to see all agent-created skills, then identify clusters and consolidate them.\n\nWait, the user has already provided a filtered list of 6 agent-created skills:\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nBut there might be more agent-created skills that I should see. Let me first call skills_list to get the full picture, including any hub/bundled skills that I should NOT touch.\n\nActually, the user said \"The candidate list below is already filtered to agent-created skills only\" and provided 6 skills. I should work with these 6.\n\nLet me identify clusters among these 6:\n- academic-research: standalone\n- daily-dose: standalone (productivity PWA)\n- esp32-desk-dashboard: standalone (maker electronics / ESP32)\n- media-file-management: standalone (media)\n- youtube-automation: standalone (media / youtube)\n- zimaos-web-app: standalone (web app for ZimaOS)\n\nHmm, only 6 skills and they seem quite distinct from each other. The user says \"Expect 10-25 clusters\" but with only 6 skills, that's not really possible. Let me look more carefully at the descriptions from the skills_list to see if there are overlapping domains.\n\nWait - I should first view the actual skills to understand their content. Maybe some of them overlap more than their names suggest. Let me view all 6.\n\nActually, let me first get the full skills list to confirm the candidate list is complete.",
"tool_calls": [
{
"id": "functions.skills_list:0",
"call_id": "functions.skills_list:0",
"response_item_id": "fc_functionsskills_list0",
"type": "function",
"function": {
"name": "skills_list",
"arguments": "{}"
}
}
]
},
{
"role": "tool",
"name": "skills_list",
"content": "{\"success\": true, \"skills\": [{\"name\": \"cad-3d-print\", \"description\": \"Parametric 3D modeling with trimesh for FDM printing. Generates STL with PNG preview and mesh validation. Headless, pure Python — uses direct mesh construction for reliable chamfers and fillets.\", \"category\": null}, {\"name\": \"dogfood\", \"description\": \"Exploratory QA of web apps: find bugs, evidence, reports.\", \"category\": null}, {\"name\": \"yuanbao\", \"description\": \"Yuanbao (元宝) groups: @mention users, query info/members.\", \"category\": null}, {\"name\": \"3d-druck-kiwi\", \"description\": \"Vollständiger Workflow zum Erstellen druckbarer 3D-Modelle aus Textbeschreibungen. Nutzt Python (trimesh + manifold3d) als primären CAD-Engine. Generiert validierte STL/3MF-Dateien für Bambu Lab Drucker.\", \"category\": \"3d-printing\"}, {\"name\": \"claude-code\", \"description\": \"Delegate coding to Claude Code CLI (features, PRs).\", \"category\": \"autonomous-ai-agents\"}, {\"name\": \"hermes-agent\", \"description\": \"Configure, extend, or contribute to Hermes Agent.\", \"category\": \"autonomous-ai-agents\"}, {\"name\": \"opencode\", \"description\": \"Delegate coding to OpenCode CLI (features, PR review).\", \"category\": \"autonomous-ai-agents\"}, {\"name\": \"architecture-diagram\", \"description\": \"Dark-themed SVG architecture/cloud/infra diagrams as HTML.\", \"category\": \"creative\"}, {\"name\": \"ascii-art\", \"description\": \"ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\", \"category\": \"creative\"}, {\"name\": \"ascii-video\", \"description\": \"ASCII video: convert video/audio to colored ASCII MP4/GIF.\", \"category\": \"creative\"}, {\"name\": \"baoyu-comic\", \"description\": \"Knowledge comics (知识漫画): educational, biography, tutorial.\", \"category\": \"creative\"}, {\"name\": \"baoyu-infographic\", \"description\": \"Infographics: 21 layouts x 21 styles (信息图, 可视化).\", \"category\": \"creative\"}, {\"name\": \"claude-design\", \"description\": \"Design one-off HTML artifacts (landing, deck, prototype).\", \"category\": \"creative\"}, {\"name\": \"comfyui\", \"description\": \"Generate images, video, and audio with ComfyUI — install, launch, manage nodes/models, run workflows with parameter injection. Uses the official comfy-cli for lifecycle and direct REST/WebSocket API for execution.\", \"category\": \"creative\"}, {\"name\": \"design-md\", \"description\": \"Author/validate/export Google's DESIGN.md token spec files.\", \"category\": \"creative\"}, {\"name\": \"excalidraw\", \"description\": \"Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\", \"category\": \"creative\"}, {\"name\": \"humanizer\", \"description\": \"Humanize text: strip AI-isms and add real voice.\", \"category\": \"creative\"}, {\"name\": \"ideation\", \"description\": \"Generate project ideas via creative constraints.\", \"category\": \"creative\"}, {\"name\": \"manim-video\", \"description\": \"Manim CE animations: 3Blue1Brown math/algo videos.\", \"category\": \"creative\"}, {\"name\": \"p5js\", \"description\": \"p5.js sketches: gen art, shaders, interactive, 3D.\", \"category\": \"creative\"}, {\"name\": \"pixel-art\", \"description\": \"Pixel art w/ era palettes (NES, Game Boy, PICO-8).\", \"category\": \"creative\"}, {\"name\": \"popular-web-designs\", \"description\": \"54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\", \"category\": \"creative\"}, {\"name\": \"pretext\", \"description\": \"Use when building creative browser demos with @chenglou/pretext — DOM-free text layout for ASCII art, typographic flow around obstacles, text-as-geometry games, kinetic typography, and text-powered generative art. Produces single-file HTML demos by default.\", \"category\": \"creative\"}, {\"name\": \"sketch\", \"description\": \"Throwaway HTML mockups: 2-3 design variants to compare.\", \"category\": \"creative\"}, {\"name\": \"songwriting-and-ai-music\", \"description\": \"Songwriting craft and Suno AI music prompts.\", \"category\": \"creative\"}, {\"name\": \"touchdesigner-mcp\", \"description\": \"Control a running TouchDesigner instance via twozero MCP — create operators, set parameters, wire connections, execute Python, build real-time visuals. 36 native tools.\", \"category\": \"creative\"}, {\"name\": \"jupyter-live-kernel\", \"description\": \"Iterative Python via live Jupyter kernel (hamelnb).\", \"category\": \"data-science\"}, {\"name\": \"kanban-orchestrator\", \"description\": \"Decomposition playbook + specialist-roster conventions + anti-temptation rules for an orchestrator profile routing work through Kanban. The \\\"don't do the work yourself\\\" rule and the basic lifecycle are auto-injected into every kanban worker's system prompt; this skill is the deeper playbook when you're specifically playing the orchestrator role.\", \"category\": \"devops\"}, {\"name\": \"kanban-worker\", \"description\": \"Pitfalls, examples, and edge cases for Hermes Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBAN_GUIDANCE (from agent/prompt_builder.py); this skill is what you load when you want deeper detail on specific scenarios.\", \"category\": \"devops\"}, {\"name\": \"webhook-subscriptions\", \"description\": \"Webhook subscriptions: event-driven agent runs.\", \"category\": \"devops\"}, {\"name\": \"zimaos-camofox-browser\", \"description\": \"Camofox-Browser als persistenten Docker-Dienst auf ZimaOS für Hermes-Browser-Automation einrichten und betreiben.\", \"category\": \"devops\"}, {\"name\": \"himalaya\", \"description\": \"Himalaya CLI: IMAP/SMTP email from terminal.\", \"category\": \"email\"}, {\"name\": \"minecraft-modpack-server\", \"description\": \"Host modded Minecraft servers (CurseForge, Modrinth).\", \"category\": \"gaming\"}, {\"name\": \"pokemon-player\", \"description\": \"Play Pokemon via headless emulator + RAM reads.\", \"category\": \"gaming\"}, {\"name\": \"codebase-inspection\", \"description\": \"Inspect codebases w/ pygount: LOC, languages, ratios.\", \"category\": \"github\"}, {\"name\": \"github-auth\", \"description\": \"GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\", \"category\": \"github\"}, {\"name\": \"github-code-review\", \"description\": \"Review PRs: diffs, inline comments via gh or REST.\", \"category\": \"github\"}, {\"name\": \"github-issues\", \"description\": \"Create, triage, label, assign GitHub issues via gh or REST.\", \"category\": \"github\"}, {\"name\": \"github-pr-workflow\", \"description\": \"GitHub PR lifecycle: branch, commit, open, CI, merge.\", \"category\": \"github\"}, {\"name\": \"github-repo-management\", \"description\": \"Clone/create/fork repos; manage remotes, releases.\", \"category\": \"github\"}, {\"name\": \"esp32-desk-dashboard\", \"description\": \"ESP32-basierte Desk-Dashboards mit AMOLED, LVGL und BLE. Hardware-Auswahl, Firmware-Architektur, Daemon-Design und Tooling für Maker.\", \"category\": \"maker-electronics\"}, {\"name\": \"native-mcp\", \"description\": \"MCP client: connect servers, register tools (stdio/HTTP).\", \"category\": \"mcp\"}, {\"name\": \"gif-search\", \"description\": \"Search/download GIFs from Tenor via curl + jq.\", \"category\": \"media\"}, {\"name\": \"heartmula\", \"description\": \"HeartMuLa: Suno-like song generation from lyrics + tags.\", \"category\": \"media\"}, {\"name\": \"media-file-management\", \"description\": \"Organize and normalize local media files (movies, TV shows, music) on ZimaOS. Rename, deduplicate, audit, and enforce naming conventions.\", \"category\": \"media\"}, {\"name\": \"songsee\", \"description\": \"Audio spectrograms/features (mel, chroma, MFCC) via CLI.\", \"category\": \"media\"}, {\"name\": \"spotify\", \"description\": \"Spotify: play, search, queue, manage playlists and devices.\", \"category\": \"media\"}, {\"name\": \"youtube-automation\", \"description\": \"Zero-cost headless YouTube video factory: Reddit sourcing → TTS → stock footage → ffmpeg assembly.\", \"category\": \"media\"}, {\"name\": \"youtube-content\", \"description\": \"YouTube transcripts to summaries, threads, blogs.\", \"category\": \"media\"}, {\"name\": \"youtube-headless-pipeline\", \"description\": \"Vollautomatische YouTube-Shorts-Pipeline: Reddit-Stories → LLM-generierte deutsche Kurzgeschichte → Conrad TTS → Pexels B-Roll → fertiges 9:16 Short. Keine Kosten, null manuelle Schritte.\", \"category\": \"media\"}, {\"name\": \"audiocraft-audio-generation\", \"description\": \"AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\", \"category\": \"mlops\"}, {\"name\": \"axolotl\", \"description\": \"Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\", \"category\": \"mlops\"}, {\"name\": \"dspy\", \"description\": \"DSPy: declarative LM programs, auto-optimize prompts, RAG.\", \"category\": \"mlops\"}, {\"name\": \"evaluating-llms-harness\", \"description\": \"lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\", \"category\": \"mlops\"}, {\"name\": \"fine-tuning-with-trl\", \"description\": \"TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.\", \"category\": \"mlops\"}, {\"name\": \"huggingface-hub\", \"description\": \"HuggingFace hf CLI: search/download/upload models, datasets.\", \"category\": \"mlops\"}, {\"name\": \"llama-cpp\", \"description\": \"llama.cpp local GGUF inference + HF Hub model discovery.\", \"category\": \"mlops\"}, {\"name\": \"obliteratus\", \"description\": \"OBLITERATUS: abliterate LLM refusals (diff-in-means).\", \"category\": \"mlops\"}, {\"name\": \"outlines\", \"description\": \"Outlines: structured JSON/regex/Pydantic LLM generation.\", \"category\": \"mlops\"}, {\"name\": \"segment-anything-model\", \"description\": \"SAM: zero-shot image segmentation via points, boxes, masks.\", \"category\": \"mlops\"}, {\"name\": \"serving-llms-vllm\", \"description\": \"vLLM: high-throughput LLM serving, OpenAI API, quantization.\", \"category\": \"mlops\"}, {\"name\": \"unsloth\", \"description\": \"Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\", \"category\": \"mlops\"}, {\"name\": \"weights-and-biases\", \"description\": \"W&B: log ML experiments, sweeps, model registry, dashboards.\", \"category\": \"mlops\"}, {\"name\": \"obsidian\", \"description\": \"Read, search, create, and edit notes in the Obsidian vault — 4-level memory system Level 3.\", \"category\": \"note-taking\"}, {\"name\": \"airtable\", \"description\": \"Airtable REST API via curl. Records CRUD, filters, upserts.\", \"category\": \"productivity\"}, {\"name\": \"daily-dose\", \"description\": \"Modify DailyDose (täglicher Aktivitäten-Tracker PWA) — Kategorien, Defaults, Server-Daten. Der Tracker von Zeyd unter /media/HDD_1TB/DailyDose/.\", \"category\": \"productivity\"}, {\"name\": \"docmaster-access\", \"description\": \"Direkter Zugriff auf DocMaster-Dokumente auf ZimaOS — API-Endpunkte, Container-Management, Auth-Steuerung und Migration.\", \"category\": \"productivity\"}, {\"name\": \"google-workspace\", \"description\": \"Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\", \"category\": \"productivity\"}, {\"name\": \"linear\", \"description\": \"Linear: manage issues, projects, teams via GraphQL + curl.\", \"category\": \"productivity\"}, {\"name\": \"maps\", \"description\": \"Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\", \"category\": \"productivity\"}, {\"name\": \"mnemo-access\", \"description\": \"Direkter Zugriff auf Mnemo (Cartographer's Zettelkasten) Docker-Container auf ZimaOS — API, Container-Management, Deploy, CasaOS-Integration.\", \"category\": \"productivity\"}, {\"name\": \"nano-pdf\", \"description\": \"Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\", \"category\": \"productivity\"}, {\"name\": \"notion\", \"description\": \"Notion API via curl: pages, databases, blocks, search.\", \"category\": \"productivity\"}, {\"name\": \"ocr-and-documents\", \"description\": \"Extract text from PDFs/scans (pymupdf, marker-pdf).\", \"category\": \"productivity\"}, {\"name\": \"powerpoint\", \"description\": \"Create, read, edit .pptx decks, slides, notes, templates.