claude-ecosystem-hygiene

Use when an agent harness's skills/tools catalog has grown large (hundreds+, e.g. from an auto-skill-minting loop) and is taxing context: the listing of skill names+descriptions is injected every turn AND into every subagent, so cost multiplies on fan-out and small-context agents can overflow ("Prompt is too long" at 0 tokens). This skill is the AUDIT + CURATION methodology plus measurement/reporting: the trimming levers are now native harness features (Claude Code ships them built in) — the durable value is deciding WHAT to trim (episodic lessons vs real skills), applying it safely, and measuring the result. The PROBLEM + curation METHODOLOGY are harness-agnostic — the Agent Skills open standard (agentskills.io) is shared by Claude Code, Cursor, Codex, Copilot CLI, Gemini CLI; only the levers differ. Covers: the portable diagnosis + classification rigor (curate by INTENT not name, conservative asymmetry, blind re-rate, deterministic checks over LLM votes); the cross-harness landscape (native budget on Claude

Wire up CI validation and automatic release-cutting for a Claude Code plugin or marketplace repo (a repo with a `.claude-plugin/marketplace.json` and `plugins/*`). Adds two GitHub Actions — a structure validator that runs on every PR/push, and a release-on-version-bump job that cuts a GitHub Release whenever a `VERSION` file changes — plus the bundled validator script and workflow templates. Use this WHENEVER a plugin/marketplace repo has no CI, when GitHub Releases have drifted behind the shipped version (e.g. release says v2.0.0 but the skill is v3.3.0), when the user says "set up CI for my plugin repo / marketplace", "my releases keep falling behind", "tag/release on version bump", "auto-cut releases", "validate my marketplace.json / plugin.json", "catch when a plugin folder and its plugin.json name disagree", or has just added/bumped plugins and wants releases to keep up. Works for both single-plugin repos (nested `skills/<name>/`) and multi-plugin bundles (flat `plugins/<name>/`). Don't use for: generic

Pre-PR checklist and repo cleanup for data science and analytics projects. Use this skill BEFORE creating a PR, merging branches, or handing off a repo. Catches common mistakes that waste hours later: data files committed to git, hardcoded paths, runtime artifacts tracked, branch ownership confusion, internal docs drifting from deliverables, and client data in public repos. Also use when the user says "clean up the repo", "is this ready to merge?", "prepare for handover", "before we push", "repo hygiene", or when you notice tracked .csv, .db, .parquet, or /Users/ paths during any file operation. Especially important for repos with multiple contributors working on parallel branches. Also covers reviewing/auditing a published plugin/skill repo: probe live CI + run the repo's own tests before eyeballing files ("review if this repo needs updating", "is this repo up to date?", "audit my plugin repo").

Scan a portfolio of authored Claude Code skills and produce, per target repo, a precise list of which skills to ADD, which to UPDATE (with direction), and which to CROSS-LINK rather than copy. Uses a per-repo function-level inclusion bar, portfolio deduplication (never recommend a skill already homed as its own repo or in a sibling target), and a version/`last_verified` divergence check for updates. Use this WHENEVER the user asks "which of my skills should go in repo X", "scan my skills and tell me what to add or update in these repos", "where should this new skill live", "find skills in the wrong bundle or duplicated across repos", "which repos have stale copies of skills I've improved locally", or wants to reorganize/consolidate a multi-repo skill portfolio. This is PLACEMENT/FIT mapping, and it produces a recommendation report — it never mutates repos. Don't use for (these are different tools): standardizing READMEs/badges or catching factual errors across skills (`skill-portfolio-audit`), finding dormant

ALWAYS use this skill when the user asks any question about their Claude Code setup, installed skills, memory system, handoffs, worktrees, or ~/.claude directory health. This is the go-to skill for introspection of the Claude Code environment itself. Specifically trigger on: (1) Skill inventory questions — "how many skills do I have", "which skills am I using", "what's dormant", "which skills can I uninstall", "are there overlapping skills"; (2) Cleanup and hygiene requests — "clean up my ecosystem", "audit my setup", "~/.claude feels bloated", "monthly hygiene check", "what needs cleanup", "stale worktrees", "orphaned handoff prompts"; (3) Diagnostic symptoms — "my memory system isn't working", "lessons aren't being picked up", "skill is not triggering", "claude keeps forgetting", "why is the wrong skill firing", "duplicate skill confusion"; (4) Health dashboards — "show me a health dashboard", "utilization across skills/memory/handoffs", "ecosystem health report"; (5) Any mention of auditing persistent arti

Detect stale normative guidance after the user adds a NEW "don't X / avoid Y" rule to ~/.claude/lessons.md, ~/.claude/axioms.md, or any ~/.claude/projects/<slug>/memory/feedback_*.md. Also audits ~/.claude/skills/ for skills whose `last_verified` frontmatter has expired or that opt into a freshness contract without declaring one (axiom #21). Trigger when: (1) a PostToolUse hook fires on Edit|Write to one of those memory files and the diff contains a new negation rule; (2) user asks "are my project docs still consistent with my lessons / feedback?", "any stale advice in docs/?", "run doc freshness audit", "any stale skills?"; (3) weekly cron audit is due. Produces a list of CANDIDATE stale claims — file:line refs only. NEVER auto-edits. Conservative by design: for prose lint, surfaces only when the new rule has an explicit negation (don't / never / avoid / stop) AND a multi-token searchable phrase AND ≥1 grep hit. For skill freshness, the default mode flags only on EXPLICIT frontmatter signals (expired `last_v

Audit and clean up Claude Code's persistent memory system — MEMORY.md, memory files, lessons, and ADRs. Use this skill when: (1) the user asks to clean up, audit, or review their memory/lessons/ADRs, (2) MEMORY.md is approaching or exceeding the 200-line limit, (3) lesson files have grown large and may contain duplicates, (4) you notice ADR numbering conflicts, (5) memory files seem stale or contradicted by current code, or (6) the user says things like 'my memory is getting messy', 'clean up my lessons', 'deduplicate', 'review ADRs', 'memory audit'. Also proactively suggest running this after 10+ sessions on a project, or when MEMORY.md triggers a truncation warning.

Quantitatively measure how effective a project's automated tests are at catching real bugs. Use this skill when: (1) the user asks 'how good are our tests?', 'do our tests actually catch bugs?', 'measure test effectiveness', or 'audit our test suite'; (2) a team has anecdotal impressions about test quality but no data; (3) before investing in more tests, to identify which gaps matter most; (4) after an incident slipped through CI, to understand whether the test suite should have caught it; (5) when evaluating whether a CI pipeline is paying for itself. Produces a report at ~/Documents/<project>_test_effectiveness_audit.md with per-incident catch rates, a classified gap list, and targeted recommendations. Read-only relative to project source — does not modify code or auto-write tests.

Run a counterfactual A/B harness on Claude Code to measure whether the user's ~/.claude setup (memories, lessons, axioms, skills, hooks, plugins) actually helps on real tasks vs. a blank-canvas env. Use when: (1) User wants to "prove my setup works" or "quantify setup impact" to colleagues; (2) User asks "is my setup actually helping" beyond what ecosystem-audit's reference-count scan can show; (3) A project has the counterfactual measurement step of an audit → measure → clean pipeline queued. Covers the clean-env mechanism (CLAUDE_CONFIG_DIR), what it does and doesn't isolate, fair-comparison knobs (model pinning, permission mode, stdin), how to mine num_turns/tool_calls/pitfall-hits from the resulting JSONL transcripts, and the honest caveats any n=3 harness report must declare.