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BD claude-clarity

用 Node.js 写的认知引擎，MCP 原生工具。 存在感知、三层持久记忆、 PAD 情绪分析、真善美评估。 不装人格，不抄模板，只有结构。单细胞。

ClawHub Agent Skills author: yun520-1 v1.1.5 MIT-0 80 files · 1 script body ≈ 7 514 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

用 Node.js 写的认知引擎，MCP 原生工具。 存在感知、三层持久记忆、 PAD 情绪分析、真善美评估。 不装人格，不抄模板，只有结构。单细胞。

As a process D 44/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI 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
76/100
safety, quality, tests
Safety 60%
94
Quality 40%
48
Run on models
none yet
Process rating
D
44/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
When it triggers w 12
20
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 SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
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 · 6

✓ No critical or high findings

Medium and low: 6
  • low Secrets in code secret-high-entropy-token package-lock.json:80
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…VHO+q2xB…AGd+Kl0mmq/MprG…MzA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:90
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…UFe+ony9…1jt+Gcn/FnGkNf8r+Vj5NOJWtQ==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:107
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…6ZJ+KBBf…ynt+Aj0x…71g==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:124
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…VHO+q2xB…AGd+Kl0mmq/MprG…MzA==",
    detector
  • low Secrets in code secret-high-entropy-token package-lock.json:196
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…55h/ff8EMaJ+cYhy…4pW+sXf9…fFg==",
    detector

A further 1 matches are quotations in this security skill's documentation and are not counted as findings.

Files scanned: 80. 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 body-long SKILL.md body ≈ 7514 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "title"

Process rating: all ten parameters 44/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 1 mutating operations with no state check
  • 40Consistency. Frontmatter name (claude-clarity) differs from the folder (claude-clarity-skill)
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 70Execution cost. Instruction body is 7514 tokens
  • 100Steps. 84 steps
  • 100Progress reporting. Reports progress
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 26 top-level sections: this looks like several domains in one skill

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)
  • +3Description length 75: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -4Absolute local paths (C:\Users, /home/…): not portable
  • -232 emoji in the instructions: noise for the model
  • -425 reference files, but SKILL.md never points to them: the model will not open them
  • +1No license
  • +2Single-language instructions
  • +4Structure: 70 headings
  • +3Step-by-step instructions: 84 items
  • +4Has examples (26 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 48.

External checks

ClawHub: suspicious
The skill presents itself as a cognitive engine, but its artifacts describe broader and under-disclosed behavior including background services, broad memory, external model fallback, and possible self-modifying workflows.
LLM: suspicious (medium) · 13 Jun 2026