# 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