ecosystem-audit
Skill1 starsChanged 5 months agoMITView on GitHub
Audit your entire .claude ecosystem (skills, agents, slash commands, hooks, rules, memory) for duplicates, overlapping capabilities, stale one-off demos, contradictory rules, and context bloat. Use ~monthly or when things feel cluttered — "audit my .claude", "find duplicate skills", "what's stale", "ecosystem audit", "clean up my agents", "find contradictory rules". Returns a low/medium/high prioritized fix list with reasons and exact paths.
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 33
Run finders in parallel, each scoped to one rot type:
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Ecosystem Audit
Periodic hygiene for a sprawling agentic OS. Inspired by Mark Kashef's third dynamic-workflow use case (YT 9_ExDZFlaNc): as you keep adding skills/agents/rules, things go stale and contradictory, and you never have time to revisit. Fan out agents to find the rot.
When to run
Sporadically — every couple weeks to monthly. NOT daily. It burns tokens via fan-out. Differs from capabilities (which counts/indexes what exists) and agent-enlightenment (which designs new agents): this one finds what to delete, merge, or fix.
The recipe
1. Deterministic inventory (zero LLM tokens)
# Skills
find ~/.claude/skills -maxdepth 2 -name 'SKILL.md' | wc -l
# Slash command name collisions (the foo-bar vs foo:bar pattern)
ls ~/.claude/commands | sed -E 's/[-:]/ /' | awk '{print $1}' | sort | uniq -d
# Agents (active vs dormant)
ls ~/.claude/agents/*.md ~/.claude/agents/dormant/*.md
# Memory files
find ~/.claude/projects/*/memory -name '*.md' | wc -l
# Hook surface
jq '.hooks' ~/.claude/settings.json2. Fan-out finders (Workflow tool, explicit opt-in)
Run finders in parallel, each scoped to one rot type:
- duplicate-skill-finder — same capability under different names; stock Anthropic skills copied multiple times; plugin variants shadowing local skills (your CLAUDE.md may already flag certain skills as existing multiple times).
- stale-demo-finder — skills/agents created for one demo/video and never used again. Cross-reference names against the tool-use histogram from a session mine — a
Skillinvocation count of 0 for a skill = never fired. - command-collision-finder — duplicate slash commands (e.g.,
dev-<project>vsdev:<project>,db-reset-*vsdb:reset-*, aliased save commands likesv/save/svg/svgg). - rule-contradiction-finder — contradictory or superseded rules across CLAUDE.md + context files + memory files (e.g., a rule that says "never push to main" vs a per-project exception; superseded branching guidance).
- dormant-bloat-finder — dormant agents that will never wake; orphaned hooks pointing at deleted scripts.
3. Synthesis → prioritized fix list
One synthesis agent merges findings into:
- HIGH — actively costs context/tokens every session, or causes wrong behavior (duplicated always-on skills, contradictory load-bearing rules).
- MEDIUM — clutter that degrades discoverability (duplicate commands, stale demos).
- LOW — cosmetic / nice-to-have.
Each item: what, where (exact path), why it's a problem, recommended action (delete / merge / rename / fix), and rollback note for anything destructive.
Guardrails
- Read before recommending deletion. A skill/agent that looks stale may be load-bearing for a hook or cron. Cross-check against
settings.jsonhooks, launchd, and cron before flagging for delete. - Output is a report, not auto-deletion. Destructive cleanup is a separate, narrated step.
- Enumerate matches and sniff size before any
rm— never bulk-delete blind.
Workflow reliability (learned in practice)
The finder agents do heavy investigation (Read/Grep/Bash) — forcing a schema on them is fragile (some fail the first run). Prefer: finders return MARKDOWN findings, a synthesis agent structures them; OR end each finder prompt with "Your FINAL action MUST be the StructuredOutput call." Also: the orphaned-hook + memory-contradiction dimensions are cheaper done deterministically (jq over settings.json hooks + test -f each script; grep MEMORY.md links vs files) than via agents.
In this repository54 other files it gives its agents.
- AGENTS.mdAGENTS.md
- skills/deep-recon/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- adversarial-researchSkill
- algorithmic-artSkill
- api-integrationSkill
- breakdownSkill
- c4-architectSkill
- canvas-designSkill
- coding-agentsSkill
- compound-engineeringSkill
- context-budgetSkill
- counterfactualSkill
- critiqueSkill
- d3js-visualizationSkill
- data-analyst-agentSkill
- database-migrationsSkill
- deep-reconSkill
- design-tasteSkill
- doc-coauthoringSkill
- e2b-sandboxSkill
- excalidraw-diagramSkill
- executing-plansSkill
- frontend-designSkill
- fullstack-agentSkill
- grillSkill
- kickoffSkill
- mcp-builderSkill
- model-migrationSkill
- naming-the-machineSkill
- full-output-enforcementSkill
- package-researchSkill
- pdf-generationSkill
- pp2pSkill
- pp3pSkill
- prompt-engineerSkill
- prompt-groundingSkill
- redesignSkill
- requesting-code-reviewSkill
- reverse-engineer-to-learnSkill
- review-changesSkill
- scratchpadSkill
- shipSkill
- slack-gif-creatorSkill
- sprint-architectSkill
- techdebtSkill
- test-and-fixSkill
- threat-modelSkill
- verification-before-completionSkill
- visual-verdictSkill
- webapp-testingSkill
- web-asset-generatorSkill
- whatdidimissSkill
- writing-plansSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

