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BD de-ai

自动扫描项目生成HTML检测报告，检测AI常用色、Emoji图标、英文报错暴露，支持一键替换为专业品牌风格。触发词：去掉AI味道、UI美化、专业化、统一配色、去除AI味、de-ai、品牌风格

ClawHub Agent Skills author: moan19921019-code v0.1.0 MIT-0 4 files body ≈ 3 806 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

自动扫描项目生成HTML检测报告，检测AI常用色、Emoji图标、英文报错暴露，支持一键替换为专业品牌风格。触发词：去掉AI味道、UI美化、专业化、统一配色、去除AI味、de-ai、品牌风格

As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureAI 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
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
Run on models
none yet
Process rating
D
49/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 0

✓ No critical or high findings

Files scanned: 4. 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 "homepage"

Process rating: all ten parameters 49/100

  • 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
  • 40Consistency. Frontmatter name (de-ai) differs from the folder (remove-ai-sence)
  • 100Tools and files. No external tools needed
  • 100Steps. 24 steps
  • 100Execution cost. Instruction body is 3806 tokens
  • 100Running it twice. No mutating operations
  • low The response is described with custom markup (16 tags): a typed call is more reliable

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 95: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -213 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 24 items
  • +4Has examples (7 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This skill performs disclosed local UI cleanup scans and edits, with no evidence of hidden data theft, persistence, or destructive behavior.
LLM: benign (high) · VirusTotal: · 6 Aug 2026