SKILLEMALL.ai
GitHub ↗ RU Sign in

BC huo15-openclaw-design-critique

6 维度设计评审（美学 / 可用性 / 品牌一致 / 内容 / 技术实现 / 时代感）+ 审美档位识别（AI-Slop / Junior / Senior / Master 四档）+ 年代识别（命中过时视觉信号自动扣分）+ Master 级对标参考库（每流派 2-3 个真实标杆）+ Keep/Fix/Quick Wins 三分类 + 雷达图。用于对现成网页、HTML、截图、Figma 链接做专业打分与改进建议。触发词：设计评审、UI 审查、给这个页面打分、review 这个设计、这个界面怎么样、优化建议、审美档位、年代识别、Master 对标。

ClawHub Agent Skills author: Job Zhao v2.0.0 MIT-0 3 files body ≈ 1 867 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerFigmaDesignInfrastructuretype 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%
69
Run on models
none yet
Process rating
C
53/100
Has gaps
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: 3. 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 "displayName"
  • note frontmatter-key unknown frontmatter key "aliases"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. No external tools needed
  • 100Steps. 51 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1867 tokens
  • 100Running it twice. No mutating operations
  • low 11 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)
  • +3Output format is not stated: the model decides each time
  • -232 emoji in the instructions: noise for the model
  • +2Single-language instructions
  • +3Description length 275: enough signal without eating the budget
  • +4Structure: 19 headings
  • +3Step-by-step instructions: 51 items
  • +4Has examples (2 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: clean
This is a design-review prompt skill with broad trigger wording, but its behavior is disclosed, purpose-aligned, and does not install code or request privileged access.
LLM: benign (high) · VirusTotal: · 29 May 2026