metaclaw-evolving-agent — Claude Code skill: deploy MetaClaw

What metaclaw-evolving-agent does

MetaClaw sits in front of your LLM as an OpenAI-compatible proxy. Clients point at http://localhost:<port>, and the agent intercepts each turn, pulls relevant skills into the system prompt, and stores the exchange in an experience buffer. The skill covers installation, the metaclaw setup wizard, and three run modes: skills injection alone, immediate RL training, or madmax, where a scheduler pushes weight updates into idle and sleep windows.

You get guidance on ~/.metaclaw/config.yaml, the environment variables, and the Python API — MetaClawAgent, SkillStore, SkillInjector, ExperienceBuffer, RLTrainer, RewardModel. The skills_only mode needs no GPU. RL training wants METACLAW_TINKER_API_KEY, or METACLAW_MINT_API_KEY when the backend is mint. Meeting detection in the scheduler reads OAuth credentials from GOOGLE_CALENDAR_CREDENTIALS_PATH.

Set METACLAW_LLM_API_KEY before anything else. Without it the proxy has no upstream model to forward to, and metaclaw start gets you nowhere. Installation runs from the local repo with pip install -e . plus extras: [rl], [evolve], [scheduler].