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 testdriverai · Claude Skill · ★ 243
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is testdriverai safe to install? View the security audit →
Computer-Use SDK for E2E QA Testing The TestDriver SDK is a JS plugin for vitest that makes it easy to spawn ephemeral devices and use vision-based LLMs to construct detemanistic and reliable tests. 🚀 Quick Start • 📖 Documentation • 💻 Examples • 📖 Pricing • 💬 Discord • 🌐 Website Why TestDriver? Don't ship bugs because flows are too hard to test. TestDriver helps engineering teams easily test, debug, and monitor E2E flows that are hard or impossible to cover with other tools like: Third-Party Web Apps • Desktop Apps • VS Code Extensions • Chrome Extensions • AI Chatbots • OAuth Flows • PDF Content • Spelling & Grammar • File System & Uploads • OS Accessibility • Visual Content • • • Example js // Click on the new text document await testdriver.find("New text doc
| Stars | 243 |
| Forks | 35 |
| Language | JavaScript |
| Category | Claude Skill |
| Quality Score | 66.0613119774211/100 |
| Open Issues | 46 |
| Last Updated | 2026-09-21 |
| Created | 2024-08-25 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~13k |
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testdriverai is Computer-Use SDK for E2E QA Testing. It is categorized as a Claude Skill with 243 GitHub stars.
testdriverai is primarily written in JavaScript. It covers topics such as agent, agent-skills, agentic-coding.
You can find installation instructions and usage details in the testdriverai GitHub repository at github.com/testdriverai/testdriverai. The project has 243 stars and 35 forks, indicating an active community.
The top alternatives to testdriverai on Agent Skills Hub include qaskills, Mysti, smart-ralph. 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: