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 juew · Codex Skill · ★ 169
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Skill-Routing-Kit safe to install? View the security audit →
Skill Routing Kit Make Codex pick the right skill or plugin more often. 中文说明 · Full English docs · Demo · Release notes Why This Exists Codex can have dozens of skills and plugins installed, but the correct one does not always trigger. That creates a quiet productivity tax: a PDF input gets mistaken for the final artifact; a routing/debugging question gets handled by the wrong domain skill; connector plugins are considered even when the user's work is local; new skills are installed, but nobody remembers when to use them. Skill Routing Kit adds a small local-first routing layer for Codex. It helps Codex answer: text What kind of task is this? Where is the source of truth? What is the final artifact? Which skill should be primary? Which plugin is only a helper? When sho
| Stars | 169 |
| Forks | 9 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 63.6318904365137/100 |
| Last Updated | 2026-06-18 |
| Created | 2026-06-03 |
| Platforms | codex, python |
| Est. Tokens | ~14k |
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Skill-Routing-Kit is Skill Routing Kit 是一个本地优先的 Codex 插件，用来提升 skill 和插件的命中率，同时避免引入缓慢、强侵入的运行时路由层。. It is categorized as a Codex Skill with 169 GitHub stars.
Skill-Routing-Kit is primarily written in Python.
You can find installation instructions and usage details in the Skill-Routing-Kit GitHub repository at github.com/juew/Skill-Routing-Kit. The project has 169 stars and 9 forks, indicating an active community.
Skill-Routing-Kit is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to Skill-Routing-Kit on Agent Skills Hub include ai-maestro, upskill, 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: