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BF browser-automation-core

Core browser automation library for OpenClaw agents. Provides reusable navigation, interaction, and capture capabilities for both Facet (Onshape learning) and Ace (competition entry). Use when any agent needs to automate web browser interactions.

ClawHub Agent Skills author: stefanferreira v1.0.0 MIT-0 9 files body ≈ 3 084 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process F 50/100 · Will not run — References files that are not bundled: /docs/browser-integration, /examples/websocket

ProcedurePlaywrightAI and agentsInfrastructuretype 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%
100
Quality 40%
70
Run on models
none yet
Process rating
F
50/100
Will not run
References files that are not bundled: /docs/browser-integration, /examples/websocket
Tools and files w 18
0
Result and completion w 14
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
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: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: /docs/browser-integration
  • warning missing-ref reference to a missing file: /examples/websocket

Process rating: all ten parameters 50/100

Will not run. References files that are not bundled: /docs/browser-integration, /examples/websocket
  • 0Tools and files. 2 referenced file(s) missing: /docs/browser-integration, /examples/websocket
  • 0Result and completion. Does not say what the result is
  • 20When it triggers. No condition that starts the skill
  • 50Failures and branches. 0 branches, has a failure section
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 83 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3084 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 16 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
  • -2localhost URLs: will not work for another user
  • -31 of 1 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 246: enough signal without eating the budget
  • +4Structure: 60 headings
  • +3Step-by-step instructions: 83 items
  • +4Has examples (22 code blocks)

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

External checks

ClawHub: suspicious
This is a real browser automation skill, but it gives agents broad control over browsing, form submission, screenshots, and in-page scripts without enough user-facing limits.
LLM: suspicious (high) · VirusTotal: · 29 May 2026