\", \"category\": \"productivity\"}, {\"name\": \"godmode\", \"description\": \"Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\", \"category\": \"red-teaming\"}, {\"name\": \"academic-research\", \"description\": \"Research professors, extract/publications, analyze research interests, and develop thesis/Bachelorarbeit topics — optimized for Austrian legal academia (WU Wien, RIS, Jina.ai workaround).\", \"category\": \"research\"}, {\"name\": \"arxiv\", \"description\": \"Search arXiv papers by keyword, author, category, or ID.\", \"category\": \"research\"}, {\"name\": \"blogwatcher\", \"description\": \"Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\", \"category\": \"research\"}, {\"name\": \"llm-wiki\", \"description\": \"Karpathy's LLM Wiki: build/query interlinked markdown KB.\", \"category\": \"research\"}, {\"name\": \"polymarket\", \"description\": \"Query Polymarket: markets, prices, orderbooks, history.\", \"category\": \"research\"}, {\"name\": \"research-paper-writing\", \"description\": \"Write ML papers for NeurIPS/ICML/ICLR: design→submit.\", \"category\": \"research\"}, {\"name\": \"openhue\", \"description\": \"Control Philips Hue lights, scenes, rooms via OpenHue CLI.\", \"category\": \"smart-home\"}, {\"name\": \"xurl\", \"description\": \"X/Twitter via xurl CLI: post, search, DM, media, v2 API.\", \"category\": \"social-media\"}, {\"name\": \"debugging-hermes-tui-commands\", \"description\": \"Debug Hermes TUI slash commands: Python, gateway, Ink UI.\", \"category\": \"software-development\"}, {\"name\": \"hermes-agent-skill-authoring\", \"description\": \"Author in-repo SKILL.md: frontmatter, validator, structure.\", \"category\": \"software-development\"}, {\"name\": \"node-inspect-debugger\", \"description\": \"Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\", \"category\": \"software-development\"}, {\"name\": \"plan\", \"description\": \"Plan mode: write markdown plan to .hermes/plans/, no exec.\", \"category\": \"software-development\"}, {\"name\": \"python-debugpy\", \"description\": \"Debug Python: pdb REPL + debugpy remote (DAP).\", \"category\": \"software-development\"}, {\"name\": \"requesting-code-review\", \"description\": \"Pre-commit review: security scan, quality gates, auto-fix.\", \"category\": \"software-development\"}, {\"name\": \"spike\", \"description\": \"Throwaway experiments to validate an idea before build.\", \"category\": \"software-development\"}, {\"name\": \"subagent-driven-development\", \"description\": \"Execute plans via delegate_task subagents (2-stage review).\", \"category\": \"software-development\"}, {\"name\": \"systematic-debugging\", \"description\": \"4-phase root cause debugging: understand bugs before fixing.\", \"category\": \"software-development\"}, {\"name\": \"test-driven-development\", \"description\": \"TDD: enforce RED-GREEN-REFACTOR, tests before code.\", \"category\": \"software-development\"}, {\"name\": \"writing-plans\", \"description\": \"Write implementation plans: bite-sized tasks, paths, code.\", \"category\": \"software-development\"}, {\"name\": \"zimaos-web-app\", \"description\": \"Build small single-file web apps for ZimaOS using FastAPI + vanilla HTML/CSS/JS. Apple-inspired minimal design, mobile-optimized, no auth unless specified.\", \"category\": \"software-development\"}], \"categories\": [\"3d-printing\", \"autonomous-ai-agents\", \"creative\", \"data-science\", \"devops\", \"email\", \"gaming\", \"github\", \"maker-electronics\", \"mcp\", \"media\", \"mlops\", \"note-taking\", \"productivity\", \"red-teaming\", \"research\", \"smart-home\", \"social-media\", \"software-development\"], \"count\": 96, \"hint\": \"Use skill_view(name) to see full content, tags, and linked files\"}",
"tool_call_id": "functions.skills_list:0"
},
{
"role": "assistant",
"content": "",
"reasoning": "Now I have the full list of 96 skills. I need to identify clusters and consolidate them. Let me first list all the agent-created skills (non-pinned ones, based on the hint in the task that the list is already filtered to agent-created skills). Wait - actually the list returned includes ALL skills, both bundled and agent-created. The task says the candidate list below is filtered to agent-created skills only, but the `skills_list` tool returns all skills including bundled ones.\n\nLooking at the output, I can see bundled skills (like `cad-3d-print`, `dogfood`, `yuanbao`, `3d-druck-kiwi`, `claude-code`, `hermes-agent`, `opencode`, etc.) and the 6 agent-created skills mentioned in the task:\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n\nWait, those 6 are agent-created ones. But the task says I should scan the FULL candidate list - all agent-created skills. There are 96 skills total in the system, but the task only listed 6 as \"agent-created.\" Let me re-read...\n\nOh, actually looking at the task more carefully:\n\n\"Agent-created skills (6):\" - these are the ONLY agent-created ones that need consolidation.\n\nBut that contradicts the instruction to look at the full landscape. Let me look again at the `skills_list` output more carefully. Actually, all 96 skills could be candidates, but the task says the list is already filtered. Wait - the task says \"The candidate list below is already filtered to agent-created skills only.\" and shows only 6 skills.\n\nBut the instructions say to scan the full candidate list and identify prefix clusters. If there are only 6 agent-created skills, there won't be many clusters among them. Let me look at those 6:\n\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nLooking at the full skills_list output, I can see there are many more skills with categories. These might include both bundled and agent-created skills. The task says \"DO NOT touch bundled or hub-installed skills\" - so I need to figure out which ones are agent-created vs bundled.\n\nActually, the task is quite specific: \"Agent-created skills (6):\" and lists exactly those 6. So maybe the full catalog has been growing and the task only lists 6 specific ones from a user's personal collection. But wait - the instructions say \"Process every obvious cluster\" and \"If you end the pass with fewer than 10 archives, you stopped too early.\"\n\nWith only 6 skills, I can't archive 10 of them. This means I need to look at ALL skills and identify which ones are agent-created (i.e., not bundled/hub-installed).\n\nLet me re-examine the task description. \"The candidate list below is already filtered to agent-created skills only.\" This refers to the list of 6. But perhaps the actual environment has more agent-created skills than were listed in the task description.\n\nLet me think about this differently. The `skills_list` returned 96 skills. Many of these look like bundled skills (they have standard names and descriptions). The 6 listed in the task have timestamps, activity counts, etc. But the list itself doesn't tell me which are agent-created vs bundled.\n\nActually, the task specifically says \"Agent-created skills (6):\" and gives me exactly 6 skills with metadata. These 6 probably exist alongside the bundled ones. But that means I should only work with these 6.\n\nWait, but \"If you end the pass with fewer than 10 archives, you stopped too early\" doesn't make sense with only 6 skills. Unless... the 6 listed are just examples or I need to look at the actual skill files on disk to determine which are agent-created.\n\nLet me check. The task instructions are very strict:\n- \"Scan the full candidate list\" \n- \"Identify PREFIX CLUSTERS\"\n- \"Expect 10-25 clusters\"\n- \"If you end the pass with fewer than 10 archives, you stopped too early\"\n\nBut there are only 6 candidate skills. This is a contradiction unless either:\n1. The task description's \"6\" is wrong/outdated and there are more agent-created skills\n2. I need to look at the filesystem directly to find more\n\nLet me view the actual skills directory to see what exists. The bundled skills are likely in a different location than agent-created ones. Actually, looking at the task again:\n\n\"The candidate list below is already filtered to agent-created skills only.\"\n\nThis suggests the 6 listed ARE all the agent-created ones. But then \"fewer than 10 archives\" couldn't be satisfied. So maybe I should look more carefully at the skills list to find others that might be agent-created. Or maybe the 6 listed are just the ones from a previous conversation context, and the actual file system has more.\n\nLet me just proceed with what I have and look at the actual skill content. The task says I should view skills and decide on consolidation. Since I only have 6 agent-created skills listed, let me check if there are more by looking at the file system or by reading the full content of skills from the list.\n\nActually, wait. Looking at the categories in the skills_list output, I see that bundled skills have categories assigned. The 6 agent-created ones I know are:\n- academic-research (category: research)\n- daily-dose (category: productivity)\n- esp32-desk-dashboard (category: maker-electronics)\n- media-file-management (category: media)\n- youtube-automation (category: media)\n- zimaos-web-app (category: software-development)\n\nAre there other skills that might also be agent-created? Let me look for ones that aren't obviously standard bundled skills. Actually, many of the skills look like they could be bundled standard skills (like `cad-3d-print`, `dogfood`, `claude-code`, `hermes-agent`, etc.). \n\nI think what happened is that the task description was written in a context with only 6 agent-created skills, but the expected behavior from the template instructions (expecting 10-25 clusters, 10+ archives) was copy-pasted from a generic curator prompt. Given the constraint \"DO NOT touch bundled or hub-installed skills\" and \"The candidate list below is already filtered to agent-created skills only\", I should ONLY work with the 6 listed skills.\n\nBut with 6 skills, finding 10+ archives is impossible. So either:\n1. There are actually more agent-created skills than listed, OR\n2. The task is somewhat inconsistent and I should do what I can with the 6\n\nGiven that this is an \"umbrella-building\" pass and I need to process clusters, let me work with the 6 agent-created skills and any others that might be agent-created. Let me look at the filesystem to see if there are more.\n\nActually, looking at the categories:\n- `blogwatcher` - could be agent-created\n- `docmaster-access` - specific to ZimaOS, likely agent-created\n- `mnemo-access` - specific to ZimaOS, likely agent-created\n- `zimaos-camofox-browser` - specific to ZimaOS, likely agent-created\n- `youtube-headless-pipeline` - similar to youtube-automation, could be agent-created\n- `3d-druck-kiwi` - German name, could be agent-created\n- `research-paper-writing` - could be agent-created\n\nWait, but the task says \"The candidate list below is already filtered to agent-created skills only.\" and lists:\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n\nMaybe I should view the content of these 6 to see if they reference other skills or if there are obvious clusters. But also maybe there are more agent-created skills that weren't listed in the task text but are on disk. Let me check the ~/.hermes/skills directory.\n\nActually, I think the most reasonable interpretation is: the task lists the specific agent-created skills to work on. The instructions about \"10 archives\" might be a standard template that doesn't apply when there are genuinely only 6 skills. But \"If you end the pass with fewer than 10 archives, you stopped too early\" might mean I should be aggressive about consolidation even among just these 6.\n\nWait - looking again at the task: \"Agent-created skills (6):\" - but the full list returned by skills_list has 96 items. I need to figure out which are the agent-created ones. The task already tells me the 6. But maybe there are more that I should identify by looking at their content or by checking the filesystem.\n\nLet me take a different approach. I'll check the directory structure of ~/.hermes/skills to see what actually exists, and look for agent-created ones.",
"finish_reason": "tool_calls",
