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 AgnosticUI · Agent Tool · ★ 822
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is agnosticui safe to install? View the security audit →
Copy the source · Own the code · Framework-agnostic · Built for humans and AI agents One component library. Every framework. Documentation · Login AI Playbook · Onboarding AI Playbook · Dashboard AI Playbook · Components · Quick Start Source-first architecture AgnosticUI components are copied into your project at install time. They live in your repo (not hidden inside ): Full control over the source Native integration with your framework AI-readable, high-fidelity context You own the source (and the Context) The component source lands directly in your project. Readable, editable, and yours. sh
| Stars | 822 |
| Forks | 47 |
| Language | TypeScript |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 65.685324467317/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-30 |
| Created | 2020-09-07 |
| Platforms | browser, cli, node |
| Est. Tokens | ~16k |
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agnosticui is AgnosticUI Local (v2) is a CLI-based UI component library that copies components directly into your project. Works with AI tools, agent-driven UIs, and prompt-ready workflows.. It is categorized as a Agent Tool with 822 GitHub stars.
agnosticui is primarily written in TypeScript. It covers topics such as accessibility, agent-skills, ai-agents.
You can find installation instructions and usage details in the agnosticui GitHub repository at github.com/AgnosticUI/agnosticui. The project has 822 stars and 47 forks, indicating an active community.
agnosticui is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to agnosticui on Agent Skills Hub include apm, Claude-Code-Everything-You-Need-to-Know, awesome-agent-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: