SKILLEMALL.ai
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AC html-analysis

Analyze the structure and content of HTML documents using MinerU. Returns structured Markdown with layout information, headings, and content hierarchy preserved. Features: deep HTML content analysis. Preserves structural hierarchy and formatting. Identifies content sections, headings, tables, and lists. Full analysis mode with comprehensive output. Use when you need to: analyze HTML document structure, understand web page content layout, inspect HTML headings and sections, get a structural overview of an HTML file. Use when asked: 'how do I analyze this HTML', 'what is the structure of this web page', 'I want to understand this HTML layout', 'can my agent analyze HTML files', 'break down this HTML for me'. Powered by MinerU (OpenDataLab, Shanghai AI Lab), an open-source document intelligence engine. Ideal for web developers, SEO analysts, content auditors, and anyone who needs to understand HTML document structure.

ClawHub Agent Skills author: mzlzyCA v0.4.0 MIT-0 2 files body ≈ 407 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 51/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerInfrastructureMarketingAI 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
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
80
Run on models
none yet
Process rating
C
51/100
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

    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: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "homepage"

    Process rating: all ten parameters 51/100

    • 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
    • 100Tools and files. No external tools needed
    • 100Steps. 9 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 407 tokens

    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 928: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 9 items
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.

    External checks

    ClawHub: clean
    This is a coherent MinerU HTML analysis helper, with normal third-party service and token-handling cautions.
    LLM: benign (high) · VirusTotal: · 29 May 2026