"reasoning_content": "Now I have the full list of 96 skills. I need to identify clusters and consolidate them. Let me first list all the agent-created skills (non-pinned ones, based on the hint in the task that the list is already filtered to agent-created skills). Wait - actually the list returned includes ALL skills, both bundled and agent-created. The task says the candidate list below is filtered to agent-created skills only, but the `skills_list` tool returns all skills including bundled ones.\n\nLooking at the output, I can see bundled skills (like `cad-3d-print`, `dogfood`, `yuanbao`, `3d-druck-kiwi`, `claude-code`, `hermes-agent`, `opencode`, etc.) and the 6 agent-created skills mentioned in the task:\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n\nWait, those 6 are agent-created ones. But the task says I should scan the FULL candidate list - all agent-created skills. There are 96 skills total in the system, but the task only listed 6 as \"agent-created.\" Let me re-read...\n\nOh, actually looking at the task more carefully:\n\n\"Agent-created skills (6):\" - these are the ONLY agent-created ones that need consolidation.\n\nBut that contradicts the instruction to look at the full landscape. Let me look again at the `skills_list` output more carefully. Actually, all 96 skills could be candidates, but the task says the list is already filtered. Wait - the task says \"The candidate list below is already filtered to agent-created skills only.\" and shows only 6 skills.\n\nBut the instructions say to scan the full candidate list and identify prefix clusters. If there are only 6 agent-created skills, there won't be many clusters among them. Let me look at those 6:\n\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nLooking at the full skills_list output, I can see there are many more skills with categories. These might include both bundled and agent-created skills. The task says \"DO NOT touch bundled or hub-installed skills\" - so I need to figure out which ones are agent-created vs bundled.\n\nActually, the task is quite specific: \"Agent-created skills (6):\" and lists exactly those 6. So maybe the full catalog has been growing and the task only lists 6 specific ones from a user's personal collection. But wait - the instructions say \"Process every obvious cluster\" and \"If you end the pass with fewer than 10 archives, you stopped too early.\"\n\nWith only 6 skills, I can't archive 10 of them. This means I need to look at ALL skills and identify which ones are agent-created (i.e., not bundled/hub-installed).\n\nLet me re-examine the task description. \"The candidate list below is already filtered to agent-created skills only.\" This refers to the list of 6. But perhaps the actual environment has more agent-created skills than were listed in the task description.\n\nLet me think about this differently. The `skills_list` returned 96 skills. Many of these look like bundled skills (they have standard names and descriptions). The 6 listed in the task have timestamps, activity counts, etc. But the list itself doesn't tell me which are agent-created vs bundled.\n\nActually, the task specifically says \"Agent-created skills (6):\" and gives me exactly 6 skills with metadata. These 6 probably exist alongside the bundled ones. But that means I should only work with these 6.\n\nWait, but \"If you end the pass with fewer than 10 archives, you stopped too early\" doesn't make sense with only 6 skills. Unless... the 6 listed are just examples or I need to look at the actual skill files on disk to determine which are agent-created.\n\nLet me check. The task instructions are very strict:\n- \"Scan the full candidate list\" \n- \"Identify PREFIX CLUSTERS\"\n- \"Expect 10-25 clusters\"\n- \"If you end the pass with fewer than 10 archives, you stopped too early\"\n\nBut there are only 6 candidate skills. This is a contradiction unless either:\n1. The task description's \"6\" is wrong/outdated and there are more agent-created skills\n2. I need to look at the filesystem directly to find more\n\nLet me view the actual skills directory to see what exists. The bundled skills are likely in a different location than agent-created ones. Actually, looking at the task again:\n\n\"The candidate list below is already filtered to agent-created skills only.\"\n\nThis suggests the 6 listed ARE all the agent-created ones. But then \"fewer than 10 archives\" couldn't be satisfied. So maybe I should look more carefully at the skills list to find others that might be agent-created. Or maybe the 6 listed are just the ones from a previous conversation context, and the actual file system has more.\n\nLet me just proceed with what I have and look at the actual skill content. The task says I should view skills and decide on consolidation. Since I only have 6 agent-created skills listed, let me check if there are more by looking at the file system or by reading the full content of skills from the list.\n\nActually, wait. Looking at the categories in the skills_list output, I see that bundled skills have categories assigned. The 6 agent-created ones I know are:\n- academic-research (category: research)\n- daily-dose (category: productivity)\n- esp32-desk-dashboard (category: maker-electronics)\n- media-file-management (category: media)\n- youtube-automation (category: media)\n- zimaos-web-app (category: software-development)\n\nAre there other skills that might also be agent-created? Let me look for ones that aren't obviously standard bundled skills. Actually, many of the skills look like they could be bundled standard skills (like `cad-3d-print`, `dogfood`, `claude-code`, `hermes-agent`, etc.). \n\nI think what happened is that the task description was written in a context with only 6 agent-created skills, but the expected behavior from the template instructions (expecting 10-25 clusters, 10+ archives) was copy-pasted from a generic curator prompt. Given the constraint \"DO NOT touch bundled or hub-installed skills\" and \"The candidate list below is already filtered to agent-created skills only\", I should ONLY work with the 6 listed skills.\n\nBut with 6 skills, finding 10+ archives is impossible. So either:\n1. There are actually more agent-created skills than listed, OR\n2. The task is somewhat inconsistent and I should do what I can with the 6\n\nGiven that this is an \"umbrella-building\" pass and I need to process clusters, let me work with the 6 agent-created skills and any others that might be agent-created. Let me look at the filesystem to see if there are more.\n\nActually, looking at the categories:\n- `blogwatcher` - could be agent-created\n- `docmaster-access` - specific to ZimaOS, likely agent-created\n- `mnemo-access` - specific to ZimaOS, likely agent-created\n- `zimaos-camofox-browser` - specific to ZimaOS, likely agent-created\n- `youtube-headless-pipeline` - similar to youtube-automation, could be agent-created\n- `3d-druck-kiwi` - German name, could be agent-created\n- `research-paper-writing` - could be agent-created\n\nWait, but the task says \"The candidate list below is already filtered to agent-created skills only.\" and lists:\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n\nMaybe I should view the content of these 6 to see if they reference other skills or if there are obvious clusters. But also maybe there are more agent-created skills that weren't listed in the task text but are on disk. Let me check the ~/.hermes/skills directory.\n\nActually, I think the most reasonable interpretation is: the task lists the specific agent-created skills to work on. The instructions about \"10 archives\" might be a standard template that doesn't apply when there are genuinely only 6 skills. But \"If you end the pass with fewer than 10 archives, you stopped too early\" might mean I should be aggressive about consolidation even among just these 6.\n\nWait - looking again at the task: \"Agent-created skills (6):\" - but the full list returned by skills_list has 96 items. I need to figure out which are the agent-created ones. The task already tells me the 6. But maybe there are more that I should identify by looking at their content or by checking the filesystem.\n\nLet me take a different approach. I'll check the directory structure of ~/.hermes/skills to see what actually exists, and look for agent-created ones.",
"tool_calls": [
{
"id": "functions.terminal:1",
"call_id": "functions.terminal:1",
"response_item_id": "fc_functionsterminal1",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"ls -la ~/.hermes/skills/ | head -50\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"total 140\\ndrwxr-xr-x 30 az-a samba 4096 Jun 1 11:27 .\\ndrwx------ 14 az-a samba 4096 Jun 1 11:28 ..\\ndrwxr-xr-x 3 az-a samba 4096 May 11 16:37 3d-printing\\ndrwxr-xr-x 6 az-a samba 4096 May 11 09:36 apple\\ndrwxr-xr-x 5 az-a samba 4096 May 20 18:59 autonomous-ai-agents\\n-rw------- 1 az-a samba 4165 May 24 17:23 .bundled_manifest\\ndrwxr-xr-x 5 az-a samba 4096 May 24 15:57 cad-3d-print\\ndrwxr-xr-x 21 az-a samba 4096 May 11 17:15 creative\\ndrwxr-xr-x 5 az-a samba 4096 Jun 1 11:27 .curator_backups\\n-rw------- 1 az-a samba 244 Jun 1 11:27 .curator_state\\ndrwxr-xr-x 3 az-a samba 4096 May 11 09:36 data-science\\ndrwxr-xr-x 6 az-a samba 4096 May 24 12:11 devops\\ndrwxr-xr-x 2 az-a samba 4096 May 11 09:36 diagramming\\ndrwxr-xr-x 4 az-a samba 4096 May 7 11:58 dogfood\\ndrwxr-xr-x 2 az-a samba 4096 May 11 09:36 domain\\ndrwxr-xr-x 3 az-a samba 4096 May 11 09:36 email\\ndrwxr-xr-x 4 az-a samba 4096 May 11 09:36 gaming\\ndrwxr-xr-x 2 az-a samba 4096 May 11 09:36 gifs\\ndrwxr-xr-x 8 az-a samba 4096 May 11 09:36 github\\ndrwxr-xr-x 2 az-a samba 4096 May 11 09:36 inference-sh\\ndrwxr-xr-x 3 az-a samba 4096 May 12 09:52 maker-electronics\\ndrwxr-xr-x 3 az-a samba 4096 May 11 09:36 mcp\\ndrwxr-xr-x 10 az-a samba 4096 May 15 13:58 media\\ndrwxr-xr-x 9 az-a samba 4096 May 11 09:36 mlops\\ndrwxr-xr-x 3 az-a samba 4096 May 11 09:36 note-taking\\ndrwxr-xr-x 13 az-a samba 4096 May 24 21:01 productivity\\ndrwxr-xr-x 3 az-a samba 4096 May 11 09:36 red-teaming\\ndrwxr-xr-x 8 az-a samba 4096 May 26 12:20 research\\ndrwxr-xr-x 3 az-a samba 4096 May 11 09:36 smart-home\\ndrwxr-xr-x 3 az-a samba 4096 May 11 09:36 social-media\\ndrwxr-xr-x 14 az-a samba 4096 May 17 21:11 software-development\\n-rw------- 1 az-a samba 5761 Jun 1 09:30 .usage.json\\ndrwxr-xr-x 2 az-a samba 4096 May 7 11:58 yuanbao\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "functions.terminal:1"
},
{
"role": "assistant",
"content": "",
"reasoning": "The user wants me to consolidate agent-created skills into umbrella skills. There are only 6 agent-created skills to work with according to the candidate list:\n\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nWait, but looking at the skills_list output, there are 96 skills total. The \"agent-created\" ones are likely those that aren't in bundled form or hub-installed. Let me look again...\n\nActually the user says \"Agent-created skills (6):\" and lists exactly those 6. So those are the ones I need to focus on. Let me view them all and also any potential siblings/clusters they might merge into or with.\n\nLet me look at the full list more carefully to spot clusters, even among the non-agent-created ones. Wait, the instructions say \"DO NOT touch bundled or hub-installed skills. The candidate list below is already filtered to agent-created skills only.\"\n\nI'm CURATOR. I only work on the 6 candidate skills. I need to identify clusters among these 6 and among the broader set they might merge into.\n\nLet me think about clusters/prefixes I can identify by looking at the 6 skills and how they relate to the broader set:\n\n1. **academic-research** - related to research category. Other research skills: arxiv, blogwatcher, llm-wiki, polymarket, research-paper-writing. This is in the 'research' cluster.\n2. **daily-dose** - in 'productivity' category. Other productivity skills: airtable, docmaster-access, google-workspace, linear, maps, mnemo-access, nano-pdf, notion, ocr-and-documents, powerpoint. This is a Zeyd's DailyDose tracker app — very specific project.\n3. **esp32-desk-dashboard** - in 'maker-electronics'. This seems like a specific hardware project. Only one in this category.\n4. **media-file-management** - in 'media' category. Other media skills: gif-search, heartmula, songsee, spotify, youtube-automation, youtube-content, youtube-headless-pipeline. Cluster: media.\n5. **youtube-automation** - also in 'media' category. Related to media-file-management? Not directly — one is about local file organization, the other is about generating YouTube videos.\n6. **zimaos-web-app** - in 'software-development'. This is about building small single-file web apps for a specific ZimaOS platform.\n\nNow looking at related skills:\n- media-file-management + youtube-automation + youtube-content + youtube-headless-pipeline = all deal with media/YouTube. Could there be an umbrella here?\n- zimaos-web-app + zimaos-camofox-browser + maybe zimaOS-specific skills in productivity: docmaster-access, mnemo-access — these are all ZimaOS-specific!\n\nWait — **zimaos-camofox-browser** (devops), **docmaster-access** (productivity), **mnemo-access** (productivity), and **zimaos-web-app** (software-development) are ALL ZimaOS-specific! That's a strong cluster.\n\nBut zimaos-camofox-browser, docmaster-access, mnemo-access are NOT in the candidate list of 6. However, they might be agent-created too and the filter might have just shown me the 6 active ones. Or are they bundled? Let me check.\n\nActually the user said \"Agent-created skills (6):\" — so only those 6 are agent-created. The rest are presumably bundled/hub-installed. So I should NOT touch zimaos-camofox-browser, docmaster-access, mnemo-access if they're not in the candidate list.\n\nBut wait, zimaos-web-app IS agent-created. And there are other ZimaOS skills in the library. However, the user says \"DO NOT touch bundled or hub-installed skills.\" So I can't merge them together if the other ZimaOS skills are bundled. But zimaos-web-app could potentially be absorbed by a ZimaOS umbrella if one existed among agent-created skills, but it doesn't.\n\nSo I have to work WITHIN the 6 agent-created skills (and potentially patch existing umbrellas if one of the 6 should be merged into a bundled umbrella? No, \"DO NOT touch bundled or hub-installed skills\" means I can't modify them).\n\nWait, there's a nuance: \"The candidate list below is already filtered to agent-created skills only.\" This means I only see agent-created skills, but OTHER agent-created skills might exist that aren't shown? No, it says \"Agent-created skills (6):\" — that's the complete set.\n\nSo my task is to consolidate these 6 agent-created skills. Let's look at them:\n\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nAre there obvious clusters?\n- academic-research stands alone (no other agent-created research skill)\n- daily-dose stands alone (specific app)\n- esp32-desk-dashboard stands alone (specific hardware)\n- media-file-management and youtube-automation: both involve media, but one is local file organization and the other is video generation pipeline. Very different workflows.\n- zimaos-web-app stands alone.\n\nBut the instructions say: \"If you end the pass with fewer than 10 archives, you stopped too early — go back and look at the clusters you left alone.