skill-infrastructure
Installation
SKILL.md
Skill Infrastructure
Coverage
- The library-as-database mental model: skill-infrastructure as the linter, integrity checker, and query planner for a SKILL.md library
- Why deterministic, zero-LLM tooling is mandatory for skill libraries (trustworthy enough for CI gates; LLM-based health checks are circular)
- The five categories of skill-health tooling: (1) inventory and frontmatter validation, (2) protocol consistency, (3) conflict detection (overlap, imperative, code duplication, heading overlap), (4) routing health (gap analysis, miss tracking), (5) drift detection (truth-source hashing, mirror parity)
- Eval quality patterns: minimum eval threshold per skill, the contradiction-check eval type, the negative-expectation requirement, valid eval-type taxonomy
- Imperative conflict detection: the same-target-opposite-polarity rule, three-check false-positive suppression, when conflicts indicate scope-tightening vs merging
- Routing gap analysis: how to read a "routing-misses" log, how to distinguish keyword gaps from skill content gaps, signal-hygiene rules to suppress noise
- Maintenance workflows: when to run a full health check, the order in which to run the categories, what to fix before what
- Anti-patterns that cause invisible decay: dirty-tree manifest writes, deletion-as-conflict-resolution, eval-renumbering during cleanup, scope misuse to mask threshold violations
- The verification gate before any batch skill commit: every category clean, every new skill meets eval minimums, every routing change is reflected in the manifest
- Package and workspace-root integrity: the npm CLI entrypoint must dispatch to the same scripts as local development while resolving schemas from the package and skills/manifests from the caller workspace
Philosophy
A skill library is only as useful as its worst skill. When agents load stale, conflicting, poorly-routed, or mirror-drifted skills, they get worse at tasks — not better. A skill library at scale (50+, certainly 200+) decays invisibly: eval counts drift below minimums, keyword maps miss whole product areas, mirror copies fall out of sync, and two skills start giving opposite instructions for the same function.