SKILLEMALL.ai
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Use an already-logged-in Edge/Chrome/Chromium browser as the agent's hands. A persistent logged-in browser bridge for OpenClaw, Copilot CLI, Claude Code, Hermes, and other local AI agents. Use when: open browser, reuse logged-in websites, check X/Gmail/Outlook/Amazon/LinkedIn/Facebook/Instagram/WeChat Web, read webpages, switch tabs, click, type, fetch pages, browser automation.

ClawHub Agent Skills author: TommyYanPS v0.1.0 MIT-0 10 files · 2 scripts body ≈ 1 466 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationGmailOutlookAI and agentstype 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
A
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
82
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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: 10. 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 48/100

    • 0Result and completion. Does not say what the result is
    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Failures and branches. Linear process with no failure handling
    • 20When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 100Steps. 28 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1466 tokens
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low The response is described with custom markup (10 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)
    • +3Output format is not stated: the model decides each time
    • -31 of 3 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +3Description length 381: enough signal without eating the budget
    • +4Structure: 10 headings
    • +3Step-by-step instructions: 28 items
    • +4Has examples (2 code blocks)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.

    External checks

    ClawHub: suspicious
    This appears to be a legitimate browser automation skill, but it gives agents broad control over logged-in accounts and public posting without enough built-in scoping or confirmation.
    LLM: suspicious (high) · 28 May 2026