Skill Forge
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Please follow https://skillhub.cn/install/skillhub.md and install @user_164f4c1f/cjg-skill-forge.
About this skill
Problem
Agent skills often stall between a rough v1 and a releasable state: descriptions are too vague, triggers are unstable, scripts only “seem to work” in the author’s environment, skill libraries grow overlapping, and post-release feedback is hard to act on. cjg-skill-forge turns these problems into an engineering process, using real calls, evidence artifacts, and validation outputs instead of vague optimization advice.
How It Works
- Forge mode: follows a
S0–S8pipeline covering scaffolding, real wiring, runtime evidence, external benchmarking, coverage audit, production sign-off, validation, packaging, clarity, and discoverability metadata. - Review mode: audits a skill against D1–D10 dimensions before release, surfaces anti-patterns, and produces a checkable report.
- Recast mode: scans existing skills for overlap and consolidates similar items so the library does not keep fragmenting.
- Clarity mode: rewrites skill content into a structure that AI can parse more reliably, with a fidelity guard to preserve intended behavior.
It has clear limits: it does not make creative decisions, choose version numbers, or publish automatically; if a path has not been runtime-tested, it should be marked as non-runtime-tested rather than invented.
Use Cases
- When creating a new skill, run the forge pipeline to add scaffolding, real wiring, runtime evidence, and release checks.
- Before release, audit a skill against ten dimensions to catch weak triggers, missing commands, and coverage gaps.
- When a skill library has duplicates, scan overlap, confirm consolidation, and tidy reusable documentation.
- When vague docs confuse the model, rewrite the skill into a clearer structure while preserving intended behavior.
Best For
- Agent skill-maintenance engineers who need to consolidate similar skills into a stable, maintainable structure.
- Developers accountable for release quality who need to audit triggers, command syntax, and coverage gaps before launch.
- Product engineers writing skill docs who want vague descriptions rewritten into clear, model-parseable structure.
- Owners managing multi-version Agent skills who need to track usage signals and locate modules that need recasting.
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