evoui-browser: Self-evolving browser automation for Codex, Claude Code, and Cursor—learn reusable site knowledge and safely

by Salmonbird · Codex Skill · ★ 100

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install evoui-browser

npx skills add Salmonbird/evoui-browser --skill evoui-browser -g
npx skills add Salmonbird/evoui-browser --skill evoui-browser -g -a codex

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 68/100

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.

agent-browseragent-skillsai-agentsbrowser-automationclaude-codecodexcomputer-usecursorpythonrecord-replay

Quick Facts

Stars100
Forks0
LanguagePython
CategoryCodex Skill
LicenseApache-2.0
Quality Score68/100
Last Updated2026-08-14
Created2026-07-25
Platformsbrowser, claude-code, codex, python
Est. Tokens~15k

About evoui-browser

Less repeated browser work. The agent keeps the judgment. English · 简体中文 Evoui Browser is an optional Agent Skill for . Run a browser task normally once; on later, similar tasks, Evoui can reuse verified navigation and mechanical steps so the agent spends less time exploring and repeating work. The host agent still chooses targets, interprets results, and decides what to do next.

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How this security grade is produced

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:

View on GitHub → Browse Codex Skill tools