Set up hierarchical Intent Layer (AGENTS.md files) for codebases. Use when initializing a new project, adding context infrastructure to an existing repo, user asks to set up AGENTS.md, add intent layer, make agents understand the codebase, or scaffolding AI-friendly project documentation.
End-of-cycle learning capture and triage. Run after completing a feature, fixing a bug, or finishing any significant work. Reviews pending learnings, analyzes conversation for undocumented insights, and integrates into the Intent Layer with appropriate scope (global workflow vs local code).
Quick health check for Intent Layer - validates nodes, checks staleness, reports coverage gaps
Remove the Intent Layer from a repository. Deletes all child AGENTS.md files and removes the Intent Layer section from the root CLAUDE.md.
Interactive review of pending mistake reports from the learning loop. Walk through each report with the user, accepting/rejecting/discarding as appropriate.
Extract Intent Layer content from git history. Analyzes commits, PRs, and blame to discover pitfalls, contracts, architecture decisions, and entry points that should be documented in AGENTS.md files.
Use when maintaining an existing Intent Layer, during quarterly reviews, after significant code changes, when something confused you, or when user asks to audit/update CLAUDE.md or AGENTS.md files.
Get oriented in an unfamiliar codebase using its Intent Layer. Use when joining a new project, exploring a codebase for the first time, or helping someone understand "where do I start?" questions.