/qiaomu-meta-skill

name: qiaomu-meta-skill
description: |
  Research, create, improve, migrate, evaluate, package, install-check, govern, and safely publish qiaomu-flavored agent skills from workflows, prompts, transcripts, docs, SOPs, runbooks, scripts, or notes. Use for new or existing skills, prior-art synthesis, routing/trigger boundaries, trigger or output evals, Skill IR, release gates, README/Profile preparation, GitHub repository and pull-request publication, versioned Releases, clean npx installation, team reuse, and create-and-publish flows. The publication path is self-contained and forbids direct default-branch pushes. Exclude one-off summaries, translations, ordinary docs, non-skill package publishing, and tasks that explicitly should not become a skill.
metadata:
  author: Qiaomu
  version: "2.12.0"
  upstream_inspiration: yaojingang/yao-meta-skill; joeseesun/qiaomu-skill-publisher

Qiaomu Meta Skill

Build reusable Qiaomu skill packages, not long prompts.

Router Rules

• Route by frontmatter `description` first.
• Once selected, `qiaomu-meta-skill` is the single authoring authority. Do not also invoke a generic `skill-creator` unless the user explicitly requests comparison or this skill is unavailable.
• Built-in prior-art discovery belongs to this skill. Do not install, load, or delegate to a separate discovery skill.
• Built-in GitHub publishing belongs to this skill. Do not require or invoke a separate publisher skill after this package is selected.
• Keep the package root `SKILL.md` to routing and the minimal workflow. Put judgment in `references/`, deterministic behavior in `scripts/`, regression cases in `evals/`, and evidence in `reports/`.
• A package has one discoverable root `SKILL.md`; embedded examples and fixtures use `SKILL.example.md` or `SKILL.fixture.md`.
• Do not turn one-off summaries, translations, explanations, or brainstorming into skills.
• Match the user's action: create/refactor/package requests may edit; audit/evaluate/diagnose-only requests remain read-only; publish only when explicitly requested.
• Default to concise Chinese-first `qiaomu-` names with no more than three preferred hyphen parts.
• Add `Copyright (c) 向阳乔木`, X `https://x.com/vista8`, and GitHub `https://github.com/joeseesun/` unless another owner is requested.

Modes

• `Scaffold`: exploratory or personal; minimum useful files.
• `Production`: team reuse; README, interface, trigger eval, output contract, and install evidence.
• `Library`: shared infrastructure; Production plus Skill IR, portability, trust, and review cadence.
• `Governed`: public or high-trust; Library plus permission, rollback, secret, release, and claim gates.

Choose proportionally with [Operating Modes](references/operating-modes.md), [Gate Selection](references/gate-selection.md), and [QA Ladder](references/qa-ladder.md).

Built-In Prior-Art Discovery

Before a new skill or substantial redesign:

1. Derive 2–4 intent-shaped queries covering outcome, domain action, quality mechanism, and an adjacent synonym when useful. 2. Prefer the unified runner:

python3 scripts/research_prior_art.py "<query 1>" "<query 2>" --strict --summary --output reports/prior-art-candidates.json

Its underlying catalog calls remain:

npx --yes skills find "<query>"
python3 scripts/search_skillsmp.py "<query>" --limit 20 --sort stars

3. Keep metrics separate: skills.sh installs measure adoption; SkillsMP stars belong to the source repository; neither is a user rating or quality score. 4. Deduplicate by canonical GitHub repository and skill path. Collapse translations, mirrors, and obvious forks without adding metrics together. 5. Shortlist genuinely relevant popularity, trust, and complementary anchors. Inspect source `SKILL.md`, maintenance, license, permissions, security signals, and available rating evidence; never execute untrusted candidate code just to study it. 6. Synthesize `keep / adapt / reject / invent`. Map each adopted mechanism to the new package instead of collaging prose. 7. Preserve dated sources, metrics, failures, deduplication, lessons, rejections, and missing evidence in `reports/prior-art-research.md` for Production+ or materially researched work.

If a catalog fails, continue with the other sources, record `missing evidence`, and lower the claim. Full method: [Prior-Art Research](references/prior-art-research.md).

Generalization Gate

Before promoting one failure into a core rule:

1. restate it as a domain-neutral behavior 2. classify it as core mechanism, optional adapter, or eval-only fixture 3. promote only safety/factual/permission invariants or behavior repeated across unrelated domains 4. keep one-off details in fixtures or specialist references 5. rerun the original and unrelated boundary cases

Prefer intent fidelity, source fidelity, and decision rules over an expanding topic encyclopedia.

Qiaomu Skill OS

1. `Intent`: recurring job, users, inputs, output, exclusions, standards, references. 2. `Skill IR`: platform-neutral meaning and evidence boundary. 3. `Package`: lean root instructions, interface, README, and earned resources. 4. `Eval`: trigger boundaries first; output/runtime/human eval when risk justifies it. 5. `Review`: package, context, trust, install, README, and public claims. 6. `Operate`: explicit feedback, failures, drift, and next-iteration proposals without raw private content.

Compact Workflow

1. Decide whether the request deserves a reusable skill; otherwise answer directly and create no package. 2. Capture job, finished output, target users, inputs, exclusions, permissions, standards, existing assets, platforms, and publication intent. 3. Pass prior-art discovery or record why it is not applicable or missing evidence. 4. Pass the generalization gate for sample-driven core changes. 5. Choose the lightest valid mode. 6. Write the `description` early (quote it or use `description: |` when it contains `: `, e.g. `Excludes:`); run `evals/trigger_cases.