audit-feedback-loop

Imported from zernie/vigiles (.claude/skills/audit-feedback-loop/SKILL.md) via skills.sh. Install upstream with npx skills add zernie/vigiles --skill audit-feedback-loop. Copyright stays with the author.

Scan the current repository and score its feedback loop maturity for AI-assisted development.

Instructions

Analyze this repository and score its feedback loop maturity using the levels below. Check for each signal, then output a summary report.

Maturity Levels

Level 0 — Vibes No CI config, no linter rules, no CLAUDE.md. The AI agent is flying blind.

Level 1 — Guardrails Has CI + standard linters, but no custom rules. The agent gets basic feedback but can't learn project-specific conventions.

Level 2 — Architecture as Code Has custom lint rules, CLAUDE.md rules have enforcement annotations. The agent gets rich, project-specific feedback.

Level 3 — The Organism Has CI + custom rules + screenshot/visual tests + observability + scheduled agent tasks. The entire development loop is instrumented.

Signals to Check

Scan the repository for the following and note which exist:

1. CI Configuration: Look for .github/workflows/, .circleci/, Jenkinsfile, .gitlab-ci.yml, bitbucket-pipelines.yml, .travis.yml, etc.
2. Linter Config (language-aware):
   • JS/TS: eslint.config.*, .eslintrc*, biome.json, .prettierrc*, deno.json
   • Python: pyproject.toml (look for [tool.ruff], [tool.pylint], [tool.flake8]), setup.cfg, .flake8, ruff.toml
   • Rust: clippy.toml, .clippy.toml, rustfmt.toml
   • Go: .golangci.yml, .golangci.yaml
   • Ruby: .rubocop.yml
   • Java/Kotlin: checkstyle.xml, pmd.xml, detekt.yml
3. Custom Lint Rules: Look for custom plugins, rule directories, or inline rule definitions in linter configs
   • JS/TS: eslint-plugin-*, eslint-rules/ directories
   • Python: custom Ruff/Pylint plugins, AST-based checks
   • Rust: custom Clippy lints
   • Go: custom analyzers
4. CLAUDE.md: Check if CLAUDE.md exists at the repo root
5. CLAUDE.md Enforcement: Check if using vigiles v2 specs (CLAUDE.md.spec.ts exists) or v1 annotations (**Enforced by:** in CLAUDE.md). v2 specs = higher maturity.
6. Type-Safe Specs: Check for CLAUDE.md.spec.ts or *.spec.ts files — indicates typed spec compilation via vigiles v2
7. Generated Types: Check for .vigiles/generated.d.ts — indicates linter rules are type-checked at authoring time
8. Screenshot/Visual Tests: Look for Playwright (playwright.config.*), Cypress (cypress.config.*), Chromatic, Percy, BackstopJS configs
9. Observability: Search for imports/usage of @sentry/, dd-trace, @datadog/, newrelic, @opentelemetry/, sentry_sdk, structlog, tracing (Rust), opentelemetry in source files
10. Scheduled Agent Tasks: Look for cron patterns in CI configs, .github/workflows/ with schedule: triggers, or references to scheduled Claude Code tasks

Output Format

## Feedback Loop Audit

**Repository:** <repo name>
**Primary language(s):** <detected languages>
**Score: Level X — <Name>**

### Signals Found
- [x] CI Configuration: <details>
- [ ] Custom Lint Rules: not found
- [x] CLAUDE.md: found, 5 enforced / 2 guidance / 1 missing
...

### Recommendations
1. <Most impactful next step to level up>
2. <Second recommendation>
3. <Third recommendation>

### How to Level Up
<Specific, actionable advice for reaching the next maturity level>

Be specific about file paths and what you found. Give actionable recommendations tailored to the project's language and toolchain.