AC book-skill-generator
从书籍中提取核心方法论并生成对应的 skill。当用户提到"从《XXX》提取方法论"、"生成《XXX》的技能"、"把这本书的方法论变成 skill"或类似需求时使用此技能。适用于商业、管理、个人成长、技术等各类书籍的方法论提取和 skill 生成。
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- 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")
Process rating: all ten parameters 53/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Tools and files. No external tools needed
- 100Steps. 79 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1116 tokens
- 100Running it twice. No mutating operations
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
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 124: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 79 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.
External checks
ClawHub: clean
This skill is a disclosed book-methodology-to-skill generator, with expected file reading and artifact generation behavior that users should review before installing generated skills.
LLM: benign (high) · VirusTotal: · 29 May 2026