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在 AI 生成的 HTML 网页上做可视化标注，把"点元素 + 写评论"的反馈通过本地 server + UserPromptSubmit hook 自动喂回模型，无需复制粘贴。当用户说"标注网页"、"给这个 HTML 加批注"、"/annotate"、或希望对生成的网页提具体元素修改意见时触发。

ClawHub Agent Skills author: Times77 v1.0.0 MIT-0 15 files · 4 scripts body ≈ 607 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ReferenceInfrastructuretype 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
A
90/100
safety, quality, tests
Safety 60%
99
Quality 40%
77
Run on models
none yet
Process rating
D
43/100
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Dangerous commands cmd-background-process injector.sh:65
    Starts a background / autostarted process
    nohup python3 "$SERVER_PY" "$RL_PORT" > "$LOGFILE" 2>&1 &

Files scanned: 9. 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")

Process rating: all ten parameters 43/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (redline) differs from the folder (redline-annotate)
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 32 steps
  • 100Execution cost. Instruction body is 607 tokens
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress

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

  • +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
  • +5Description quotes 3 example trigger phrases
  • +3Description length 149: enough signal without eating the budget
  • +4Structure: 8 headings
  • +3Step-by-step instructions: 32 items
  • +4Has examples (2 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: suspicious
This is a useful local HTML annotation skill, but it installs persistent prompt hooks and exposes under-scoped local and browser execution paths that users should review before installing.
LLM: suspicious (high) · 28 May 2026