\"\n\nWait, there are only 6 agent-created skills. How can I archive 10+ of them? The instruction might be referring to the broader set. Hmm.\n\nLet me re-read: \"Agent-created skills (6):\" — maybe these are newly created but there are others that were created in previous sessions? Or maybe looking at the .curator_state file will show more context.\n\nActually wait, maybe there are skills in the .archive that I should look at? Or maybe there are more agent-created skills than 6 and the message is showing 6 because those are the ones that need processing?\n\nLet me check the .curator_state file and .usage.json to understand the full picture.\n\nAlso: maybe some of the other 96 skills ARE agent-created but were not shown in that summary because they are bundled? The skills_list shows ALL skills. The candidate list was filtered.\n\nActually, the user likely generated that candidate list by querying the system somehow. It's possible there are exactly 6 agent-created skills total.\n\nBut then \"If you end the pass with fewer than 10 archives, you stopped too early\" makes no sense with only 6 candidates. Unless the intent is that I should also look at SKILLS that are agent-created but not in this list — e.g., skills that were already archived, or skills that are in subdirectories.\n\nWait, let me look at the directory listing again. There's `3d-printing/cad-3d-print/` and `3d-printing/3d-druck-kiwi/`. The first one might be `cad-3d-print` and the second `3d-druck-kiwi`. Both are about 3D printing. Are these agent-created? `3d-druck-kiwi` is in the skills_list under category 3d-printing. `cad-3d-print` is also there. But they're not in the candidate list of 6.\n\nSimilarly, there's `media/` directory which might contain multiple skills. Let me explore more.\n\nActually, I realize the candidate list might have been generated recently, and some agent-created skills might have been already archived in previous curator passes. But the current list shows 6 active ones.\n\nBut the instruction says \"If you end the pass with fewer than 10 archives, you stopped too early\". With only 6 candidates, this is impossible unless I need to look at ALL skills more carefully and realize that many more than 6 are actually agent-created. The user's \"Agent-created skills (6)\" might be the output of some filter that only counts RECENTLY agent-created skills, or skills with a certain property.\n\nLet me not rely on the number 6 too heavily. I should look for prefix clusters across ALL skills and then figure out which ones are agent-created. The hard rules say \"DO NOT touch bundled or hub-installed skills. The candidate list below is already filtered to agent-created skills only.\"\n\nSo I must work only on the 6 listed. But then < 10 archives is impossible. Hmm.\n\nMaybe the user expects me to find that some of the other skills are actually agent-created too, and the \"6\" was just what was in the state file, not a final count.\n\nOr... maybe there's a `.curator_state` file that tracks what's pending, and I need to look at it to see all skills that need processing, not just the 6 shown now. Let me check that state file.\n\nActually, let me look at the .usage.json to see all skills and their origins.",
"finish_reason": "tool_calls",
"reasoning_content": "The user wants me to consolidate agent-created skills into umbrella skills. There are only 6 agent-created skills to work with according to the candidate list:\n\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nWait, but looking at the skills_list output, there are 96 skills total. The \"agent-created\" ones are likely those that aren't in bundled form or hub-installed. Let me look again...\n\nActually the user says \"Agent-created skills (6):\" and lists exactly those 6. So those are the ones I need to focus on. Let me view them all and also any potential siblings/clusters they might merge into or with.\n\nLet me look at the full list more carefully to spot clusters, even among the non-agent-created ones. Wait, the instructions say \"DO NOT touch bundled or hub-installed skills. The candidate list below is already filtered to agent-created skills only.\"\n\nI'm CURATOR. I only work on the 6 candidate skills. I need to identify clusters among these 6 and among the broader set they might merge into.\n\nLet me think about clusters/prefixes I can identify by looking at the 6 skills and how they relate to the broader set:\n\n1. **academic-research** - related to research category. Other research skills: arxiv, blogwatcher, llm-wiki, polymarket, research-paper-writing. This is in the 'research' cluster.\n2. **daily-dose** - in 'productivity' category. Other productivity skills: airtable, docmaster-access, google-workspace, linear, maps, mnemo-access, nano-pdf, notion, ocr-and-documents, powerpoint. This is a Zeyd's DailyDose tracker app — very specific project.\n3. **esp32-desk-dashboard** - in 'maker-electronics'. This seems like a specific hardware project. Only one in this category.\n4. **media-file-management** - in 'media' category. Other media skills: gif-search, heartmula, songsee, spotify, youtube-automation, youtube-content, youtube-headless-pipeline. Cluster: media.\n5. **youtube-automation** - also in 'media' category. Related to media-file-management? Not directly — one is about local file organization, the other is about generating YouTube videos.\n6. **zimaos-web-app** - in 'software-development'. This is about building small single-file web apps for a specific ZimaOS platform.\n\nNow looking at related skills:\n- media-file-management + youtube-automation + youtube-content + youtube-headless-pipeline = all deal with media/YouTube. Could there be an umbrella here?\n- zimaos-web-app + zimaos-camofox-browser + maybe zimaOS-specific skills in productivity: docmaster-access, mnemo-access — these are all ZimaOS-specific!\n\nWait — **zimaos-camofox-browser** (devops), **docmaster-access** (productivity), **mnemo-access** (productivity), and **zimaos-web-app** (software-development) are ALL ZimaOS-specific! That's a strong cluster.\n\nBut zimaos-camofox-browser, docmaster-access, mnemo-access are NOT in the candidate list of 6. However, they might be agent-created too and the filter might have just shown me the 6 active ones. Or are they bundled? Let me check.\n\nActually the user said \"Agent-created skills (6):\" — so only those 6 are agent-created. The rest are presumably bundled/hub-installed. So I should NOT touch zimaos-camofox-browser, docmaster-access, mnemo-access if they're not in the candidate list.\n\nBut wait, zimaos-web-app IS agent-created. And there are other ZimaOS skills in the library. However, the user says \"DO NOT touch bundled or hub-installed skills.\" So I can't merge them together if the other ZimaOS skills are bundled. But zimaos-web-app could potentially be absorbed by a ZimaOS umbrella if one existed among agent-created skills, but it doesn't.\n\nSo I have to work WITHIN the 6 agent-created skills (and potentially patch existing umbrellas if one of the 6 should be merged into a bundled umbrella? No, \"DO NOT touch bundled or hub-installed skills\" means I can't modify them).\n\nWait, there's a nuance: \"The candidate list below is already filtered to agent-created skills only.\" This means I only see agent-created skills, but OTHER agent-created skills might exist that aren't shown? No, it says \"Agent-created skills (6):\" — that's the complete set.\n\nSo my task is to consolidate these 6 agent-created skills. Let's look at them:\n\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nAre there obvious clusters?\n- academic-research stands alone (no other agent-created research skill)\n- daily-dose stands alone (specific app)\n- esp32-desk-dashboard stands alone (specific hardware)\n- media-file-management and youtube-automation: both involve media, but one is local file organization and the other is video generation pipeline. Very different workflows.\n- zimaos-web-app stands alone.\n\nBut the instructions say: \"If you end the pass with fewer than 10 archives, you stopped too early — go back and look at the clusters you left alone.\"\n\nWait, there are only 6 agent-created skills. How can I archive 10+ of them? The instruction might be referring to the broader set. Hmm.\n\nLet me re-read: \"Agent-created skills (6):\" — maybe these are newly created but there are others that were created in previous sessions? Or maybe looking at the .curator_state file will show more context.\n\nActually wait, maybe there are skills in the .archive that I should look at? Or maybe there are more agent-created skills than 6 and the message is showing 6 because those are the ones that need processing?\n\nLet me check the .curator_state file and .usage.json to understand the full picture.\n\nAlso: maybe some of the other 96 skills ARE agent-created but were not shown in that summary because they are bundled? The skills_list shows ALL skills. The candidate list was filtered.\n\nActually, the user likely generated that candidate list by querying the system somehow. It's possible there are exactly 6 agent-created skills total.\n\nBut then \"If you end the pass with fewer than 10 archives, you stopped too early\" makes no sense with only 6 candidates. Unless the intent is that I should also look at SKILLS that are agent-created but not in this list — e.g., skills that were already archived, or skills that are in subdirectories.\n\nWait, let me look at the directory listing again. There's `3d-printing/cad-3d-print/` and `3d-printing/3d-druck-kiwi/`. The first one might be `cad-3d-print` and the second `3d-druck-kiwi`. Both are about 3D printing. Are these agent-created? `3d-druck-kiwi` is in the skills_list under category 3d-printing. `cad-3d-print` is also there. But they're not in the candidate list of 6.\n\nSimilarly, there's `media/` directory which might contain multiple skills. Let me explore more.\n\nActually, I realize the candidate list might have been generated recently, and some agent-created skills might have been already archived in previous curator passes. But the current list shows 6 active ones.\n\nBut the instruction says \"If you end the pass with fewer than 10 archives, you stopped too early\". With only 6 candidates, this is impossible unless I need to look at ALL skills more carefully and realize that many more than 6 are actually agent-created. The user's \"Agent-created skills (6)\" might be the output of some filter that only counts RECENTLY agent-created skills, or skills with a certain property.\n\nLet me not rely on the number 6 too heavily. I should look for prefix clusters across ALL skills and then figure out which ones are agent-created. The hard rules say \"DO NOT touch bundled or hub-installed skills. The candidate list below is already filtered to agent-created skills only.\"\n\nSo I must work only on the 6 listed. But then < 10 archives is impossible. Hmm.\n\nMaybe the user expects me to find that some of the other skills are actually agent-created too, and the \"6\" was just what was in the state file, not a final count.\n\nOr... maybe there's a `.curator_state` file that tracks what's pending, and I need to look at it to see all skills that need processing, not just the 6 shown now. Let me check that state file.\n\nActually, let me look at the .usage.json to see all skills and their origins.",
"tool_calls": [
{
"id": "functions.terminal:2",
"call_id": "functions.terminal:2",
"response_item_id": "fc_functionsterminal2",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"cat ~/.hermes/skills/.curator_state \\u0026\\u0026 echo \\\"---\\\" \\u0026\\u0026 cat ~/.hermes/skills/.usage.json\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"{\\n \\\"last_report_path\\\": \\\"/DATA/.hermes/logs/curator/20260525-092322\\\",\\n \\\"last_run_at\\\": \\\"2026-06-01T09:27:40.550916+00:00\\\",\\n \\\"last_run_duration_seconds\\\": 96.225624,\\n \\\"last_run_summary\\\": \\\"auto: no changes\\\",\\n \\\"paused\\\": false,\\n \\\"run_count\\\": 3\\n}---\\n{\\n \\\"3d-druck-kiwi\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-11T14:37:32.022724+00:00\\\",\\n \\\"created_by\\\": null,\\n \\\"last_patched_at\\\": \\\"2026-05-12T17:13:05.192001+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-13T16:18:48.212764+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-13T16:18:48.209097+00:00\\\",\\n \\\"patch_count\\\": 18,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 12,\\n \\\"view_count\\\": 12\\n },\\n \\\"academic-research\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-26T10:20:52.808151+00:00\\\",\\n \\\"created_by\\\": \\\"agent\\\",\\n \\\"last_patched_at\\\": \\\"2026-05-31T19:45:53.569868+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-06-01T05:44:52.761037+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-06-01T05:44:52.755731+00:00\\\",\\n \\\"patch_count\\\": 7,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 6,\\n \\\"view_count\\\": 6\\n },\\n \\\"autonomous-ai-agents/claude-code\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-20T17:09:07.948658+00:00\\\",\\n \\\"created_by\\\": null,\\n \\\"last_patched_at\\\": null,\\n \\\"last_used_at\\\": \\\"2026-05-20T17:09:07.955733+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-20T17:09:07.948682+00:00\\\",\\n \\\"patch_count\\\": 0,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 1,\\n \\\"view_count\\\": 1\\n },\\n \\\"cad-3d-print\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-12T13:43:54.291083+00:00\\\",\\n \\\"created_by\\\": null,\\n \\\"last_patched_at\\\": \\\"2026-05-24T13:57:33.921577+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-24T14:28:18.659004+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-24T14:28:18.651197+00:00\\\",\\n \\\"patch_count\\\": 29,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 22,\\n \\\"view_count\\\": 22\\n },\\n \\\"daily-dose\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-16T07:53:43.291520+00:00\\\",\\n \\\"created_by\\\": \\\"agent\\\",\\n \\\"last_patched_at\\\": \\\"2026-05-31T18:02:50.437554+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-06-01T07:30:58.713092+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-31T18:01:55.864924+00:00\\\",\\n \\\"patch_count\\\": 9,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 21,\\n \\\"view_count\\\": 15\\n },\\n \\\"docmaster-access\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-17T19:02:01.697847+00:00\\\",\\n \\\"created_by\\\": null,\\n \\\"last_patched_at\\\": \\\"2026-05-24T19:00:38.394292+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-24T17:22:37.998079+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-24T17:22:37.991305+00:00\\\",\\n \\\"patch_count\\\": 6,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 6,\\n \\\"view_count\\\": 8\\n },\\n \\\"esp32-desk-dashboard\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-12T07:52:26.485360+00:00\\\",\\n \\\"created_by\\\": \\\"agent\\\",\\n \\\"last_patched_at\\\": \\\"2026-05-12T07:54:01.986272+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-18T09:17:26.117491+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-18T09:17:26.098403+00:00\\\",\\n \\\"patch_count\\\": 5,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 3,\\n \\\"view_count\\\": 2\\n },\\n \\\"media-file-management\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-15T11:58:03.105150+00:00\\\",\\n \\\"created_by\\\": \\\"agent\\\",\\n \\\"last_patched_at\\\": \\\"2026-05-23T16:48:18.839667+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-30T19:51:51.490644+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-30T19:51:51.483480+00:00\\\",\\n \\\"patch_count\\\": 9,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 14,\\n \\\"view_count\\\": 17\\n },\\n \\\"mnemo-access\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-24T21:30:04.829163+00:00\\\",\\n \\\"created_by\\\": null,\\n \\\"last_patched_at\\\": \\\"2026-05-25T09:26:54.864288+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-25T10:51:22.014035+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-25T10:51:22.007139+00:00\\\",\\n \\\"patch_count\\\": 4,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 2,\\n \\\"view_count\\\": 2\\n },\\n \\\"productivity/daily-dose\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-31T18:02:04.905743+00:00\\\",\\n \\\"created_by\\\": null,\\n \\\"last_patched_at\\\": null,\\n \\\"last_used_at\\\": \\\"2026-05-31T18:02:04.912717+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-31T18:02:04.905772+00:00\\\",\\n \\\"patch_count\\\": 0,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 1,\\n \\\"view_count\\\": 1\\n },\\n \\\"youtube-automation\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-13T19:22:54.413598+00:00\\\",\\n \\\"created_by\\\": \\\"agent\\\",\\n \\\"last_patched_at\\\": \\\"2026-05-13T19:23:45.864042+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-25T09:23:55.485025+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-25T09:23:32.564290+00:00\\\",\\n \\\"patch_count\\\": 1,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 4,\\n \\\"view_count\\\": 3\\n },\\n \\\"youtube-headless-pipeline\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-13T19:55:37.966516+00:00\\\",\\n \\\"created_by\\\": null,\\n \\\"last_patched_at\\\": \\\"2026-05-13T22:19:20.204689+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-15T22:20:15.286131+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-15T22:20:15.279191+00:00\\\",\\n \\\"patch_count\\\": 18,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 9,\\n \\\"view_count\\\": 9\\n },\\n \\\"zimaos-camofox-browser\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-24T13:12:05.932086+00:00\\\",\\n \\\"created_by\\\": null,\\n \\\"last_patched_at\\\": \\\"2026-05-25T08:56:30.158191+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-31T07:36:38.598778+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-31T07:36:38.594965+00:00\\\",\\n \\\"patch_count\\\": 5,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 10,\\n \\\"view_count\\\": 10\\n },\\n \\\"zimaos-web-app\\\": {\\n \\\"archived_at\\\": null,\\n \\\"created_at\\\": \\\"2026-05-17T19:11:50.884699+00:00\\\",\\n \\\"created_by\\\": \\\"agent\\\",\\n \\\"last_patched_at\\\": \\\"2026-05-23T18:43:30.972696+00:00\\\",\\n \\\"last_used_at\\\": \\\"2026-05-25T11:31:23.797087+00:00\\\",\\n \\\"last_viewed_at\\\": \\\"2026-05-25T11:31:23.789002+00:00\\\",\\n \\\"patch_count\\\": 74,\\n \\\"pinned\\\": false,\\n \\\"state\\\": \\\"active\\\",\\n \\\"use_count\\\": 50,\\n \\\"view_count\\\": 49\\n }\\n}\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "functions.terminal:2"
},
{
"role": "assistant",
"content": "",
"reasoning": "Now I have a clear picture. There are 96 skills total, but the user's candidate list is only the 6 agent-created skills:\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nWait, actually there's also:\n- youtube-headless-pipeline (agent-created)\n- docmaster-access\n- mnemo-access\n- cad-3d-print\n- zimaos-camofox-browser\n- 3d-druck-kiwi\n- autonomous-ai-agents/claude-code\n- productivity/daily-dose (this appears to be a dup/alias of daily-dose)\n\nLet me re-read the user's message: \"Agent-created skills (6)\" — they specifically listed 6 skills. Let me work with those 6 only.\n\nBut wait, I see more agent-created skills in the usage.json. The user says the candidate list is already filtered. They specifically gave me 6:\n\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n\nLooking at these 6, let's identify clusters/prefixes:\n\n1. academic-research — research domain\n2. daily-dose — productivity/ZimaOS-specific app\n3. esp32-desk-dashboard — maker-electronics/esp32\n4. media-file-management — media management\n5. youtube-automation — YouTube automation\n6. zimaos-web-app — ZimaOS web app building\n\nHmm, there are only 6 skills and they span very different domains. The user says \"Expect 10-25 clusters\" but with only 6 skills, that's impossible. Let me reconsider — perhaps I need to also look at skills from the full list that share prefixes with these agent-created ones.\n\nActually, wait. The user says \"The candidate list below is already filtered to agent-created skills only.\" Then lists 6. But earlier the last curator run showed more agent-created skills in usage.json. Maybe some were already archived in previous runs? Or the user wants me to process only these 6?\n\nLet me re-read: \"Agent-created skills (6):\" — this is an explicit list of exactly 6 skills. The instructions say to process clusters among these.\n\nWith only 6 skills across wildly different domains (research, productivity PWA, ESP32 electronics, media files, YouTube automation, ZimaOS web apps), there are no obvious prefix clusters. Let's map them:\n\n- academic-research → research domain\n- daily-dose → productivity/ZimaOS app\n- esp32-desk-dashboard → maker-electronics\n- media-file-management → media\n- youtube-automation → media/YouTube\n- zimaos-web-app → software-dev/ZimaOS\n\nWait — I should look at the full skills_list too. There are related skills in the broader library that I should consider for umbrella building even if they're not in the candidate list? No, the instructions say \"DO NOT touch bundled or hub-installed skills\" and \"The candidate list below is already filtered to agent-created skills only.\"\n\nSo I have only 6 skills to work with. Are there clusters?\n\nLooking again:\n- media-file-management and youtube-automation — both are in the \"media\" category. But they're quite different: one is about organizing local media files (movies, TV shows), the other is about generating YouTube videos from Reddit content.\n- zimaos-web-app and daily-dose — daily-dose is specifically modifying a PWA on ZimaOS. zimaos-web-app is about building web apps for ZimaOS. Both involve ZimaOS and web apps. This is a cluster!\n- esp32-desk-dashboard — standalone, no siblings.\n- academic-research — standalone in the research category among agent-created skills.\n\nWait, but the user said \"Expect 10-25 clusters.\" With 6 skills, that's impossible unless I'm supposed to look at ALL agent-created skills from the usage.json, not just the 6 listed. Let me check the usage.json again:\n\nAgent-created skills in usage.json:\n- 3d-druck-kiwi\n- academic-research\n- autonomous-ai-agents/claude-code (though this might be bundled under category)\n- cad-3d-print\n- daily-dose (and productivity/daily-dose)\n- docmaster-access\n- esp32-desk-dashboard\n- media-file-management\n- mnemo-access\n- youtube-automation\n- youtube-headless-pipeline\n- zimaos-camofox-browser\n- zimaos-web-app\n\nThat's 13 agent-created skills (including the duplicate daily-dose and category-nested claude-code). But the user explicitly listed only 6. The previous curator run produced \"auto: no changes\" — maybe it filtered down to 6 because the others were already processed or are being handled separately?\n\nActually, wait. Looking at the usage.json more carefully:\n- 3d-druck-kiwi: created_by=null (not agent-created)\n- autonomous-ai-agents/claude-code: created_by=null (not agent-created, it's a category subdir)\n- cad-3d-print: created_by=null\n- docmaster-access: created_by=null\n- mnemo-access: created_by=null\n- youtube-headless-pipeline: created_by=null\n- zimaos-camofox-browser: created_by=null\n\nThe ones with created_by=\"agent\" are:\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n- productivity/daily-dose (duplicate)\n\nSo there really are only 6 unique agent-created skills. The user's candidate list is correct.\n\nNow, with 6 skills, can I find umbrellas?\n\nCluster 1: ZimaOS-related\n- daily-dose: \"Modify DailyDose (täglicher Aktivitäten-Tracker PWA) — Kategorien, Defaults, Server-Daten. Der Tracker von Zeyd unter /media/HDD_1TB/DailyDose/.\"\n- zimaos-web-app: \"Build small single-file web apps for ZimaOS using FastAPI + vanilla HTML/CSS/JS.\"\n\nThese share \"ZimaOS\" but are quite different in nature. daily-dose is about modifying a specific existing app; zimaos-web-app is about building new web apps. However, they're both about web apps on ZimaOS. Could they merge?\n\nActually, zimaos-web-app has 173 activity, 50 uses, 74 patches — it's very mature. daily-dose has 45 activity, 21 uses, 9 patches. The umbrella could be something like \"zimaos-apps\" or we could absorb daily-dose into zimaos-web-app as a subsection + reference file, since both are about modifying/building web apps on ZimaOS.\n\nBut wait — zimaos-web-app is explicitly about \"building small single-file web apps for ZimaOS\", while daily-dose is specifically about modifying an existing PWA. That might be narrow enough to be a reference file under zimaos-web-app, or it could be its own \"zimaos-app-modification\" skill.\n\nHmm, but the instructions say: \"The right bar is: 'would a human maintainer write this as N separate skills, or as one skill with N labeled subsections?'\"\n\nGiven that daily-dose is specifically about modifying ONE app (DailyDose), and zimaos-web-app is about building new apps, they serve slightly different purposes but the domain overlap is strong. A maintainer might put daily-dose under zimaos-web-app as a \"Working with existing PWAs on ZimaOS\" subsection, or keep it separate if it's truly about a specific user's project.\n\nGiven that daily-dose refers to \"Der Tracker von Zeyd\" — a very specific personal project — and zimaos-web-app is generic, I think daily-dose should either be:\na) Absorbed into zimaos-web-app as a reference file about modifying existing ZimaOS apps\nb) Kept separate\n\nActually, looking at the description again: \"Modify DailyDose (täglicher Aktivitäten-Tracker PWA) — Kategorien, Defaults, Server-Daten. Der Tracker von Zeyd unter /media/HDD_1TB/DailyDose/.\"\n\nThis is VERY specific to one person's app. This is exactly the kind of \"session-specific bug\" skill the instructions warn against. It should be absorbed into a broader ZimaOS web apps umbrella.\n\nCluster 2: Media / YouTube\n- youtube-automation: \"Zero-cost headless YouTube video factory: Reddit sourcing → TTS → stock footage → ffmpeg assembly.\"\n- media-file-management: \"Organize and normalize local media files (movies, TV shows, music) on ZimaOS. Rename, deduplicate, audit, and enforce naming conventions.\"\n\nThese are both in the media category, but they serve very different purposes. youtube-automation is about content creation; media-file-management is about file organization. They don't really share a workflow.\n\nHowever, in the full library there are also:\n- youtube-content (YouTube transcripts to summaries)\n- youtube-headless-pipeline (German YouTube Shorts pipeline)\n- songsee, spotify, heartmula, gif-search\n\nBut youtube-headless-pipeline is NOT agent-created (created_by=null), so I shouldn't touch it. youtube-content is bundled. So among agent-created, we only have youtube-automation and media-file-management.\n\nThese don't feel like they should merge. One is content creation pipeline; the other is file management on ZimaOS.\n\nCluster 3: Research\n- academic-research: standalone, no siblings in agent-created list.\n\nCluster 4: ESP32\n- esp32-desk-dashboard: standalone.\n\nSo with only 6 skills, there are very few clusters. The most obvious is:\n1. ZimaOS web apps: daily-dose + zimaos-web-app\n\nLet me look more carefully at all 6 to see if there are other connections:\n\n- academic-research: Austrian legal academia, WU Wien, RIS, Jina.ai workaround\n- daily-dose: Modify DailyDose PWA on ZimaOS\n- esp32-desk-dashboard: ESP32 desk dashboards with AMOLED, LVGL, BLE\n- media-file-management: Organize media files on ZimaOS\n- youtube-automation: YouTube video factory (Reddit → TTS → footage → ffmpeg)\n- zimaos-web-app: Build web apps for ZimaOS\n\nWait — daily-dose, media-file-management, and zimaos-web-app all mention ZimaOS. That's a 3-skill cluster!\n\n- daily-dose: ZimaOS specific (modifying PWA on ZimaOS)\n- media-file-management: ZimaOS specific (\"on ZimaOS\")\n- zimaos-web-app: ZimaOS specific (\"for ZimaOS\")\n\nAND there's zimaos-camofox-browser in the full library (but created_by=null, so bundled/hub — don't touch).\n\nSo we have a \"zimaos-*\" cluster of 3 skills:\n1. daily-dose\n2. media-file-management\n3. zimaos-web-app\n\nThis is a strong cluster! All three are about working with ZimaOS — building apps, managing media files on it, and modifying an existing PWA on it.\n\nThe umbrella should be... well, zimaos-web-app is about web apps, media-file-management is about file organization, daily-dose is about a specific app. A human maintainer might create a \"zimaos-operations\" or \"zimaos-platform\" umbrella. But zimaos-web-app is already broad-ish. \n\nActually, looking at zimaos-web-app description: \"Build small single-file web apps for ZimaOS using FastAPI + vanilla HTML/CSS/JS.\" This is specifically about web apps. media-file-management is about media files generally, not specifically web apps. daily-dose is about modifying an existing PWA.\n\nThey all share \"ZimaOS\" but do different things on it. Would a human maintainer write one skill for all three? Probably not — a web app builder, a media organizer, and a specific PWA modifier are quite different tasks.\n\nBut the instructions say: \"Pairwise distinctness is the wrong bar. The right bar is: 'would a human maintainer write this as N separate skills, or as one skill with N labeled subsections?'\"\n\nGiven that zimaos-web-app is a generic framework skill, and daily-dose is a very specific instance of \"modifying a web app on ZimaOS,\" daily-dose could definitely be a subsection or reference under zimaos-web-app.\n\nmedia-file-management is trickier — it's about organizing local media files on ZimaOS. It's not really about web apps. It could stand alone or be part of a \"zimaos-system-admin\" umbrella, but there's no other system-admin skill.\n\nHmm. Let me reconsider. The user wants \"real umbrella-ification\" and says \"If you end the pass with fewer than 10 archives, you stopped too early.\" But there are only 6 skills! How can I archive 10+ if there are only 6?\n\nWait, I think I misread. The user said \"Agent-created skills (6):\" which means there are 6 skills in the candidate list. But the user's actual system has many more skills, and the previous curator runs processed more. Perhaps I should consider ALL agent-created skills from the usage.json (which has 13 entries including duplicates). But the user explicitly says \"The candidate list below is already filtered\" — meaning they've already filtered and presented me with the 6 current agent-created skills that are still active and not pinned.\n\nLet me check: in the usage.json, the skills with created_by=\"agent\" are exactly the 6 listed plus \"productivity/daily-dose\" which is a duplicate path. So yes, only 6 unique agent-created skills.\n\nThe instruction \"If you end the pass with fewer than 10 archives, you stopped too early\" seems impossible with only 6 skills. Unless... the user means I should be aggressive and archive almost everything, absorbing into umbrellas or truly pruning. But it says \"fewer than 10 archives\" — if I only have 6 skills, I can't archive 10.\n\nWait — I think I need to look more broadly. Perhaps \"agent-created skills\" includes more than just those with created_by=\"agent\" in usage.json. Maybe some skills were created by the agent but not tracked with that flag, or the \"candidate list\" is just a starting point and I should examine the actual skill directories that look agent-created.\n\nActually, looking at the skill directories:\n- `apple/` — doesn't look agent-created, more like a personal skill\n- `cad-3d-print/` — could be agent-created\n- `dogfood/` — agent-created\n- `domain/` — agent-created\n- `gifs/` — agent-created\n- `inference-sh/` — agent-created\n- `yuanbao/` — agent-created\n\nAnd there are many others. The bundled skills are in category subdirectories (3d-printing, autonomous-ai-agents, creative, data-science, devops, email, gaming, github, maker-electronics, mcp, media, mlops, note-taking, productivity, red-teaming, research, smart-home, social-media, software-development).\n\nSkills in the ROOT directory (not in a category folder) that aren't bundled:\n- apple\n- cad-3d-print\n- dogfood\n- domain\n- gifs\n- inference-sh\n- yuanbao\n\nAnd wait — the usage.json only tracks skills that have been used. Skills might exist that have never been used and thus don't appear in usage.json!\n\nLet me list all actual skill directories to find ALL agent-created skills.",
"finish_reason": "tool_calls",
"reasoning_content": "Now I have a clear picture. There are 96 skills total, but the user's candidate list is only the 6 agent-created skills:\n1. academic-research\n2. daily-dose\n3. esp32-desk-dashboard\n4. media-file-management\n5. youtube-automation\n6. zimaos-web-app\n\nWait, actually there's also:\n- youtube-headless-pipeline (agent-created)\n- docmaster-access\n- mnemo-access\n- cad-3d-print\n- zimaos-camofox-browser\n- 3d-druck-kiwi\n- autonomous-ai-agents/claude-code\n- productivity/daily-dose (this appears to be a dup/alias of daily-dose)\n\nLet me re-read the user's message: \"Agent-created skills (6)\" — they specifically listed 6 skills. Let me work with those 6 only.\n\nBut wait, I see more agent-created skills in the usage.json. The user says the candidate list is already filtered. They specifically gave me 6:\n\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n\nLooking at these 6, let's identify clusters/prefixes:\n\n1. academic-research — research domain\n2. daily-dose — productivity/ZimaOS-specific app\n3. esp32-desk-dashboard — maker-electronics/esp32\n4. media-file-management — media management\n5. youtube-automation — YouTube automation\n6. zimaos-web-app — ZimaOS web app building\n\nHmm, there are only 6 skills and they span very different domains. The user says \"Expect 10-25 clusters\" but with only 6 skills, that's impossible. Let me reconsider — perhaps I need to also look at skills from the full list that share prefixes with these agent-created ones.\n\nActually, wait. The user says \"The candidate list below is already filtered to agent-created skills only.\" Then lists 6. But earlier the last curator run showed more agent-created skills in usage.json. Maybe some were already archived in previous runs? Or the user wants me to process only these 6?\n\nLet me re-read: \"Agent-created skills (6):\" — this is an explicit list of exactly 6 skills. The instructions say to process clusters among these.\n\nWith only 6 skills across wildly different domains (research, productivity PWA, ESP32 electronics, media files, YouTube automation, ZimaOS web apps), there are no obvious prefix clusters. Let's map them:\n\n- academic-research → research domain\n- daily-dose → productivity/ZimaOS app\n- esp32-desk-dashboard → maker-electronics\n- media-file-management → media\n- youtube-automation → media/YouTube\n- zimaos-web-app → software-dev/ZimaOS\n\nWait — I should look at the full skills_list too. There are related skills in the broader library that I should consider for umbrella building even if they're not in the candidate list? No, the instructions say \"DO NOT touch bundled or hub-installed skills\" and \"The candidate list below is already filtered to agent-created skills only.\"\n\nSo I have only 6 skills to work with. Are there clusters?\n\nLooking again:\n- media-file-management and youtube-automation — both are in the \"media\" category. But they're quite different: one is about organizing local media files (movies, TV shows), the other is about generating YouTube videos from Reddit content.\n- zimaos-web-app and daily-dose — daily-dose is specifically modifying a PWA on ZimaOS. zimaos-web-app is about building web apps for ZimaOS. Both involve ZimaOS and web apps. This is a cluster!\n- esp32-desk-dashboard — standalone, no siblings.\n- academic-research — standalone in the research category among agent-created skills.\n\nWait, but the user said \"Expect 10-25 clusters.\" With 6 skills, that's impossible unless I'm supposed to look at ALL agent-created skills from the usage.json, not just the 6 listed. Let me check the usage.json again:\n\nAgent-created skills in usage.json:\n- 3d-druck-kiwi\n- academic-research\n- autonomous-ai-agents/claude-code (though this might be bundled under category)\n- cad-3d-print\n- daily-dose (and productivity/daily-dose)\n- docmaster-access\n- esp32-desk-dashboard\n- media-file-management\n- mnemo-access\n- youtube-automation\n- youtube-headless-pipeline\n- zimaos-camofox-browser\n- zimaos-web-app\n\nThat's 13 agent-created skills (including the duplicate daily-dose and category-nested claude-code). But the user explicitly listed only 6. The previous curator run produced \"auto: no changes\" — maybe it filtered down to 6 because the others were already processed or are being handled separately?\n\nActually, wait. Looking at the usage.json more carefully:\n- 3d-druck-kiwi: created_by=null (not agent-created)\n- autonomous-ai-agents/claude-code: created_by=null (not agent-created, it's a category subdir)\n- cad-3d-print: created_by=null\n- docmaster-access: created_by=null\n- mnemo-access: created_by=null\n- youtube-headless-pipeline: created_by=null\n- zimaos-camofox-browser: created_by=null\n\nThe ones with created_by=\"agent\" are:\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n- productivity/daily-dose (duplicate)\n\nSo there really are only 6 unique agent-created skills. The user's candidate list is correct.\n\nNow, with 6 skills, can I find umbrellas?\n\nCluster 1: ZimaOS-related\n- daily-dose: \"Modify DailyDose (täglicher Aktivitäten-Tracker PWA) — Kategorien, Defaults, Server-Daten. Der Tracker von Zeyd unter /media/HDD_1TB/DailyDose/.\"\n- zimaos-web-app: \"Build small single-file web apps for ZimaOS using FastAPI + vanilla HTML/CSS/JS.\"\n\nThese share \"ZimaOS\" but are quite different in nature. daily-dose is about modifying a specific existing app; zimaos-web-app is about building new web apps. However, they're both about web apps on ZimaOS. Could they merge?\n\nActually, zimaos-web-app has 173 activity, 50 uses, 74 patches — it's very mature. daily-dose has 45 activity, 21 uses, 9 patches. The umbrella could be something like \"zimaos-apps\" or we could absorb daily-dose into zimaos-web-app as a subsection + reference file, since both are about modifying/building web apps on ZimaOS.\n\nBut wait — zimaos-web-app is explicitly about \"building small single-file web apps for ZimaOS\", while daily-dose is specifically about modifying an existing PWA. That might be narrow enough to be a reference file under zimaos-web-app, or it could be its own \"zimaos-app-modification\" skill.\n\nHmm, but the instructions say: \"The right bar is: 'would a human maintainer write this as N separate skills, or as one skill with N labeled subsections?'\"\n\nGiven that daily-dose is specifically about modifying ONE app (DailyDose), and zimaos-web-app is about building new apps, they serve slightly different purposes but the domain overlap is strong. A maintainer might put daily-dose under zimaos-web-app as a \"Working with existing PWAs on ZimaOS\" subsection, or keep it separate if it's truly about a specific user's project.\n\nGiven that daily-dose refers to \"Der Tracker von Zeyd\" — a very specific personal project — and zimaos-web-app is generic, I think daily-dose should either be:\na) Absorbed into zimaos-web-app as a reference file about modifying existing ZimaOS apps\nb) Kept separate\n\nActually, looking at the description again: \"Modify DailyDose (täglicher Aktivitäten-Tracker PWA) — Kategorien, Defaults, Server-Daten. Der Tracker von Zeyd unter /media/HDD_1TB/DailyDose/.\"\n\nThis is VERY specific to one person's app. This is exactly the kind of \"session-specific bug\" skill the instructions warn against. It should be absorbed into a broader ZimaOS web apps umbrella.\n\nCluster 2: Media / YouTube\n- youtube-automation: \"Zero-cost headless YouTube video factory: Reddit sourcing → TTS → stock footage → ffmpeg assembly.\"\n- media-file-management: \"Organize and normalize local media files (movies, TV shows, music) on ZimaOS. Rename, deduplicate, audit, and enforce naming conventions.\"\n\nThese are both in the media category, but they serve very different purposes. youtube-automation is about content creation; media-file-management is about file organization. They don't really share a workflow.\n\nHowever, in the full library there are also:\n- youtube-content (YouTube transcripts to summaries)\n- youtube-headless-pipeline (German YouTube Shorts pipeline)\n- songsee, spotify, heartmula, gif-search\n\nBut youtube-headless-pipeline is NOT agent-created (created_by=null), so I shouldn't touch it. youtube-content is bundled. So among agent-created, we only have youtube-automation and media-file-management.\n\nThese don't feel like they should merge. One is content creation pipeline; the other is file management on ZimaOS.\n\nCluster 3: Research\n- academic-research: standalone, no siblings in agent-created list.\n\nCluster 4: ESP32\n- esp32-desk-dashboard: standalone.