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伏羲.skill - 专家级认知操作系统生成器。 用于自动化生成特定人物的「正面专家级认知操作系统」Skill。 当用户要求「提炼一个XXX的精华」「帮我创建一个XXX的商业版Skill」「蒸馏XXX的最优一面」时触发。 通过网络调研（主）与用户素材（辅），采用「六爻画卦」方法论， 仅从互联网公开资料中搜集和提炼，将人物最有价值的思想提炼为可供大众直接使用的专家级思维框架。 生成的 Skill 以目标人物视角回应，开头声明不是本人，每次回答后附局限性总结和免责声明。

ClawHub Agent Skills author: yewubin-jpg v0.1.1 MIT-0 5 files body ≈ 533 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process F 35/100 · Will not run — References files that are not bundled: references/research/, examples/demo-conversation.md

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: references/research/, examples/demo-conversation.md
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 5. 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")
  • warning missing-ref reference to a missing file: references/research/
  • warning missing-ref reference to a missing file: examples/demo-conversation.md

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: references/research/, examples/demo-conversation.md
  • 0Tools and files. 2 referenced file(s) missing: references/research/, examples/demo-conversation.md
  • 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
  • 100Steps. 19 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 533 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • +4No input/output examples
  • +2Single-language instructions
  • +3Description length 235: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 19 items
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This is an instruction-only skill that openly generates positive, persona-style skill packages from public research, with bias and privacy caveats but no hidden code, credential use, or destructive behavior found.
LLM: benign (high) · VirusTotal: · 29 May 2026