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BF 敏感词筛查-CMT-1.0

This skill should be used when the user wants to check files (PDF, Word, Excel) for sensitive/prohibited words from a word library, and highlight them in yellow. The skill has a built-in word library (65 words, 9 categories) and also supports external word files.

ClawHub Agent Skills author: betty831221 v3.0.0 MIT-0 4 files body ≈ 450 tokens Open the sourceclawhub.ai↗ analyzed 23 h ago

This skill should be used when the user wants to check files (PDF, Word, Excel) for sensitive/prohibited words from a word library, and highlight them in…

As a process F 37/100 · Will not run — References files that are not bundled: scripts/sensitive_word_checker.py

ProcedureWordSoftware developmentData and analyticstype 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
88/100
safety, quality, tests
Safety 60%
100
Quality 40%
71
Run on models
none yet
Process rating
F
37/100
Will not run
References files that are not bundled: scripts/sensitive_word_checker.py
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

The same skill appears in 1 more place: ClawHub

How to improve

  1. 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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning name-format name should be kebab-case (lowercase letters, digits, hyphens)
  • warning missing-ref reference to a missing file: scripts/sensitive_word_checker.py
  • note frontmatter-key unknown frontmatter key "agent_created"
  • note frontmatter-key unknown frontmatter key "disable"

Process rating: all ten parameters 37/100

Will not run. References files that are not bundled: scripts/sensitive_word_checker.py
  • 0Tools and files. 1 referenced file(s) missing: scripts/sensitive_word_checker.py
  • 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
  • 40Consistency. Frontmatter name (敏感词筛查-CMT-1.0) differs from the folder (sensitive-word-checker-cmt)
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 14 steps
  • 100Execution cost. Instruction body is 450 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 263: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 14 items
  • +4Has examples (3 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: clean
This skill locally checks user-chosen documents for sensitive words and saves highlighted copies, with no evidence of hidden network access, credential use, or destructive intent.
LLM: benign (high) · VirusTotal: · 1 Jul 2026