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BC distill-concept-books

将概念、理论或分析方法类图书蒸馏为证据可追溯、经人工门禁审核且不暴露书名、作者、出版社等来源身份的任务型 Skill 候选。用于新建或恢复图书蒸馏、以本地 Tesseract 扫描 DOCX 全部内嵌图像或 Poppler 渲染的扫描 PDF 全页、建立 source map 与 evidence/claim/relation/capability rule、用第一性原理重构可迁移方法，以及按权威 task contract 防止上下文压缩后的产品任务漂移；仅在本元 Skill 自身的 owning distillation 中路由其 Gate 4 评测。不用于单纯摘要、事实问答、人物思维模仿、实验或临床 SOP、临床决策，也不作为其他 Skill 的通用物化、评测、Git、发布或部署工具。

xuzhougeng/wisp-science Agent Skills author: xuzhougeng AGPL-3.0 47 files · 16 scripts body ≈ 2 173 tokens Open the sourcegithub.com↗ analyzed 7 d ago

将概念、理论或分析方法类图书蒸馏为证据可追溯、经人工门禁审核且不暴露书名、作者、出版社等来源身份的任务型 Skill 候选。用于新建或恢复图书蒸馏、以本地 Tesseract 扫描 DOCX 全部内嵌图像或 Poppler 渲染的扫描 PDF 全页、建立 source map 与…

As a process C 56/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureWordSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
99
Quality 40%
76
Run on models
none yet
Process rating
C
56/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

  1. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Obfuscation obf-base64-blob scripts/test_normalize_docx_source.py:18
    Long base64-looking blob (test fixture / example file; quoted — discussed, not commanded)
    "iVBO…mNk+A8AA…YII="
    fixturequoted

Files scanned: 45. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 56/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 40Result and completion. Does not say what the result is
  • 100Tools and files. No external tools needed
  • 100Steps. 50 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2173 tokens

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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • -314 of 16 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 350: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 50 items
  • +3Output format is stated explicitly
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (10 of 10)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.