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Scaffold a new brooks-lint analysis skill so it passes `npm run validate` and `npm run evals` on the first try — generates skills/{name}/SKILL.md (with the mandatory "Do NOT trigger for:" clause and a Process section citing guide step ranges) plus skills/{name}/{name}-guide.md

From plugin
brooks-lint
1.5k9 skills5 agents6 commands1 hook
Install
$ npx -y skills add hyhmrright/brooks-lint --skill new-skill --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/new-skill

Context preview

The summary Claude sees to decide when to auto-load this skill.

Scaffold a new brooks-lint analysis skill so it passes `npm run validate` and `npm run evals` on the first try — generates skills/{name}/SKILL.md (with the mandatory "Do NOT trigger for:" clause and a Process section citing guide step ranges) plus skills/{name}/{name}-guide.md

SKILL.md

new-skill.SKILL.md
name: new-skill
description: >
  Scaffold a new brooks-lint analysis skill so it passes `npm run validate` and
  `npm run evals` on the first try — generates skills/{name}/SKILL.md (with the
  mandatory "Do NOT trigger for:" clause and a Process section citing guide step
  ranges) plus skills/{name}/{name}-guide.md (sequentially numbered steps), then
  appends paired eval scenarios.
  Triggers when the maintainer asks to "add a new skill", "scaffold a skill", or
  "create a brooks-lint mode".
  Do NOT trigger for: editing an existing skill's content, adding a single eval to
  an existing skill, or authoring skills for some other plugin.
disable-model-invocation: true

brooks-lint — New Skill Scaffold

Skill name comes from `$ARGUMENTS` (kebab-case, e.g. `brooks-security`). If empty, ask for the name and a one-line purpose first.

Follow the repo's "Adding a New Skill" checklist exactly:

1. **Create `skills/{name}/SKILL.md`** with frontmatter — `name`, a `description` that ends with a `Do NOT trigger for:` clause (validate-enforced for shipped skills; omitting it causes false triggering), and a `Process` section of 3–6 bullets that cite the guide's step ranges inline (e.g. `Scan risks (Steps 1–6 of the guide)`). Mirror the structure of an existing skill such as `skills/brooks-review/SKILL.md` (Setup → Process → Mode line). 2. **Create `skills/{name}/{name}-guide.md`** with sequentially numbered steps — no gaps, no duplicates. Sub-steps like `Step 2a` are allowed. The guide owns the detailed steps; the SKILL.md Process is just an orientation skeleton. 3. **Wire the framework.** The new SKILL.md Setup section must Read the relevant `_shared/` files (`common.md` for Iron Law + Report Template, plus `decay-risks.md` / `test-decay-risks.md` as applicable) — `_shared/` is NOT auto-loaded. 4. **Add eval coverage** to `evals/evals.json`: append with the next sequential `id` at least one happy-path scenario (with the relevant risk code in `expected_output`) and at least one false-positive scenario flagged `no_risk_codes: true`. Each scenario needs `id`, `name`, `prompt`, `expected_output`, `mode`, `files`. 5. **Validate.** `npm run validate` (structure + step continuity + Process-section presence) and `npm run evals` (eval schema). Fix until both pass. 6. **Local-test.** `cp -r skills/* ~/.claude/skills/brooks-lint/` (if you've symlinked `~/.claude/skills/brooks-lint` to the repo, skip this — edits are already live), trigger the new skill in a Claude session, verify the Iron Law output, then restore the marketplace copy: `/plugin marketplace update` → `/plugin install brooks-lint@brooks-lint-marketplace`.

Do NOT register a slash command by hand — short forms are auto-installed by the session-start hook. Report the files created and the validate/evals results.

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AI code reviews grounded in 12 classic engineering books — decay risk diagnostics with book citations, severity labels, and 6 analysis modes including full-sweep auto-fix

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