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Fast headless browser for QA testing and site dogfooding. Navigate any URL, interact with elements, verify page state, diff before/after actions, take annotated screenshots, check responsive layouts, test forms and uploads, handle dialogs, and assert element states. ~100ms per command. Use when you need to test a feature, verify a deployment, dogfood a user flow, or file a bug with evidence.

Not recommendedcritical or high security findings
LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 37 files body ≈ 3 112 tokens Open the sourcegithub.com↗ analyzed 2 d ago

Fast headless browser for QA testing and site dogfooding.

As a process B 68/100 · Nearly there — weak spots: when it triggers, inputs and preconditions

IntegrationData and analyticsInfrastructuretype 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
77/100
safety, quality, tests
Safety 60%
71
Quality 40%
87
Run on models
none yet
Process rating
B
68/100
Nearly there
Inputs and preconditions w 11
0
When it triggers w 12
20
Result and completion w 14
60
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Exfiltration
If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
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 · 4

  • high Exfiltration intent-browser-credential-store SKILL.md:250
    Accesses a browser credential / cookie store
    | `cookie-import-browser [browser] [--domain d]` | Import cookies from Comet, Chrome, Arc, Brave, or Edge (opens picker, or use --domain for direct import) |
Medium and low: 3
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read AskUserQuestion
  • medium Exfiltration intent-browser-credential-store src/commands.ts:75
    Accesses a browser credential / cookie store (quoted — discussed, not commanded)
    'cookie-import-browser': { category: 'Interaction', description: 'Import cookies from Comet, Chrome, Arc, Brave, or Edge (opens picker, or use --domain for direct import)', usage: 'cookie-import-brows
    quoted
  • low Dangerous commands cmd-pipe-to-shell-known-host SKILL.md:106
    Pipe-to-shell installer from a well-known host (still executes remote code) (quoted — discussed, not commanded)
    3. If `bun` is not installed: `curl -fsSL https://bun.sh/install | bash`
    quoted

Files scanned: 15. 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 68/100

  • 0Inputs and preconditions. Does not say what the process needs to start
  • 20When it triggers. No condition that starts the skill
  • 60Result and completion. Output format stated, no completion criterion
  • 60Failures and branches. 2 branches
  • 85Steps. 7 steps, 1 vague phrases
  • 100Tools and files. Tools declared in frontmatter
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3112 tokens
  • 100Running it twice. Mutating operations check current state
  • 100Progress reporting. Reports progress
  • low The response is described with custom markup (29 tags): a typed call is more reliable

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)
  • +1No license
  • +2Single-language instructions
  • +3Description length 394: enough signal without eating the budget
  • +4Structure: 27 headings
  • +3Step-by-step instructions: 7 items
  • +3Output format is stated explicitly
  • +4Has examples (17 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.