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BD html-visual-editor

把任意静态 HTML 转成可视化编辑版：注入可拖动工具栏、颜色/字号/布局/风格面板、就地文字编辑、撤销保存导出干净版、元素与面板双向跳转、中英文 i18n、6 套场景风格 Prompt 一键复制给 AI 重塑样式。颜色面板数据驱动：扫 DOM 文字字符数 top 5 + 背景元素数 top 4 + 边框元素数 top 3，跨主题通用。适用于用户说可编辑版HTML、html可视化编辑、让html可编辑、样式面板、改html不写代码、所见即所得、点击直接编辑、把报告/页面/演示稿变成可调样式、给 AI 复制风格提示词。

ClawHub Agent Skills author: ytisvibecoding v1.8.4 MIT-0 17 files body ≈ 1 056 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureInfrastructureAI 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%
95
Quality 40%
74
Run on models
none yet
Process rating
D
41/100
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 · 5

✓ No critical or high findings

Medium and low: 5
  • low Secrets in code secret-high-entropy-token scripts/verify.py:351
    High-entropy token-like string (may be an id, hash or a credential)
    def chec…mat(html: str, constants: dict) -> CheckItem:
  • low Secrets in code secret-high-entropy-token scripts/verify.py:384
    High-entropy token-like string (may be an id, hash or a credential)
    def chec…nel(html: str, constants: dict) -> CheckItem:
  • low Secrets in code secret-high-entropy-token scripts/verify.py:450
    High-entropy token-like string (may be an id, hash or a credential)
    def chec…ure(html: str, constants: dict) -> CheckItem:
  • low Secrets in code secret-high-entropy-token scripts/verify.py:463
    High-entropy token-like string (may be an id, hash or a credential)
    def chec…tch(html: str, constants: dict) -> CheckItem:
  • low Secrets in code secret-high-entropy-token scripts/verify.py:498
    High-entropy token-like string (may be an id, hash or a credential)
    def chec…mat(html: str, constants: dict) -> CheckItem:

Files scanned: 17. 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 "agent_created"

Process rating: all ten parameters 41/100

  • 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 (html-visual-editor) differs from the folder (html-editor)
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 33 steps
  • 100Execution cost. Instruction body is 1056 tokens
  • 100Running it twice. No mutating operations
  • low 10 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 261: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (6 code blocks)
  • +3All 6 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: clean
The skill coherently creates editable copies of static HTML, with disclosed file changes and optional LLM label generation, but users should be aware cloud calls can occur when API keys are present.
LLM: benign (high) · VirusTotal: · 23 Jul 2026