SKILLEMALL.ai

AB playwright-mcp-automation

Launch and operate the Playwright MCP server to let agents browse real websites (login, search, checkout, dashboards) through structured tools. Use when the task requires interacting with live pages beyond simple fetches—e.g., filling ecommerce carts, downloading statements behind auth, capturing screenshots, or testing UI flows with Playwright automation.

ClawHub Agent Skills author: zhanglinghao01-rakuten v1.0.0 5 files · 1 script body ≈ 1 543 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process B 70/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

ProcedurePlaywrightAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
91
Run on models
none yet
Process rating
B
70/100
Nearly there
Progress reporting w 2
0
Running it twice w 4
30
Result and completion w 14
40
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: 5. 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 70/100

    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (bash, 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
    • 85Steps. 49 steps, 1 vague phrases
    • 100Failures and branches. 4 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1543 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)
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +3Description length 358: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 49 items
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.

    External checks

    ClawHub: suspicious
    This appears to be a legitimate browser automation skill, but it needs review because it gives agents broad control over logged-in browser sessions with weak safety guidance.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026