by Kulaxyz · Agent Tool · ★ 948
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won golden path in a session and harvest it into a reusable skill/rule for next time.
| Stars | 948 |
| Forks | 42 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 51.4564420129974/100 |
| Open Issues | 3 |
| Last Updated | 2026-07-01 |
| Created | 2026-06-28 |
| Platforms | claude-code |
| Est. Tokens | ~2k |
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self-learning-skills is A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won golden path in a session and harvest it into a reusable skill/rule for next time.. It is categorized as a Agent Tool with 948 GitHub stars.
You can find installation instructions and usage details in the self-learning-skills GitHub repository at github.com/Kulaxyz/self-learning-skills. The project has 948 stars and 42 forks, indicating an active community.
self-learning-skills is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to self-learning-skills on Agent Skills Hub include excalidraw-diagram-skill, raptor, playwright-skill. 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: