Agentype

Description

--- name: agentype description: Run the Agentype workflow for local AI-agent usage analysis: collect and cache deterministic JSON, infer a persona/archetype from aggregate usage signals, then render a terminal summary or PNG poster. Supports Claude Code, Codex, OpenCode, pi-agent, Gemini CLI, OpenClaw, Nanobot, and configured Nanobot-compatible roots. Use when the user asks to understand their agent usage, AI workflow, token footprint, preferred agents/models/projects, or "agentype". version: 0.1.3 tags: [ai-agents, analytics, persona, tokens, local-first] --- # Agentype Agentype summarizes a user's local AI-agent history into one deterministic usage overview. In skill mode, the triggering agent must run a short workflow: collect and cache JSON, infer the persona/archetype from that JSON, then render the final text or image poster. ## When to Use Use this skill when the user asks: - "what is my agentype?" - "analyze my agent usage" - "show my AI usage stats" - "which agents or models do I use most?" - "what persona am I based on my AI workflow?" - `/agentype` Do not use it for billing estimates. Agentype reports tokens and local usage signals, not provider invoices. ## What It Reads Agentype collects local session and token metadata from supported agents where available: - Claude Code - Codex - OpenCode - pi-agent - Gemini CLI - OpenClaw - Nanobot - Nanobot-compatible JSONL roots configured through `AGENTYPE_NANOBOT_ROOTS` Agentype is fully local in this skill workflow. It reads agent history from disk and prints a terminal summary. Handle persona inference on the agent side rather than asking the CLI to contact external model services. ## Required Skill Workflow When this skill is triggered by an agent, do the full loop below. The first CLI output is only the raw deterministic stats view; it is not the final user-facing Agentype result. The PyPI distribution is `agentype-cli` because `agentype` is not available on PyPI. The installed command is still `agentype`. 1. Collect and cache the deterministic analysis: ```bash agentype --json-out ``` If `agentype` is not installed and there is no source checkout, run the published CLI directly: ```bash uvx --from agentype-cli agentype --json-out ``` From a source checkout, use: ```bash uv run agentype --json-out ``` 2. Read the cached JSON at `output/agentype.json`. 3. Infer the user's persona from aggregate signals in the JSON: top projects, agents, models, skill metadata, token shape, and usage rhythm. 4. Fill these top-level JSON fields in `output/agentype.json`, preserving all other fields: - `archetype`: short persona label. - `description`: one-line explanation of the archetype. - `keywords`: 3-6 concise keywords. - `comment`: 2-3 evidence-grounded sentences starting with "You are a...". 5. Render the filled JSON: ```bash agentype --json-in output/agentype.json ``` For chat, IM, or gateway environments that can display images, also create the poster image: ```bash agentype --json-in output/agentype.json --png-out ``` 6. Final response: - Terminal agents: relay the rendered text summary with the persona/archetype and top stats. - Chat or IM gateway agents: send a compact text summary and attach `output/agentype.png` when supported. 7. Do not expose raw session files, prompts, private transcripts, or full JSON unless the user explicitly asks for debugging data. ## Run For manual CLI use outside the agent workflow, if Agentype is installed: ```bash agentype ``` If working from a source checkout: ```bash uv run agentype ``` For users without `uv`, prefer installing the published CLI: ```bash pipx install agentype-cli agentype ``` ## Custom Local Paths If a user's agent history lives outside the default locations, ask for the relevant root and configure it before running Agentype. Nanobot-compatible JSONL roots can be added with `AGENTYPE_NANOBOT_ROOTS`: ```bash AGENTYPE_NANOBOT_ROOTS="/path/to/workspace:/path/to/another/root" agentype --json-out ``` For unsupported agent layouts, tell the user the collector paths live in `src/agentype/paths.py` and source adapters live in `src/agentype/sources/`, so they can add their own local path or adapter before publishing private stats. ## Output Modes - Default: terminal overview with AGENTYPE/persona first when persona fields exist, otherwise deterministic token usage, breakdowns, and trends. No LLM calls by default. - `-v`: adds detailed tables for statistics, discovered themes, and data confidence. - `--json-out`: writes `output/agentype.json` with the full analysis. - `--json-in PATH`: renders a previously written Agentype JSON file. Use this after filling top-level persona fields. - `--png-out`: writes `output/agentype.png`, a shareable poster-style summary for chat or IM environments. ## Debugging If the user asks for debugging or validation, rerun collection as: ```bash agentype -v --json-out ``` From a source checkout: ```bash uv run agentype -v --json-out ```

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