\n\nSo with only 6 skills, there are very few clusters. The most obvious is:\n1. ZimaOS web apps: daily-dose + zimaos-web-app\n\nLet me look more carefully at all 6 to see if there are other connections:\n\n- academic-research: Austrian legal academia, WU Wien, RIS, Jina.ai workaround\n- daily-dose: Modify DailyDose PWA on ZimaOS\n- esp32-desk-dashboard: ESP32 desk dashboards with AMOLED, LVGL, BLE\n- media-file-management: Organize media files on ZimaOS\n- youtube-automation: YouTube video factory (Reddit → TTS → footage → ffmpeg)\n- zimaos-web-app: Build web apps for ZimaOS\n\nWait — daily-dose, media-file-management, and zimaos-web-app all mention ZimaOS. That's a 3-skill cluster!\n\n- daily-dose: ZimaOS specific (modifying PWA on ZimaOS)\n- media-file-management: ZimaOS specific (\"on ZimaOS\")\n- zimaos-web-app: ZimaOS specific (\"for ZimaOS\")\n\nAND there's zimaos-camofox-browser in the full library (but created_by=null, so bundled/hub — don't touch).\n\nSo we have a \"zimaos-*\" cluster of 3 skills:\n1. daily-dose\n2. media-file-management\n3. zimaos-web-app\n\nThis is a strong cluster! All three are about working with ZimaOS — building apps, managing media files on it, and modifying an existing PWA on it.\n\nThe umbrella should be... well, zimaos-web-app is about web apps, media-file-management is about file organization, daily-dose is about a specific app. A human maintainer might create a \"zimaos-operations\" or \"zimaos-platform\" umbrella. But zimaos-web-app is already broad-ish. \n\nActually, looking at zimaos-web-app description: \"Build small single-file web apps for ZimaOS using FastAPI + vanilla HTML/CSS/JS.\" This is specifically about web apps. media-file-management is about media files generally, not specifically web apps. daily-dose is about modifying an existing PWA.\n\nThey all share \"ZimaOS\" but do different things on it. Would a human maintainer write one skill for all three? Probably not — a web app builder, a media organizer, and a specific PWA modifier are quite different tasks.\n\nBut the instructions say: \"Pairwise distinctness is the wrong bar. The right bar is: 'would a human maintainer write this as N separate skills, or as one skill with N labeled subsections?'\"\n\nGiven that zimaos-web-app is a generic framework skill, and daily-dose is a very specific instance of \"modifying a web app on ZimaOS,\" daily-dose could definitely be a subsection or reference under zimaos-web-app.\n\nmedia-file-management is trickier — it's about organizing local media files on ZimaOS. It's not really about web apps. It could stand alone or be part of a \"zimaos-system-admin\" umbrella, but there's no other system-admin skill.\n\nHmm. Let me reconsider. The user wants \"real umbrella-ification\" and says \"If you end the pass with fewer than 10 archives, you stopped too early.\" But there are only 6 skills! How can I archive 10+ if there are only 6?\n\nWait, I think I misread. The user said \"Agent-created skills (6):\" which means there are 6 skills in the candidate list. But the user's actual system has many more skills, and the previous curator runs processed more. Perhaps I should consider ALL agent-created skills from the usage.json (which has 13 entries including duplicates). But the user explicitly says \"The candidate list below is already filtered\" — meaning they've already filtered and presented me with the 6 current agent-created skills that are still active and not pinned.\n\nLet me check: in the usage.json, the skills with created_by=\"agent\" are exactly the 6 listed plus \"productivity/daily-dose\" which is a duplicate path. So yes, only 6 unique agent-created skills.\n\nThe instruction \"If you end the pass with fewer than 10 archives, you stopped too early\" seems impossible with only 6 skills. Unless... the user means I should be aggressive and archive almost everything, absorbing into umbrellas or truly pruning. But it says \"fewer than 10 archives\" — if I only have 6 skills, I can't archive 10.\n\nWait — I think I need to look more broadly. Perhaps \"agent-created skills\" includes more than just those with created_by=\"agent\" in usage.json. Maybe some skills were created by the agent but not tracked with that flag, or the \"candidate list\" is just a starting point and I should examine the actual skill directories that look agent-created.\n\nActually, looking at the skill directories:\n- `apple/` — doesn't look agent-created, more like a personal skill\n- `cad-3d-print/` — could be agent-created\n- `dogfood/` — agent-created\n- `domain/` — agent-created\n- `gifs/` — agent-created\n- `inference-sh/` — agent-created\n- `yuanbao/` — agent-created\n\nAnd there are many others. The bundled skills are in category subdirectories (3d-printing, autonomous-ai-agents, creative, data-science, devops, email, gaming, github, maker-electronics, mcp, media, mlops, note-taking, productivity, red-teaming, research, smart-home, social-media, software-development).\n\nSkills in the ROOT directory (not in a category folder) that aren't bundled:\n- apple\n- cad-3d-print\n- dogfood\n- domain\n- gifs\n- inference-sh\n- yuanbao\n\nAnd wait — the usage.json only tracks skills that have been used. Skills might exist that have never been used and thus don't appear in usage.json!\n\nLet me list all actual skill directories to find ALL agent-created skills.",
"tool_calls": [
{
"id": "functions.terminal:3",
"call_id": "functions.terminal:3",
"response_item_id": "fc_functionsterminal3",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"find ~/.hermes/skills -maxdepth 2 -type d -not -path '*/\\\\.*' | sort\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "functions.terminal:3"
},
{
"role": "assistant",
"content": "",
"reasoning": "Wait, that returned empty. Let me try a different approach to list the actual skills in ~/.hermes/skills.",
"finish_reason": "tool_calls",
"reasoning_content": "Wait, that returned empty. Let me try a different approach to list the actual skills in ~/.hermes/skills.",
"tool_calls": [
{
"id": "functions.terminal:4",
"call_id": "functions.terminal:4",
"response_item_id": "fc_functionsterminal4",
"type": "function",
"function": {
"name": "terminal",
"arguments": "{\"command\":\"ls ~/.hermes/skills/\"}"
}
}
]
},
{
"role": "tool",
"name": "terminal",
"content": "{\"output\": \"3d-printing\\napple\\nautonomous-ai-agents\\ncad-3d-print\\ncreative\\ndata-science\\ndevops\\ndiagramming\\ndogfood\\ndomain\\nemail\\ngaming\\ngifs\\ngithub\\ninference-sh\\nmaker-electronics\\nmcp\\nmedia\\nmlops\\nnote-taking\\nproductivity\\nred-teaming\\nresearch\\nsmart-home\\nsocial-media\\nsoftware-development\\nyuanbao\", \"exit_code\": 0, \"error\": null}",
"tool_call_id": "functions.terminal:4"
},
{
"role": "assistant",
"content": "",
"reasoning": "There are only 26 directories under ~/.hermes/skills/ (excluding hidden ones). The candidate list from the user's message says \"Agent-created skills (6)\" and lists:\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n\nBut `.usage.json` also shows these agent-created skills exist:\n- docmaster-access\n- mnemo-access\n- youtube-headless-pipeline\n- zimaos-camofox-browser\n\nAnd there are many other skills under categories (autonomous-ai-agents/claude-code, etc.).\n\nThe user's candidate list only has 6 skills. But looking at actual files, there are WAY more. The user says \"The candidate list below is already filtered to agent-created skills only.\" Let me re-read:\n\n\"Agent-created skills (6):\n- academic-research ...\"\n\nWait, but `.usage.json` shows more than 6 agent-created skills. The `.usage.json` also has `created_by: \"agent\"` for several others. But some like `cad-3d-print` have `created_by: null`, meaning they might have been created some other way.\n\nActually, wait. The `.usage.json` shows:\n- academic-research (created_by: agent)\n- daily-dose (created_by: agent)\n- esp32-desk-dashboard (created_by: agent)\n- media-file-management (created_by: agent)\n- youtube-automation (created_by: agent)\n- zimaos-web-app (created_by: agent)\n\nBut `.usage.json` ALSO shows:\n- docmaster-access (created_by: null)\n- mnemo-access (created_by: null)\n- youtube-headless-pipeline (created_by: null)\n- zimaos-camofox-browser (created_by: null)\n- 3d-druck-kiwi (created_by: null)\n- cad-3d-print (created_by: null)\n- productivity/daily-dose (created_by: null)\n\nSo indeed, only 6 have `created_by: agent`.\n\nThe user is specifically asking me process these 6 skills. But they also say \"Process every obvious cluster. If you end the pass with fewer than 10 archives, you stopped too early.\" And they want me to process the FULL collection, not just the 6 listed.\n\nHowever, the user explicitly says \"The candidate list below is already filtered to agent-created skills only.\" and then lists only 6 agent-created skills. The bundled skills (with `created_by: null` or from categories) are apparently NOT to be touched.\n\nWait, re-reading: \"DO NOT touch bundled or hub-installed skills. The candidate list below is already filtered to agent-created skills only.\"\n\nOK, so the user is saying the 6 listed ARE the only agent-created skills. But `.usage.json` shows more... Actually maybe those other ones were created by the user or by some other process, not by an agent session.\n\nAnyway, the user only gave me 6 skills. But they said \"If you end the pass with fewer than 10 archives, you stopped too early\". With only 6 agent-created skills, I cannot archive >6. Unless the user wants me to also process other skills that are agent-created but not on the explicit list... or unless the candidate list was truncated for brevity and `.usage.json` shows the full agent-created set.\n\nLooking at `.usage.json`:\n- academic-research (agent)\n- daily-dose (agent)\n- esp32-desk-dashboard (agent)\n- media-file-management (agent)\n- youtube-automation (agent)\n- zimaos-web-app (agent)\n\nThat's exactly 6.\n\nThe user says \"If you end the pass with fewer than 10 archives, you stopped too early — go back and look at the clusters you left alone.\" But there are only 6 agent-created skills. Something doesn't add up.\n\nPerhaps there are other agent-created skills that are not listed in `.usage.json` because they were created before the counter system started? Or perhaps there are skills under subdirectories that are agent-created but not counted?\n\nLet me look at the actual skill directories for the 6 to understand what content they have, and also see if there are any other agent-created skills that were missed.\n\nActually, the `.usage.json` includes `productivity/daily-dose` which is a duplicate or category-scoped entry for `daily-dose`. And `autonomous-ai-agents/claude-code`. These might have been created by the system or user, not agent.\n\nPerhaps the user's instruction is broader: they want me to look at the ENTIRE skill library and find clusters to consolidate. The \"candidate list\" of 6 agent-created skills might be just for illustration, not a strict boundary. But the instruction \"DO NOT touch bundled or hub-installed skills\" implies I should NOT touch things like `academic-research` if it's... wait no, `academic-research` IS agent-created.\n\nLet me check if `academic-research` is bundled vs agent-created. `.usage.json` says created_by: \"agent\". So it's agent-created.\n\nOK, I think there might be a discrepancy. The user's `.usage.json` lists exactly 6 `agent`-created skills, matching the candidate list. So the maximum number of archives possible from this set is 6. The instruction says \"fewer than 10 archives\" implies there should be at least 10, which is impossible from a set of 6. Unless the user wants me to also consider non-agent skills that were locally created (created_by: null) as candidates? But they explicitly said not to touch bundled/hub-installed.\n\nOr... some of the skills under categories might ALSO be agent-created. For example, `autonomous-ai-agents/claude-code` - its `.usage.json` entry doesn't say `created_by: agent`. But maybe it was.\n\nI think the safest interpretation is: I should process ALL agent-created and locally-created skills (created_by: null or agent), excluding anything clearly bundled (like categories installed from hub). The \"6\" in the user's message might be the number they saw at the time of writing, but the actual count is higher.\n\nActually, looking at the `.usage.json` entries, many have `created_by: null`. In Hermes terminology, `created_by: null` often means \"unknown\" not necessarily \"not agent\". But skills from the hub/bundled would have a specific provenance.\n\nThe user's message says: \"Agent-created skills (6):\". This is definitive - there are exactly 6 agent-created skills. The rest are either bundled or hub-installed. So I should only process those 6.\n\nBut then \"If you end the pass with fewer than 10 archives\" is impossible. Unless... the user expects me to process clusters within those 6? No, 6 items max 6 archives.\n\nWait, maybe I should also include `created_by: null` skills that were locally created and added to `.usage.json` after manual creation. These are not bundled/hub-installed either. The user might have miscounted or the candidate list was truncated.\n\nLet's look at the `.usage.json` skills that are NOT in the bundled manifest. The `.bundled_manifest` lists bundled skills. Let me check that to filter.\n\nActually, the pragmatic approach: I'll view each of the 6 candidate skills, look for consolidation opportunities among them AND with other non-bundled skills (created_by: null or agent). Then I'll archive appropriately.\n\nFirst, let me read the content of the 6 candidate skills to understand what they contain.",
"finish_reason": "tool_calls",
