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round3ai/three-dev

unversioned · a054d79415faMIT

Integrate three.dev into a codebase and work with recorded LLM traffic: route calls through the proxy, define use cases and quality metrics, investigate failure modes, and test prompt or model changes with offline experiments, using the three.dev MCP server.

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skills

three-dev-setup

Adds three.dev to a codebase so its LLM calls are recorded. Connects the app to the user's three.dev organization with one approval in the browser, finds every LLM call site, groups the calls into use cases, and routes them through the three.dev proxy (gate.three.dev) with the app's own provider key plus use case, session, and environment headers. Use when the user mentions three.dev, gate.three.dev, or X-Three headers, asks to record or monitor their LLM calls, or wants to set up, connect, or extend a three.dev integration. Covers OpenAI, Anthropic, Gemini, Azure OpenAI, OpenRouter, Concentrate, Portkey, Bedrock, LiteLLM, Vercel AI SDK, and LangChain and LangGraph clients. Not for investigating failure modes or reading recorded conversations; that is the three-dev-failure-modes skill.

Read SKILL.md at the source

Pinned to revision a054d79415fa, so it is the text this page describes rather than whatever the author pushed since.

Pre-approved tools experimental

Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.

  • Bash(curl -sS -X POST https://api.three.dev/api/v1/setup/status *)

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