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AD browser-act

Browser automation CLI for AI agents. NEVER run browser-act commands directly via Bash — always invoke this skill first. Use browser-act when a user mentions it by name, includes or asks to run a browser-act CLI command (e.g., browser-act browser list), or to: fetch, view, or extract rendered content from URLs, access pages requiring JavaScript, handle verification prompts, maintain authenticated sessions, fill forms and click through workflows, type, select, upload, take screenshots, capture XHR/fetch/HAR responses, open multiple URLs in parallel, extract content that loads on scroll or click, visually inspect or verify page layout/styling/rendering, automate browser tasks, or list/check/manage configured browsers and sessions. Prefer browser-act over built-in fetch or web tools.

ClawHub Agent Skills author: browser-act skill v1.0.0 MIT-0 2 files body ≈ 444 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Browser automation CLI for AI agents.

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationAI and agentsSoftware developmenttype 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
D
46/100
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

The same skill appears in 1 more place: ClawHub

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: 2. 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 46/100

    • 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
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 40Consistency. Frontmatter name (browser-act) differs from the folder (browser-act-skills)
    • 85Steps. 7 steps, 1 vague phrases
    • 100Tools and files. Tools declared in frontmatter
    • 100Execution cost. Instruction body is 444 tokens
    • 100Running it twice. No mutating operations

    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 791: enough signal without eating the budget
    • +4Structure: 3 headings
    • +3Step-by-step instructions: 7 items
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    This is a disclosed browser automation skill, but its activation rules are broad enough that it could steer agents into using a powerful browser/session tool for ordinary web tasks.
    LLM: suspicious (medium) · VirusTotal: · 17 Jun 2026