playbook/antigravity-awesome-skills/skills/yao-meta-skill/references/governance.md

Governance Model

This project treats important skills as governed assets rather than one-shot prompt files.

Goals

• keep shared skills trustworthy over time
• make ownership explicit
• avoid stale or oversized skill packages
• define when a skill should evolve, split, or retire

Required Governance Metadata

For reusable or library-grade skills, manifest.json should include:

• name
• version
• owner
• updated_at
• review_cadence
• status
• maturity_tier
• lifecycle_stage

Allowed Values

status

• experimental
• active
• deprecated

maturity_tier

• scaffold
• production
• library
• governed

lifecycle_stage

• scaffold
• production
• library
• governed

review_cadence

• monthly
• quarterly
• semiannual
• annual
• per-release

Governance Rules

1. Owner Required

Any skill meant for reuse must have a named owner or owning team.

2. Review Cadence Required

If a skill is shared, it must declare how often it should be reviewed.

3. Maturity Should Match Rigor

• scaffold: lightweight, personal, low-governance
• production: reusable team skill with validation
• library: curated shared skill with explicit packaging and evals
• governed: critical or meta-level skill with regression, maintenance, and review expectations

4. Deprecated Skills Need Explicit Intent

Deprecated skills should include a deprecation note or replacement reference in adjacent documentation or manifest extensions.

5. Drift Must Be Observable

Important skills should keep:

• a regression history
• visible evaluation results
• known anti-patterns or failure modes

Governance Actions

Use governance review to decide whether a skill should:

• stay as-is
• tighten trigger boundaries
• split into sibling skills
• move detail into references/
• move brittle logic into scripts/
• be deprecated or replaced

Governance Maturity Scoring

scripts/governance_check.py also computes a maturity score out of 100.

Score Buckets

The governance checker computes a score band in addition to the declared manifest tier. The score band is a diagnostic output, not a replacement for the declared lifecycle tier.

• 90-100: governed
• 80-89: production
• 65-79: reusable
• 45-64: emerging
• <45: draft

Recommended Minimums For Declared Tiers

• scaffold: no hard minimum
• production: 80
• library: 85
• governed: 90

Score Dimensions

• metadata integrity
• ownership and review cadence
• boundary and eval evidence
• operational assets
• maintenance evidence

The score is not a replacement for human review. It is a fast signal that a shared skill is structured enough to be trusted, maintained, and audited. scripts/governance_check.py warns when a declared tier claims more rigor than the score currently supports.

Why This Matters

Most skill systems stop at creation. World-class skill systems also manage:

• ownership
• drift
• maturity
• deprecation
• evidence of ongoing quality