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 esengine · Agent Tool · ★ 372
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is reasonix safe to install? View the security audit →
English · 简体中文 · Guide · Spec · Website · Discord [!IMPORTANT] Reasonix 1.0 is a ground-up rewrite in Go — this branch () is the new default and where development happens now. The earlier TypeScript releases are legacy, living on the branch (maintenance only). See the migration guide. stays the install command — + delivers the Go binary, is the legacy TS build. <img src="https://img.shields.io/npm/l/reason
| Stars | 372 |
| Forks | 21 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 70.9478033834501/100 |
| Open Issues | 23 |
| Last Updated | 2026-05-06 |
| Created | 2026-04-21 |
| Platforms | cli, node |
| Est. Tokens | ~401k |
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reasonix is DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability — leave it running.. It is categorized as a Agent Tool with 372 GitHub stars.
reasonix is primarily written in TypeScript. It covers topics such as agent, agent-framework, ai-agent.
You can find installation instructions and usage details in the reasonix GitHub repository at github.com/esengine/reasonix. The project has 372 stars and 21 forks, indicating an active community.
reasonix is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to reasonix on Agent Skills Hub include Overture, formax, toktrack. 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: