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Analyze an unfamiliar codebase and generate a structured onboarding guide with architecture map, key entry points, conventions, and a starter CLAUDE.md.
Passed 11 of 17 test cases with the skill, and 9 of 17 without it.
and 4 more in the full report
6 fixed8 passed either way5 still failing3 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
When building the directory snapshot in the initial reconnaissance phase of codebase analysis, how many directory levels deep should be inspected and which directories must be excluded?
| Checked | Without skill | With skill |
|---|---|---|
| Limits directory snapshot analysis to the top 2 levels | Missed | Passed |
| Excludes heavy dependency and build directories like node_modules, vendor, or .git | Passed | Passed |
The instructions your model reads when the skill loads.
Systematically analyze an unfamiliar codebase and produce a structured onboarding guide. Designed for developers joining a new project or setting up Claude Code in an existing repo for the first time.
Gather raw signals about the project without reading every file. Run these checks in parallel:
1. Package manifest detection
→ package.json, go.mod, Cargo.toml, pyproject.toml, pom.xml, build.gradle,
Gemfile, composer.json, mix.exs, pubspec.yaml
2. Framework fingerprinting
→ next.config.*, nuxt.config.*, angular.json, vite.config.*,
django settings, flask app factory, fastapi main, rails config
3. Entry point identification
→ main.*, index.*, app.*, server.*, cmd/, src/main/
4. Directory structure snapshot
→ Top 2 levels of the directory tree, ignoring node_modules, vendor,
.git, dist, build, __pycache__, .next
5. Config and tooling detection
→ .eslintrc*, .prettierrc*, tsconfig.json, Makefile, Dockerfile,
docker-compose*, .github/workflows/, .env.example, CI configs
6. Test structure detection
→ tests/, test/, __tests__/, *_test.go, *.spec.ts, *.test.js,
test cases passed, vs 9 / 17 without
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