3.0 KiB

Raw Permalink Blame History

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

3.0 KiB Raw Permalink Blame History