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Yao meta skill

Skill sickn33/agentic-awesome-skills/skills/yao-meta-skill

Create, refactor, evaluate, and package agent skills from workflows, prompts, transcripts, docs, or notes. Use for skill creation, reusable workflow packaging, skill improvement, evals, and team-ready distribution.From its SKILL.md

Install
npx -y skills add sickn33/agentic-awesome-skills --skill yao-meta-skill

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

4.2 KB, 810 tokens by cl100k_base, as published. Nobody here has run it

Yao Meta Skill

When to Use

Use when this workflow matches the user request: Create, refactor, evaluate, and package agent skills from workflows, prompts, transcripts, docs, or notes. Use for skill creation, reusable workflow packaging, skill improvement, evals, and team-ready distribution.

Source: yaojingang/yao-meta-skill (MIT).

Router Rules

  • Route by frontmatter description.
  • Keep SKILL.md lean; put guidance in references/, logic in scripts/, and evidence in reports/.
  • Use the lightest reliable process.

Modes

  • Scaffold: exploratory/personal. Production: team reuse. Library: shared infrastructure. Governed: high-trust, policy-sensitive, or release-critical.
  • Rules: Method, Operating Modes, Resource Boundaries.

Compact Workflow

  1. For one-off/no reusable process: Do not create a skill; near-neighbor; require repeated use + reusable output contract.
  2. Capture job, output, exclusions, constraints, standards, and the lightest fit.
  3. Scan references in order: external benchmark, user source, local fit; surface only uncertainty or conflict.
  4. Write description early, test route quality, then add only earned folders and gates.
  5. Add output-risk, artifact-design, prompt-quality, system-model, and next directions only when useful.

Playbooks: Method, Intent, Skill IR, Output Eval, Review Studio.

Skill OS 2.0 Gates

For production, library, governed, or team-distributed work, run Skill IR, target compiler, trigger + output eval, Skill Atlas, conformance, trust, registry/package/install, upgrade, drift, waiver, and Review Studio gates before release.

Governed Package Boundary

For file-backed, release-critical, or governed packages, name input_files as file-backed fixture evidence; include owner, review cadence, input_files, output contract, rollback boundary; require trust report and reports/output_quality_scorecard.md; mark unavailable telemetry, approvals, metrics, or benchmarks as missing evidence; do not fabricate evidence.

Preserve audit labels literally when they apply: file-backed fixture, input_files, output contract, rollback boundary, trust report, reports/output_quality_scorecard.md, missing evidence.

First-Turn Style

  • Start from the user's work/outcome before structure.
  • Ask only 2-3 key questions unless enough detail exists.
  • In Chinese, sound soft and companion-like; use Intent Dialogue.

Output Contract

Unless asked otherwise, produce SKILL.md, aligned agents/interface.yaml, justified assets, and a short summary of boundary, exclusions, gates, and next steps.

Reference Map

Primary: Method, Artifact Design, Systems Thinking, Governance, SkillOps Decision.

Limitations

  • Requires the upstream tool, account, API key, or local setup when the workflow names one.
  • Does not authorize destructive, production, paid, or external-message actions without explicit user approval.
  • Validate generated artifacts or recommendations against the user's real sources before treating them as final.

What ships with it: 37 files

113.2 KB alongside SKILL.md

agents/

references/

Gives 0 of the 12 instructions most skill authoring skills give in 810 tokens

Counted across 408 of the 422 authors here whose files we hold, read 2026-09-06

  • Keep SKILL.md under 500 linesin 118 of 408, across 104 files
  • Write skill instructions in imperative formin 44 of 408, across 37 files
  • Move detailed reference material into references filesin 41 of 408, across 34 files
  • Run init_skill.py to initialize new skillsin 40 of 408, across 33 files
  • Draft assertions while test runs are in progressin 32 of 408, across 25 files
  • Keep description under 1024 charactersin 31 of 408, across 18 files
  • Run package_skill.py once the skill is completein 29 of 408, across 23 files
  • Spawn with-skill and baseline runs in the same turnin 28 of 408, across 21 files
  • Test added scripts by actually running themin 27 of 408, across 21 files
  • Follow the creation steps in orderin 24 of 408, across 17 files
  • Generate the eval viewer before evaluating outputs yourselfin 24 of 408, across 17 files
  • Write the description in third personin 24 of 408, across 18 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.