AC skill-factory
Turn any idea into a polished, versioned, publishable OpenClaw skill — no scaffolding, no guesswork. Just say "新 skill" or "build a skill" and Skill Factory handles the rest: captures the spec, collects sources, distills knowledge, and packages it into a GitHub-ready repo. Also supports upgrading existing skills with "升级 skill" or "upgrade skill". Built for makers who want quality without reinventing the process. Triggers: "新 skill", "做一个skill", "build a skill", "create skill", "skill制作", "把这个做成skill", "帮我把...打包成skill", "skill升级", "skill发行", "skill factory", "制造skill", "skill工厂", "skill from scratch", "我有个skill想法", "skill迭代", "skill打磨", "做一个关于...的skill", "skill版本管理", "skill如何发行", "skill如何升级", "skill生产", "skill自动化", "更新skill", "升级skill", "维护skill", "升级已有skill", "upgrade skill", "update skill", "维护现有skill", "skill版本升级", "skill生命周期".
As a process C 60/100 · Has gaps — weak spots: when it triggers, consistency, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 60/100
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 25 mutating operations with no state check
- 40Consistency. Frontmatter name (skill-factory) differs from the folder (skillfactory)
- 60Tools and files. Uses tools (web, git) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 60Failures and branches. 2 branches
- 70Inputs and preconditions. Inputs and preconditions are listed
- 85Steps. 70 steps, 2 vague phrases
- 100Execution cost. Instruction body is 3663 tokens
- 100Progress reporting. Reports progress
- low The response is described with custom markup (6 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 842: 120–800 characters recommended
- +2Single-language instructions
- +5Description quotes 35 example trigger phrases
- +4Structure: 30 headings
- +3Step-by-step instructions: 70 items
- +3Output format is stated explicitly
- +4Has examples (14 code blocks)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.