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 Tencent · Codex Skill · ★ 159
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is SkillHone safe to install? View the security audit →
SkillHone-Skills Continual Agent Skill Evolution Through Persistent Decision History English • 简体中文 Paper • News • Why SkillHone • Compare • Install • Usage • Whole-Skill Optimisation • Observability • Runtimes • Eval / Skill Split • Bundle • Configure Overview Video <video src="https://github.com/user-
| Stars | 159 |
| Forks | 13 |
| Language | TypeScript |
| Category | Codex Skill |
| Quality Score | 65.3539520203361/100 |
| Last Updated | 2026-09-19 |
| Created | 2026-06-09 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~17k |
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SkillHone is Continual agent skill evolution through persistent decision history. Whole-skill optimisation (SKILL.md + scripts + references) with every decision landing as a local Git issue / PR / wiki. Runs on an. It is categorized as a Codex Skill with 159 GitHub stars.
SkillHone is primarily written in TypeScript. It covers topics such as agent-skills, llm-agents, self-improving-agents.
You can find installation instructions and usage details in the SkillHone GitHub repository at github.com/Tencent/SkillHone. The project has 159 stars and 13 forks, indicating an active community.
The top alternatives to SkillHone on Agent Skills Hub include wikiskill, grace-marketplace, 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: