ai-common

API debugging agent with full IO capture, log analysis, and codebase exploration

Control per-directory public/private visibility via git submodules

Analyze content from URLs (YouTube, LinkedIn, web posts, Git repos) and generate structured learning plans or analysis documents

Universal AI harness engineering: 6-layer architecture with SDD pipeline, ambiguity-gated shaping, 6-dimension review, lifecycle (GC/evolve/diet/audit), doctor health-check, enforcement hooks, context routing, and doc generation

Study pipeline: parse topics from temp.md, refine direction via brainstorming, execute structured deep-learning with codebase exploration and interview prep

Idea-to-implementation pipeline: raw ideas → structured PRDs → brainstorming refinement → service scaffolding

Launch kit for new desktop apps — scaffold README/LICENSE/Distribution + GitHub SEO metadata + release pipeline + GitHub Pages banner + discoverability checklist. Validated on macOS menu bar apps (muxbar, aieye).

Build and incrementally update a developer portfolio from git commit history. Default: current repo + ~/.claude/portfolio/{user}.md. Modes: single repo, multi-repo, GitHub-wide scan

Analyze layered CLAUDE.md/memory/settings to surface which rules survive (Active) vs overridden in the current session. Introspect + fs evidence verification + hybrid output. Cross-repo diff + virtual prompt simulation.

Dynamic skill quality evaluator — fork target skills, enforce JSON output via --json-schema, run N-repeat against ground-truth snapshots with semantic-judge + calibration, surface regressions vs baseline + auto-propose SKILL.md edits