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 reticlehq · MCP Server · ★ 730
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is reticle safe to install? View the security audit →
Your AI agent says "Feature complete." Then you open the app: ✗ a silent under a page that looks perfect ✗ a flow that used to work, now broken ✗ mock data where the real API should be Reticle is a proofreader for AI-written code. Your agent writes code. Reticle checks it against the real running app — the network calls, the store, the console, the things a screenshot can never show — and hands back pass, fail, or "couldn't tell", with the to fix. The agent fixes and retries until it passes, before you ever open the app. [](https://github.com/reticlehq/reticle/star
| Stars | 730 |
| Forks | 132 |
| Language | TypeScript |
| Category | MCP Server |
| Quality Score | 63.8340273573395/100 |
| Open Issues | 132 |
| Last Updated | 2026-09-19 |
| Created | 2026-06-11 |
| Platforms | browser, claude-code, mcp, node |
| Est. Tokens | ~21k |
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reticle is AI agents can generate code, but still struggle to understand what they build. Reticle brings Jev-style machine-native runtime perception to web & desktop applications.. It is categorized as a MCP Server with 730 GitHub stars.
reticle is primarily written in TypeScript. It covers topics such as agent-skill, agent-skills, agent-testing.
You can find installation instructions and usage details in the reticle GitHub repository at github.com/reticlehq/reticle. The project has 730 stars and 132 forks, indicating an active community.
The top alternatives to reticle on Agent Skills Hub include agent-skills, testdriverai, Claude-Code-Everything-You-Need-to-Know. 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: