AF book-to-skill
【知识技能化】把技术书/PDF/白皮书/设计规范/运营手册蒸馏成可导入的 AI 技能（知识包）——不是 RAG 检索原文，而是把书里方法论内化为决策规则、模板、心智模型，让 AI 边干活边套用专业方法。适合：把《Clean Code》变代码审查 Skill、把品牌规范变审图 Skill、把投资问答录变投研 Skill。当用户说"把这本书变成 skill""把 PDF 转成技能""知识即服务"时使用。
【知识技能化】把技术书/PDF/白皮书/设计规范/运营手册蒸馏成可导入的 AI 技能（知识包）——不是 RAG 检索原文，而是把书里方法论内化为决策规则、模板、心智模型，让 AI 边干活边套用专业方法。适合：把《Clean Code》变代码审查 Skill、把品牌规范变审图 Skill、把投资问答录变投研…
As a process F 42/100 · Will not run — References files that are not bundled: references/<book>.md
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The text references files that are not there: add them or drop the references.
- 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: 7. 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") - warning
missing-refreference to a missing file: references/<book>.md - note
frontmatter-keyunknown frontmatter key "slug" - note
frontmatter-keyunknown frontmatter key "display_name" - note
frontmatter-keyunknown frontmatter key "displayName" - note
frontmatter-keyunknown frontmatter key "agent_created" - note
frontmatter-keyunknown frontmatter key "emoji"
Process rating: all ten parameters 42/100
- 0Tools and files. 1 referenced file(s) missing: references/<book>.md
- 0Result and completion. Does not say what the result is
- 0Failures and branches. Linear process with no failure handling
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 2 mutating operations with no state check
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 18 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 746 tokens
- 100Progress reporting. Reports progress
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)
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +5Description quotes 2 example trigger phrases
- +3Description length 201: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 18 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 2 scripts are documented
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.