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BC cognitive-bias-advisor

认知偏差顾问。覆盖决策、学习、行动、沟通、影响、管理六大人生领域，基于查理·芒格"25类人类误判心理学"+经典认知偏差理论。六大领域并列，根据用户问题路由到对应领域文件执行诊断与策略输出。触发词：决策、学习、拖延、说服、谈判、影响别人、管理团队、带人等。

ClawHub Agent Skills author: jacksu v2.1.3 MIT-0 32 files body ≈ 1 318 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

认知偏差顾问。覆盖决策、学习、行动、沟通、影响、管理六大人生领域，基于查理·芒格"25类人类误判心理学"+经典认知偏差理论。六大领域并列，根据用户问题路由到对应领域文件执行诊断与策略输出。触发词：决策、学习、拖延、说服、谈判、影响别人、管理团队、带人等。

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware developmentAI and agentstype 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
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
72
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: cognitive-bias-advisor (ClawHub)

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 · 0

✓ No critical or high findings

Files scanned: 32. 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")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"

Process rating: all ten parameters 54/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (cognitive-bias-advisor) differs from the folder (cognitive-bias-adivsor)
  • 50Failures and branches. 0 branches, has a failure section
  • 100Tools and files. No external tools needed
  • 100Steps. 11 steps
  • 100Execution cost. Instruction body is 1318 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
  • -225 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 127: enough signal without eating the budget
  • +4Structure: 18 headings
  • +3Step-by-step instructions: 11 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (10 of 20)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 72.

External checks

ClawHub: clean
This is a Chinese cognitive-bias coaching skill with broad conversational triggers and persuasion advice, but its behavior is disclosed, text-only, and does not request credentials, tool authority, persistence, or hidden execution.
LLM: benign (high) · VirusTotal: · 10 Jul 2026