agentleFS
rikvanrielrikvanriel/code-hygiene/skills/catalog/SKILL.md

catalog

Skill2 starsChanged 56 days agoMITView on GitHub

Use when starting work in an unfamiliar repo, setting up hygiene skills, or unsure which skills a task needs. Recommends and installs a subset.

5 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

4 rules. 0 are common, 3 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use when user says "set up hygiene", "make my AI write better PRs", "what skills exist?", or wants onboarding.

    line 16
  2. Distinctive:

    Ask 2-3 discovery Qs (clarify choices array, never embed options inside question text):

    line 26
  3. Very specific:

    Always unless personal repo only: upstream-hygiene + factual-integrity CLI/library: + comment-quality + code-structure + changelog-quality …

    line 35
  4. Distinctive:

    No auto-install ever — confirmation gate.

    line 51

“Common” is measured: kept by at least 6 in 10 of the 5 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.

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

Catalog — What's Available + Install

Use when user says "set up hygiene", "make my AI write better PRs", "what skills exist?", or wants onboarding.

What this skill does

  1. Load inventory:
    • skills/ dirs — read frontmatter description + first para — positive framing, what skill provides not what isn't.
    • references/index.md — cliff notes on external repos/tools (10 entries v0.2).
    • references/generic-principles.md summary.
    • AGENTS.md canonical + CLAUDE.md shim note per ADR 0001.
  2. Ask 2-3 discovery Qs (clarify choices array, never embed options inside question text):

    • What type of project: library, CLI tool, web service, docs, kernel/module?
    • Where does code ship: personal repo only, OSS fork/PR, company monorepo, mail list patch series?
    • Subject spec: does project already have conventional commits / commitlint / own subject style per CONTRIBUTING? — decides between conventional-commits reference vs changelog-quality GC-10.
    • Agent home where you want install: ~/.claude/skills, ~/.hermes/skills, ~/.agents/skills (Claw), ~/.openclaw/skills, ~/.config/opencode/skills, AGENTS.md generic, .cursor/rules, .github/copilot-instructions.md?
  3. Recommend 5-7 core + 2-3 references based on answers:

    Always unless personal repo only: upstream-hygiene + factual-integrity CLI/library: + comment-quality + code-structure + changelog-quality + change-splitting Ambiguous task incoming: + socratic-spec + plan-iteration-gate + systematic-debugging PRs to OSS: + project-discovery + pre-commit-check Pre-commit self-check: self-review-gate 4Q (a) wrong (b) better way (c) missing (d) boundaries + llm-tells New language/project with sparse style: + language-style-sampling + ref google-eng-practices Conventional commits detected: ref conventional-commits + lint-chain Stacked PR workflow: ref stacked-pr + core change-splitting

  4. Present as checklist with one-sentence TL;DR per skill (cite source file path, not memory) + positive capability. Then offer install.
  5. Install gate:

    • List: scripts/install.sh --list — probes agent homes.
    • Install: scripts/install.sh --install <comma-list> — requires explicit yes.
    • Generic agent: append cat skills/<name>/SKILL.md snippet + reference link into AGENTS.md with provenance comment <!-- from code-hygiene skills/<name> -->.
    • No auto-install ever — confirmation gate.

Output format

## Available — core (shipped, 15 skills v0.2)
- upstream-hygiene — public-only commits/comments class-based ban placeholder-only
- factual-integrity — never invent...
- change-splitting — one logical change per commit, 200-line seam trigger...
- systematic-debugging — 4-phase root cause...
...

## Available — references (cliff notes, not vendored, 10 entries)
- google-eng-practices — small CLs, WHY, reviewer quality
- conventional-commits — type(scope): subject spec + commitlint
- stacked-pr — ghstack/jj/git-branchless
...

## Recommended for your project (5-7 core + 2-3 refs)
- [ ] upstream-hygiene — ...
- [ ] ...
Invoke: ./scripts/install.sh --install <list>

Verification — 4Q

(a) Wrong? Does catalog list skill that doesn't exist on disk, invents description, or violates upstream-hygiene placeholder-only? (b) Better way? Existing generic mechanism — project already has AGENTS.md with rules — reuse and extend not duplicate? State if none beats with tradeoff. (c) Missing? Rollback plan if install overwrites existing AGENTS.md, observability per install step (file exists + content hash), failure notification if skill dir not writable, what unblocks downstream (PR creation), what stays out of scope (full language lint config). (d) Boundaries explicit? Which skills core vs reference cliff notes not vendored, dep version pinned, which checks org-specific private overlay ~/.config/hygiene/extra-check.sh, scope positive: "provides installable skills + probe + confirmation, not auto-install".

Anti-patterns

  • Listing everything without recommendation — choice paralysis defeats purpose.
  • Auto-installing without asking — never.
  • Defining by negation "kernel-free" in description — positive capability per positive framing rule.
  • Installing references as vendored code — only cliff notes + link, user opts in.

Related

  • project-discovery Step0 finds upstream CONTRIBUTING that bounds recommendation.
  • upstream-hygiene owns banned classes — verification gate uses its check-hygiene.sh.
  • self-review-gate 4Q own recommendation before presenting.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
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.