by anomalyco · Agent Tool · ★ 441
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
npm install --global @opencode-ai/browser-control
npx skills add anomalyco/browser-control --skill browser-control -g
Taken from the project's README on GitHub. Check the security audit before running it.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 441 |
| Forks | 27 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64/100 |
| Open Issues | 4 |
| Last Updated | 2026-10-10 |
| Created | 2026-07-02 |
| Platforms | browser, node |
| Est. Tokens | ~20k |
Browser Control Browser Control lets trusted coding agents run Playwright against your existing Chromium-family browser. It uses your real browser profile, including logged-in sessions and installed extensions, instead of launching a separate headless browser. The driver runs locally and does not contain an LLM or make planning decisions.
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: