No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by PramodDutta · Agent Tool · ★ 214
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is qaskills safe to install? View the security audit →
-- QASkills.sh The Curated QA Skills Directory for AI Coding Agents The curated QA skills directory for Claude Code, Cursor, Copilot, Windsurf, and 27+ AI coding agents. Website Get Started Why QASkills.sh? Among 49,000+ skills on Vercel's skills.sh, barely any are dedicated to QA testing. QASkills.sh fills that gap — a curated, QA-specific skills directory that gives your AI coding agent expert-level testing knowledge with a single command. <img
| Stars | 214 |
| Forks | 23 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67.8265836505937/100 |
| Open Issues | 4 |
| Last Updated | 2026-08-30 |
| Created | 2026-02-11 |
| Platforms | browser, claude-code, node |
| Est. Tokens | ~16k |
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qaskills is QA Skills Directory QA Skills is a curated directory of testing-specific skills for AI coding agents (Claude Code, Cursor, Copilot, etc.).. It is categorized as a Agent Tool with 214 GitHub stars.
qaskills is primarily written in TypeScript. It covers topics such as agent-browser, agent-skills, ai-testing.
You can find installation instructions and usage details in the qaskills GitHub repository at github.com/PramodDutta/qaskills. The project has 214 stars and 23 forks, indicating an active community.
qaskills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to qaskills on Agent Skills Hub include testdriverai, claude-code-skills, ai-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. 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: