SkillHone: Continual agent skill evolution through persistent decision history

by Tencent · Codex Skill · ★ 172

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 65/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agent-skillsllm-agentsself-improving-agentsskill-optimization

Quick Facts

Stars172
Forks17
LanguageTypeScript
CategoryCodex Skill
Quality Score65/100
Open Issues4
Last Updated2026-11-03
Created2026-06-09
Platformsclaude-code, codex, node
Est. Tokens~17k

About SkillHone

&nbsp;SkillHone-Skills Continual Agent Skill Evolution Through Persistent Decision History English &bull; 简体中文 Paper &bull; News &bull; Why SkillHone &bull; Compare &bull; Install &bull; Usage &bull; Whole-Skill Optimisation &bull; Observability &bull; Runtimes &bull; Eval / Skill Split &bull; Bundle &bull; Configure Overview Video <video src="https://github.com/user-

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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