codebase-inspection
Skill22 starsChanged 8 days agoMITView on GitHub
First-pass survey of an unfamiliar codebase. Counts LOC by language, finds entry points and config files, scans the dependency graph, and reports back in three sections (shape, conventions, risks) so the agent grounds its next action in what's actually there rather than guessing.
25 other projects use a version of this.
Adopted by
Most recently taken up by
- ashleysbrain/skillstheir own version, first seen Nov 8, 2026
- delorenj/skillstheir own version, first seen Nov 7, 2026
- gquthier/CLAWGtheir own version, first seen Oct 17, 2026
- iberi22/skillstheir own version, first seen Oct 15, 2026
- Fahrnetic/engineering-agent-skill-workflowtheir own version, first seen Oct 15, 2026
- Stuko0/alice-agenttheir own version, first seen Oct 13, 2026
Used with
Projects with it also use touchdesigner-mcp, blocked-page-recovery and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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Tommy-ywSkillsongwriting-and-ai-music
Songwriting craft, AI music generation prompts (Suno focus), parody/adaptation techniques, phonetic tricks, and lessons learned. These are tools and ideas, not rules. Break any of them when the art calls for it.
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aivrarSkillcompetitor-news-monitor
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mae616Skillp5js
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Also in 12 projects that use this
- +3 more from aivrar
Other versions25 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 25
- NousResearch/hermes-agent★ 262ksame name
- math-inc/OpenGauss★ 1.3ksame name
- Tommy-yw/RunbookHermes★ 546same name
- aivrar/portable-hermes-agent★ 239same name
- RedWoodOG/Hermes-Desktop★ 177same name
- AtlasOmnia/donna-starter★ 136same name
- AtlasOmnia/hermes-custom-pack★ 75same name
- wundercorp/loki★ 28same name
- delorenj/skills★ 17same name
- gquthier/CLAWG★ 16same name
15 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository45 other files it gives its agents.
- AGENTS.mdAGENTS.md
- dependency-analyzerSkill
- docsSkill
- handoffSkill
- openai-reviewerSkill
- plugin-homeSkill
- schema-validatorSkill
- security-auditSkill
- session-auditSkill
- test-validatorSkill
- claude-codeSkill
- codexSkill
- opencodeSkill
- chartsSkill
- export-csvSkill
- export-excelSkill
- make-chartSkill
- make-html-reportSkill
- make-pdfSkill
- a2a-communicateSkill
- a2a-handle-inboundSkill
- ethos-skill-authoringSkill
- native-mcpSkill
- github-authSkill
- github-code-reviewSkill
- github-issuesSkill
- github-pr-workflowSkill
- github-repo-managementSkill
- birth-ritualSkill
- get-to-know-youSkill
- xurlSkill
- arxivSkill
- grounded-citationsSkill
- research-paper-writingSkill
- reddit-researchSkill
- code-reviewSkill
- coding-agentSkill
- planSkill
- requesting-code-reviewSkill
- spikeSkill
- subagent-driven-developmentSkill
- systematic-debuggingSkill
- tddSkill
- writing-plansSkill
- no-ai-slopSkill
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 24 edited versions we read keep these.
2
Distinctive
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 67
Read whichever exist, in order:
- Distinctive: line 128
Inventing rules: If CLAUDE.md says nothing about commit messages, don't enforce a convention you imagined.
“Common” is measured: kept by at least 6 in 10 of the 24 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Codebase Inspection
Survey a codebase you don't already know before recommending changes. The output is a short report, not a deep dive.
When to use this skill
- Agent is about to work in a repo it has never touched in this session.
- User asks "what does this project do?" or "walk me through the layout".
- A change request lands and you can't articulate the architecture from memory.
When NOT to use this skill
- The repo is already familiar — re-running the survey on every turn is waste.
- The user asked for a specific file edit — read just that file, don't survey the world.
- The task is "fix this typo" — the survey is overkill.
Step 1 — top-level shape
ls -la
git log -1 --format="%h %s · %ad" --date=short # last commit, when
cat README.md 2>/dev/null | head -60 # what the project says it isNote the top-level layout: monorepo (packages/, apps/, extensions/)? Library (src/, lib/)? Framework (pages/, routes/, app/)?
Step 2 — language + size
# Lightweight, no install — works in any unix shell
git ls-files | sed 's/.*\.//' | sort | uniq -c | sort -rn | head -10
# Richer if pygount is available
command -v pygount >/dev/null && pygount --format=summary . 2>/dev/nullCapture: which languages dominate, rough LOC, the file-type ratio (e.g. "80% TS, 12% test, 5% config, 3% docs").
Step 3 — convention files
Read whichever exist, in order:
| File | Role |
CLAUDE.md / AGENTS.md / .cursorrules | Project rules for agents |
CONTRIBUTING.md | Human-process rules |
ARCHITECTURE.md / DESIGN.md | Structural source of truth |
package.json / pyproject.toml / Cargo.toml | Manifest + scripts + deps |
tsconfig.json / biome.json / eslint.config.* | Tooling + style |
.github/workflows/*.yml | CI gates |
The point is to learn the rules before changing anything. Don't invent new ones.
Step 4 — entry points
Find where execution starts:
# Node / TS
grep -E '"main"|"bin"|"exports"' package.json 2>/dev/null
# CLI binary?
ls bin/ 2>/dev/null; ls cmd/ 2>/dev/null
# Tests
find . -name "*.test.*" -not -path "*/node_modules/*" | head -5Step 5 — dependency surface
# Node
jq -r '.dependencies // {} | keys[]' package.json 2>/dev/null | head -20
# Python
head -40 pyproject.toml 2>/dev/null
# Anything
find . -maxdepth 2 -name "*.lock" -o -name "package-lock.json" -o -name "yarn.lock" -o -name "pnpm-lock.yaml" -o -name "uv.lock" 2>/dev/null | headStep 6 — write the report
Return three short sections — no more than 20 lines total. The user wanted a survey, not a re-read of the codebase.
## Shape
- <language(s) + LOC bucket + monorepo/library/framework>
- <top-level layout in one sentence>
- <entry point(s)>
## Conventions
- <rules source: CLAUDE.md / AGENTS.md / etc.>
- <build/test commands from the manifest>
- <style/lint tooling>
## Risks for the requested change
- <pre-existing test failures / lint baselines / frozen schemas>
- <relevant constraints from rules files>
- <anything surprising>Anti-patterns
- Re-reading every file. Survey is fast and shallow. Deep reads are for the actual change.
- Inventing rules. If
CLAUDE.mdsays nothing about commit messages, don't enforce a convention you imagined. - Skipping the rules step. The whole point of the survey is to ground later changes in documented rules.
- Re-running the survey on every turn. Once is enough per repo per session.
Hard rules
- Findings come with file paths. "There's a frozen schema" without
<path>is gossip. - Survey reads, never writes. No
write_file, nopatch_file, nogitmutations. - Stop at the report. The next turn decides what to do; this skill's job ends at "here's what's there".
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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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.

