SKILLEMALL.ai
GitHub ↗ RU Sign in

BC playwright-scraper-skill

Playwright-based web scraping OpenClaw Skill with anti-bot protection. Successfully tested on complex sites like Discuss.com.hk.

ClawHub Agent Skills v1.2.0 14 files · 2 scripts body ≈ 1 456 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 60/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedurePlaywrightInfrastructuretype 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
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
73
Run on models
none yet
Process rating
C
60/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

The same skill appears in 4 more places: ClawHub, ClawHub, ClawHub, ClawHub

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 · 2

✓ No critical or high findings

Medium and low: 2
  • low Secrets in code secret-high-entropy-token package-lock.json:18
    High-entropy token-like string (may be an id, hash or a credential) (detector / deny-list definition)
    "integrity": "sha5…uWm+fFRcIOgKBMiOBP+eXiy…9ab+DDKA==",
    detector
  • low Dangerous commands cmd-privilege scripts/playwright-stealth.js:47
    Privilege escalation / world-writable permissions (string literal in code, not executed)
    '--disable-setuid-sandbox',
    code literal

Files scanned: 14. 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 60/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 65Failures and branches. 3 branches
  • 100Tools and files. No external tools needed
  • 100Steps. 42 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1456 tokens
  • 100Running it twice. No mutating operations
  • low 12 top-level sections: this looks like several domains in one skill

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
  • -233 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 128: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (7 code blocks)
  • +3All 2 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
This is a working web-scraping skill, but it should be reviewed because it is built around evading anti-bot protections and saving page captures with limited safeguards.
LLM: suspicious (high) · VirusTotal: suspicious