agentleFS
zerniezernie/vigiles/.claude/skills/audit-feedback-loop/SKILL.md

audit-feedback-loop

Skill15 starsChanged 5 months agoMITView on GitHub

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

The file

We split this skill into the rules it gives an agent

10 rules. About 0 are common, 3 are distinctive, and 7 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 7

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    No CI config, no linter rules, no CLAUDE.md.

    line 16
  2. Very specific:

    CI Configuration: Look for .github/workflows/, .circleci/, Jenkinsfile, .gitlab-ci.yml, bitbucket-pipelines.yml, .travis.yml, etc.

    line 31
  3. Distinctive:

    Custom Lint Rules: Look for custom plugins, rule directories, or inline rule definitions in linter configs

    line 39
  4. Distinctive:

    CLAUDE.md: Check if CLAUDE.md exists at the repo root

    line 44
  5. Very specific:

    CLAUDE.md Enforcement: Check if using vigiles v2 specs (CLAUDE.md.spec.ts exists) or v1 annotations (Enforced by: in CLAUDE.md).

    line 45
  6. Very specific:

    Type-Safe Specs: Check for CLAUDE.md.spec.ts or *.spec.ts files — indicates typed spec compilation via vigiles v2

    line 46
  7. Very specific:

    Generated Types: Check for .vigiles/generated.d.ts — indicates linter rules are type-checked at authoring time

    line 47
  8. Very specific:

    Screenshot/Visual Tests: Look for Playwright (playwright.config.*), Cypress (cypress.config.*), Chromatic, Percy, BackstopJS configs

    line 48
  9. Very specific:

    Observability: Search for imports/usage of @sentry/, dd-trace, @datadog/, newrelic, @opentelemetry/, sentry_sdk, structlog, tracing (Rust), …

    line 49
  10. Very specific:

    Scheduled Agent Tasks: Look for cron patterns in CI configs, .github/workflows/ with schedule: triggers, or references to scheduled Claude …

    line 50

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

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.