Practical Notes
- Quant: the README claims 18 source types and export to 20 platforms—start with 2 sources and 1 target until quality is stable.
- Quant: define a regression set of 5 docs URLs and compare output diffs after every version bump.
A team-friendly skill pipeline
A durable pipeline has three explicit stages:
- Ingest (what sources are allowed)
- Normalize (how to chunk, name, and scope)
- Package (how the target agent consumes skills)
How to avoid skill conflicts
- Keep a naming convention per domain (e.g.,
django/*,k8s/*). - Treat “global” skills as rare; prefer scoped skills.
- Review generated skills like code: diff, approve, version.
Operational tip
Run skill generation in CI for known sources so you notice docs changes early, not during an incident.
FAQ
Q: Should I generate skills from a whole repo at once? A: Start small: pick one subdir/module first so output quality is predictable.
Q: How do I keep skills up-to-date? A: Schedule regeneration and diff the results; pin versions for production use.
Q: What is the biggest risk? A: Conflicting instructions across skills—scope and naming discipline solves most issues.