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BD prototype-design

通用页面原型设计技能。基于 58种设计风格（默认Figma 风格） UI 的复杂业务系统 HTML 原型开发， 包括标准页面结构、统计卡片、筛选条件、数据表格、弹窗设计。 适用场景：(1) 创建新的管理页面原型 (2) 对照业务文档实现功能模块 (3) 设计弹窗和详情页 (4) 构建带看板和列表视图的页面。 **样式选择**：内置58+设计系统，直接引用 `references/design-systems/` 目录。 使用时指定 DESIGN_SYSTEM=<名称> 即可应用对应设计风格。

ClawHub Agent Skills author: contsun v1.0.2 MIT-0 63 files body ≈ 6 870 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceFigmaInfrastructuretype 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%
99
Quality 40%
71
Run on models
none yet
Process rating
D
42/100
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. 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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Secrets in code secret-high-entropy-token references/design-systems/hashicorp-DESIGN.md:66
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    - **Primary Brand**: `__ha…0ca` (HashiCorp Sans), with fallback: `__ha…0ca`
    quoted

Files scanned: 63. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning body-long SKILL.md body ≈ 6870 tokens (recommended < 5000); move details to references/
  • note frontmatter-key unknown frontmatter key "origin"
  • note frontmatter-key unknown frontmatter key "last_updated"
  • note frontmatter-key unknown frontmatter key "changelog"

Process rating: all ten parameters 42/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Execution cost. Instruction body is 6870 tokens
  • 100Steps. 84 steps
  • 100Consistency. Name and required fields are in place
  • low 18 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (4 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)
  • +3Output format is not stated: the model decides each time
  • -2localhost URLs: will not work for another user
  • -214 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 249: enough signal without eating the budget
  • +4Structure: 64 headings
  • +3Step-by-step instructions: 84 items
  • +4Has examples (37 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)

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

External checks

ClawHub: suspicious
This prototype-design skill is mostly coherent, but it includes under-scoped persistence, repository commits, local tool execution, and unrelated capability tags that users should review before installing.
LLM: suspicious (high) · VirusTotal: · 29 May 2026