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BB datalens

Use DataLens MCP tools to scrape structured data from any website open in Chrome. Triggers when the user wants to extract lists, tables, comments, products, reviews, or any repeating data from a webpage, or wants to manage active scraping jobs.

ClawHub Agent Skills author: weird94 v1.0.0 MIT-0 2 files body ≈ 1 731 tokens Open the sourceclawhub.ai↗ analyzed 13 d ago

Use DataLens MCP tools to scrape structured data from any website open in Chrome.

As a process B 66/100 · Nearly there — weak spots: result and completion, consistency

ProcedureAI and agentsSoftware developmenttype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
66/100
Nearly there
Result and completion w 14
0
Consistency w 8
40
Failures and branches w 10
50
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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 66/100

    • 0Result and completion. Does not say what the result is
    • 40Consistency. Frontmatter name (datalens) differs from the folder (datalens-web-scraper)
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash, web, node) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 13 steps
    • 100When it triggers. States when to use and when not to
    • 100Execution cost. Instruction body is 1731 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

    • +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 244: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 13 items
    • +4Has examples (17 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    The skill is a legitimate web-scraping helper, but it can process authenticated browser pages, call a backend AI, run unpinned npm tooling, and save scraped data locally without enough user-facing guardrails.
    LLM: suspicious (high) · VirusTotal: · 16 Sept 2026