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Get Started Free →Analyze a codebase and generate onboarding docs: architecture overviews, file maps, setup guides, runbooks, and debugging guides. Use when onboarding new team members, open-sourcing, or documenting after a major refactor.
.claude/skills/borghei-codebase-onboarding/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 3% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 35% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -20% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 282% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 26% | 0% |
Analyze any codebase and generate production-quality onboarding documentation tailored to the audience. Produces architecture overviews with system diagrams, annotated key file maps, step-by-step local setup guides, common developer task runbooks, debugging guides with real error solutions, and contribution guidelines. Supports Markdown, Notion, and Confluence output formats.
git clone-to-tests steps, env-var docs, infra setup (Docker/DB/cache), and a verification checklist.Keywords: codebase onboarding, developer experience, documentation, architecture overview, setup guide, debugging guide, contribution guidelines, code walkthrough, new hire onboarding
Before generating the docs, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
| Tool | Purpose | Command | |------|---------|---------| | architecture_mapper.py | Analyze project structure and generate a high-level architecture map | python scripts/architecture_mapper.py /path/to/project --json | | onboarding_generator.py | Scan a project directory and generate an onboarding guide | python scripts/onboarding_generator.py /path/to/project --json | | setup_validator.py | Validate a project's development setup completeness | python scripts/setup_validator.py /path/to/project --json |
All tools accept an optional directory argument (default: current directory) and --json for machine-readable output.
Load the reference that matches the task — keep this file lean and pull detail on demand:
This skill covers:
This skill does NOT cover:
engineering/changelog-generator for release-oriented docs or engineering/api-design-reviewer for API qualityengineering/ci-cd-pipeline-builder for pipeline automationengineering/skill-security-auditor for security auditingengineering/runbook-generator for operational runbooks| Skill | Integration | Data Flow | |-------|------------|-----------| | engineering/runbook-generator | Onboarding task runbooks can seed operational runbooks for production incident response | Onboarding runbook templates → Runbook Generator for ops-grade expansion | | engineering/api-design-reviewer | API route analysis from Phase 1 feeds into API design quality reviews | Discovered API endpoints → API Design Reviewer for consistency checks | | engineering/database-schema-designer | Database schema files identified during key file mapping inform schema design reviews | Schema file paths and ORM type → Schema Designer for migration planning | | engineering/tech-debt-tracker | Technical debt items surfaced during architecture analysis should be logged for tracking | Architecture analysis findings → Tech Debt Tracker backlog entries | | engineering/ci-cd-pipeline-builder | CI/CD config discovered in Phase 1 can be validated and improved by the pipeline builder | CI config paths and workflow list → Pipeline Builder for optimization | | engineering/dependency-auditor | Dependency counts and lockfiles gathered in Phase 1 feed directly into security and license audits | Package manifests and lockfiles → Dependency Auditor for vulnerability scanning |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 30,483 | 31,988 | +5% | 1 | 1 | 0% | 5,850 | 7,568 | +29% | 0 | 0 | — |
case-02 | fail→fail | 25,033 | 30,342 | +21% | 1 | 1 | 0% | 4,591 | 6,968 | +52% | 0 | 0 | — |
case-03 | fail→pass | 12,233 | 5,750 | -53% | 1 | 1 | 0% | 2,299 | 2,364 | +3% | 0 | 0 | — |
case-04 | fail→pass | 10,657 | 9,359 | -12% | 1 | 1 | 0% | 2,214 | 2,991 | +35% | 0 | 0 | — |
case-05 | fail→pass | 17,851 | 5,923 | -67% | 1 | 1 | 0% | 2,873 | 2,312 | -20% | 0 | 0 | — |
case-06 | fail→pass | 11,111 | 34,186 | +208% | 1 | 1 | 0% | 1,968 | 7,517 | +282% | 0 | 0 | — |
case-12 | pass→pass | 19,345 | 29,065 | +50% | 1 | 1 | 0% | 3,478 | 6,599 | +90% | 0 | 0 | — |
case-07 | fail→pass | 9,173 | 2,986 | -67% | 1 | 1 | 0% | 1,501 | 1,888 | +26% | 0 | 0 | — |
case-08 | fail→pass | 16,496 | 1,557 | -91% | 1 | 1 | 0% | 2,720 | 1,581 | -42% | 0 | 0 | — |
case-09 | fail→pass | 16,347 | 1,864 | -89% | 1 | 1 | 0% | 1,016 | 1,641 | +62% | 0 | 0 | — |
case-10 | pass→pass | 15,254 | 16,330 | +7% | 1 | 1 | 0% | 2,472 | 3,891 | +57% | 0 | 0 | — |
case-11 | fail→pass | 17,171 | 25,096 | +46% | 1 | 1 | 0% | 2,993 | 5,665 | +89% | 0 | 0 | — |
case-13 | pass→pass | 16,214 | 13,417 | -17% | 1 | 1 | 0% | 2,550 | 3,348 | +31% | 0 | 0 | — |
case-14 | pass→pass | 17,741 | 26,851 | +51% | 1 | 1 | 0% | 2,768 | 5,855 | +112% | 0 | 0 | — |
case-15 | pass→pass | 26,262 | 35,514 | +35% | 1 | 1 | 0% | 3,771 | 6,288 | +67% | 0 | 0 | — |
case-16 | pass→pass | 17,366 | 36,702 | +111% | 1 | 1 | 0% | 2,734 | 7,516 | +175% | 0 | 0 | — |
case-17 | fail→pass | 19,629 | 5,544 | -72% | 1 | 1 | 0% | 2,958 | 2,174 | -27% | 0 | 0 | — |
case-18 | pass→pass | 20,684 | 28,975 | +40% | 1 | 1 | 0% | 3,235 | 5,714 | +77% | 0 | 0 | — |
case-19 | fail→fail | 17,584 | 7,836 | -55% | 1 | 1 | 0% | 3,056 | 1,793 | -41% | 0 | 0 | — |
case-20 | fail→pass | 10,455 | 1,870 | -82% | 1 | 1 | 0% | 1,658 | 1,586 | -4% | 0 | 0 | — |
case-21 | fail→pass | 12,199 | 1,947 | -84% | 1 | 1 | 0% | 1,842 | 1,603 | -13% | 0 | 0 | — |
case-22 | fail→pass | 4,014 | 2,513 | -37% | 1 | 1 | 0% | 544 | 1,736 | +219% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted, and 20 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +55 percentage points is the difference between those two pass rates over the 20 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.