SKILLEMALL.ai

AC playwright-browser

Use Playwright to browse websites with a real (non-headless) browser and extract data by hooking network responses. Use when the user wants to: - View a website's content, especially SPAs (Single Page Applications) - Navigate websites and click links - Search for keywords within web pages - Extract data from JavaScript-heavy sites - Capture API responses directly Triggers on: "查看网页", "browse site", "get content from URL", "extract data from website", "hook API responses", "抓取网页内容", "find link", "click link", "search page"

ClawHub Agent Skills author: elijahxb v1.0.0 MIT-0 8 files body ≈ 561 tokens Open the sourceclawhub.ai analyzed 2 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, failures and branches, progress reporting

IntegrationPlaywrightSoftware developmentInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
86
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Failures and branches w 10
0
Progress reporting w 2
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: 8. 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 60/100

    • 0Result and completion. Does not say what the result is
    • 0Failures and branches. Linear process with no failure handling
    • 0Progress reporting. Says nothing while it works
    • 60Tools and files. Uses tools (web) that frontmatter does not declare
    • 70When it triggers. States when to use, but not when not to
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 10 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 561 tokens
    • 100Running it twice. No mutating operations
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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
    • -35 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 528: enough signal without eating the budget
    • +4Structure: 9 headings
    • +3Step-by-step instructions: 10 items
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.

    External checks

    ClawHub: suspicious
    The main browser automation feature is plausible, but the package also includes unrelated scripts that read local attendance files and save website images/reports to Desktop without clear disclosure.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026