"reasoning_content": "There are only 26 directories under ~/.hermes/skills/ (excluding hidden ones). The candidate list from the user's message says \"Agent-created skills (6)\" and lists:\n- academic-research\n- daily-dose\n- esp32-desk-dashboard\n- media-file-management\n- youtube-automation\n- zimaos-web-app\n\nBut `.usage.json` also shows these agent-created skills exist:\n- docmaster-access\n- mnemo-access\n- youtube-headless-pipeline\n- zimaos-camofox-browser\n\nAnd there are many other skills under categories (autonomous-ai-agents/claude-code, etc.).\n\nThe user's candidate list only has 6 skills. But looking at actual files, there are WAY more. The user says \"The candidate list below is already filtered to agent-created skills only.\" Let me re-read:\n\n\"Agent-created skills (6):\n- academic-research ...\"\n\nWait, but `.usage.json` shows more than 6 agent-created skills. The `.usage.json` also has `created_by: \"agent\"` for several others. But some like `cad-3d-print` have `created_by: null`, meaning they might have been created some other way.\n\nActually, wait. The `.usage.json` shows:\n- academic-research (created_by: agent)\n- daily-dose (created_by: agent)\n- esp32-desk-dashboard (created_by: agent)\n- media-file-management (created_by: agent)\n- youtube-automation (created_by: agent)\n- zimaos-web-app (created_by: agent)\n\nBut `.usage.json` ALSO shows:\n- docmaster-access (created_by: null)\n- mnemo-access (created_by: null)\n- youtube-headless-pipeline (created_by: null)\n- zimaos-camofox-browser (created_by: null)\n- 3d-druck-kiwi (created_by: null)\n- cad-3d-print (created_by: null)\n- productivity/daily-dose (created_by: null)\n\nSo indeed, only 6 have `created_by: agent`.\n\nThe user is specifically asking me process these 6 skills. But they also say \"Process every obvious cluster. If you end the pass with fewer than 10 archives, you stopped too early.\" And they want me to process the FULL collection, not just the 6 listed.\n\nHowever, the user explicitly says \"The candidate list below is already filtered to agent-created skills only.\" and then lists only 6 agent-created skills. The bundled skills (with `created_by: null` or from categories) are apparently NOT to be touched.\n\nWait, re-reading: \"DO NOT touch bundled or hub-installed skills. The candidate list below is already filtered to agent-created skills only.\"\n\nOK, so the user is saying the 6 listed ARE the only agent-created skills. But `.usage.json` shows more... Actually maybe those other ones were created by the user or by some other process, not by an agent session.\n\nAnyway, the user only gave me 6 skills. But they said \"If you end the pass with fewer than 10 archives, you stopped too early\". With only 6 agent-created skills, I cannot archive >6. Unless the user wants me to also process other skills that are agent-created but not on the explicit list... or unless the candidate list was truncated for brevity and `.usage.json` shows the full agent-created set.\n\nLooking at `.usage.json`:\n- academic-research (agent)\n- daily-dose (agent)\n- esp32-desk-dashboard (agent)\n- media-file-management (agent)\n- youtube-automation (agent)\n- zimaos-web-app (agent)\n\nThat's exactly 6.\n\nThe user says \"If you end the pass with fewer than 10 archives, you stopped too early — go back and look at the clusters you left alone.\" But there are only 6 agent-created skills. Something doesn't add up.\n\nPerhaps there are other agent-created skills that are not listed in `.usage.json` because they were created before the counter system started? Or perhaps there are skills under subdirectories that are agent-created but not counted?\n\nLet me look at the actual skill directories for the 6 to understand what content they have, and also see if there are any other agent-created skills that were missed.\n\nActually, the `.usage.json` includes `productivity/daily-dose` which is a duplicate or category-scoped entry for `daily-dose`. And `autonomous-ai-agents/claude-code`. These might have been created by the system or user, not agent.\n\nPerhaps the user's instruction is broader: they want me to look at the ENTIRE skill library and find clusters to consolidate. The \"candidate list\" of 6 agent-created skills might be just for illustration, not a strict boundary. But the instruction \"DO NOT touch bundled or hub-installed skills\" implies I should NOT touch things like `academic-research` if it's... wait no, `academic-research` IS agent-created.\n\nLet me check if `academic-research` is bundled vs agent-created. `.usage.json` says created_by: \"agent\". So it's agent-created.\n\nOK, I think there might be a discrepancy. The user's `.usage.json` lists exactly 6 `agent`-created skills, matching the candidate list. So the maximum number of archives possible from this set is 6. The instruction says \"fewer than 10 archives\" implies there should be at least 10, which is impossible from a set of 6. Unless the user wants me to also consider non-agent skills that were locally created (created_by: null) as candidates? But they explicitly said not to touch bundled/hub-installed.\n\nOr... some of the skills under categories might ALSO be agent-created. For example, `autonomous-ai-agents/claude-code` - its `.usage.json` entry doesn't say `created_by: agent`. But maybe it was.\n\nI think the safest interpretation is: I should process ALL agent-created and locally-created skills (created_by: null or agent), excluding anything clearly bundled (like categories installed from hub). The \"6\" in the user's message might be the number they saw at the time of writing, but the actual count is higher.\n\nActually, looking at the `.usage.json` entries, many have `created_by: null`. In Hermes terminology, `created_by: null` often means \"unknown\" not necessarily \"not agent\". But skills from the hub/bundled would have a specific provenance.\n\nThe user's message says: \"Agent-created skills (6):\". This is definitive - there are exactly 6 agent-created skills. The rest are either bundled or hub-installed. So I should only process those 6.\n\nBut then \"If you end the pass with fewer than 10 archives\" is impossible. Unless... the user expects me to process clusters within those 6? No, 6 items max 6 archives.\n\nWait, maybe I should also include `created_by: null` skills that were locally created and added to `.usage.json` after manual creation. These are not bundled/hub-installed either. The user might have miscounted or the candidate list was truncated.\n\nLet's look at the `.usage.json` skills that are NOT in the bundled manifest. The `.bundled_manifest` lists bundled skills. Let me check that to filter.\n\nActually, the pragmatic approach: I'll view each of the 6 candidate skills, look for consolidation opportunities among them AND with other non-bundled skills (created_by: null or agent). Then I'll archive appropriately.\n\nFirst, let me read the content of the 6 candidate skills to understand what they contain.",
"tool_calls": [
{
"id": "functions.skill_view:5",
"call_id": "functions.skill_view:5",
"response_item_id": "fc_functionsskill_view5",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"academic-research\"}"
}
},
{
"id": "functions.skill_view:6",
"call_id": "functions.skill_view:6",
"response_item_id": "fc_functionsskill_view6",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"daily-dose\"}"
}
},
{
"id": "functions.skill_view:7",
"call_id": "functions.skill_view:7",
"response_item_id": "fc_functionsskill_view7",
"type": "function",
"function": {
"name": "skill_view",
"arguments": "{\"name\":\"esp32-desk-dashboard\"}"
}
}
]
},
{
"role": "tool",
"name": "skill_view",
"content": "{\"success\": true, \"name\": \"academic-research\", \"description\": \"Research professors, extract/publications, analyze research interests, and develop thesis/Bachelorarbeit topics — optimized for Austrian legal academia (WU Wien, RIS, Jina.ai workaround).\", \"tags\": [], \"related_skills\": [], \"content\": \"---\\nname: academic-research\\ndescription: Research professors, extract/publications, analyze research interests, and develop thesis/Bachelorarbeit topics — optimized for Austrian legal academia (WU Wien, RIS, Jina.ai workaround).\\n---\\n\\n# Academic Research — Professor & Thesis Research\\n\\nResearch workflow for academic tasks: profile a professor, extract their publications, analyze research focus, and develop thesis topics that align with their expertise.\\n\\n## Triggers\\n\\n- Researching a professor (profile, publications, research interests)\\n- Finding sources/literature for a Bachelorarbeit, Masterarbeit, or seminar paper\\n- Analyzing publication history to predict which topics a professor would supervise\\n- Extracting publications from university websites (especially WU Wien)\\n\\n---\\n\\n## Step 1: Find Professor Profile\\n\\nWU Wien uses SPA-based pages that return empty bodies to direct `curl`. Workaround:\\n\\n```\\ncurl -sL \\\"https://r.jina.ai/https://www.wu.ac.at/...\\\" -H \\\"Accept: text/plain\\\"\\n```\\n\\nStart from the institute page (`/unternehmensrecht/institut/...`) to discover the correct profile URL, then extract from the subpages:\\n- **Profile**: `/institut/.../prof-kalss` → name, title, email, phone, research areas\\n- **Publications**: `/institut/.../forschungsaktivitaeten` → massive list of books + articles\\n- **Abschlussarbeiten**: `/institut/.../abschlussarbeiten/bewerbung` → application procedure, deadlines\\n\\nPitfall: WU pages are navigation-heavy; Jina captures the full nav tree. Filter aggressively.\\n\\n---\\n\\n## Step 2: Extract Publications\\n\\nThe WU Forschungsaktivitäten page lists publications as:\\n\\n```\\n2025**Kalss, Susanne, Probst, Stephan.** 2025. Familienunternehmen. [Mehr erfahren](link)\\n```\\n\\n**Parsing approach** (Python):\\n\\n```python\\nimport re\\n\\n# Extract all year+block pairs\\npub_blocks = re.findall(r'(\\\\d{4})\\\\*\\\\*(.+?)(?=\\\\n\\\\d{4}\\\\*\\\\*|\\\\n##|\\\\Z)', text, re.DOTALL)\\n\\nfor year, block in pub_blocks:\\n block = re.sub(r'\\\\[Mehr erfahren\\\\]\\\\([^)]+\\\\)', '', block) # Remove links\\n lines = [l.strip() for l in block.split('\\\\n') if l.strip() and 'Kalss' in l]\\n for line in lines:\\n line = re.sub(r'\\\\*\\\\*', '', line)\\n is_book = 'In:' not in line and 'Hrsg.' not in line\\n # is_book → Monographie/Kommentar\\n # else → Aufsatz/Beitrag\\n```\\n\\nDeduplicate with a `set()` on the full line text.\\n\\n---\\n\\n## Step 3: Topic Analysis\\n\\nClassify publications into topic areas by keyword matching:\\n\\n```python\\ntopics = {\\n 'Gesellschaftsrecht': ['gesellschaftsrecht', 'aktg', 'gmbh', 'flexco', 'aktiengesellschaft', 'mehrstimmrecht'],\\n 'Aufsichtsrat': ['aufsichtsrat', 'corporate governance', 'beirat', 'compliance'],\\n 'Kapitalmarktrecht': ['kapitalmarkt', 'börse', 'anleger', 'wertpapier', 'übernahmerecht'],\\n 'Stiftungsrecht': ['stiftung', 'privatstiftung', 'stiftungsvorstand'],\\n 'Nachhaltigkeit/ESG': ['nachhaltigkeit', 'klima', 'csddd', 'lieferkette'],\\n # ... add more as needed\\n}\\n```\\n\\nCount per topic and per year; look for *recent* clusters (2023+) as indicators of active interest.\\n\\n---\\n\\n## Step 4: Topic Selection Strategy\\n\\nFor thesis topics that maximize acceptance chance:\\n\\n1. **Highest volume** → safest (professor has written most about this, you can cite them heavily)\\n2. **Recent activity** → highest interest (they're currently building this area)\\n3. **Cross-cutting topics** → best of both worlds (bridges two of their established fields)\\n\\nFor Kalss specifically:\\n- Aufsichtsrat: 91 publications, 44 since 2016 → safest\\n- Nachhaltigkeit/ESG: 11 publications, all from 2022–2025 → her current passion\\n- Mehrstimmrechte: 36 publications, co-authored with Hopt → prestige connection\\n\\n---\\n\\n## Austrian Legal Research: Source Strategy\\n\\n### RIS (Rechtsinformationssystem des Bundes) — DO NOT USE\\n\\nRIS at `ris.bka.gv.at` is **completely broken for programmatic access**. Every approach fails:\\n\\n- **GeltendeFassung.wxe** returns 404 for valid Gesetzesnummern (e.g. WEG 2002: 20000724) — \\\"nicht mehr oder noch nicht in Kraft\\\" even when the law is in force. Jina.ai captures only this error message.\\n- **Dokument.wxe** with NOR-nummer (e.g. NOR40252684) returns **random wrong documents** — an ABGB query returned \\\"Land- und forstwirtschaftliche Verordnung biologische Arbeitsstoffe § 10\\\"\\n- **ELI URLs** (`/eli/bgbl/I/2002/70/P13/...`) redirect to completely wrong laws (e.g. \\\"Limit-Verordnung 2012/13\\\" instead of WEG § 13)\\n- **OGH decision search** (`Ergebnis.wxe?Abfrage=Justiz`) returns ASP.NET ViewState pages — Geschäftszahlen and titles are buried in postback-dependent JavaScript, unextractable by curl or Jina\\n- **HTML-only URLs** (`/Dokumente/Bundesnormen/NOR.../NOR....html`) return 44 KB pages with zero text content after tag stripping — just navigation and JavaScript\\n- **Jina.ai** captures only the navigation sidebar, not document content, because RIS is a SPA that renders content client-side via ViewState postbacks\\n\\n### Workflow for Austrian Legal Research (USE THIS)\\n\\n```\\n1. JUSLINE.at → Gesetzestext im Volltext (immer treffer, direkt verlinkbar)\\n2. delegate_task mit web-Toolset → OGH-Rechtsprechung + Fachliteratur finden\\n3. Ergebnis als Markdown-Gutachten in /tmp/ speichern lassen\\n4. Gutachten lesen + Quellen prüfen, dann als Antwort formatieren\\n```\\n\\n### 1. JUSLINE.at — Primary Source for Gesetzestexte\\n\\nDirectly linkable, always returns current text. URL pattern:\\n- `https://www.jusline.at/gesetz/abgb/paragraf/829` → § 829 ABGB\\n- `https://www.jusline.at/gesetz/weg/paragraf/13` → § 13 WEG 2002\\n- `https://www.jusline.at/gesetz/abgb/paragraf/781` → § 781 ABGB (Schenkungsanrechnung)\\n\\nJUSLINE HTML is clean: strip `