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 loulanyue · Codex Skill · ★ 267
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is awesome-claude-notes safe to install? View the security audit →
awesome claude notes 语言 简体中文（当前） 简体中文镜像 Português (Brasil) 繁體中文 日本語 한국어 Türkçe 一套面向 Claude Code 与多种 AI coding harness 的生产级工作流资产库。 把 AI coding agent 从“偶尔好用”，推进到“稳定可复用”。 awesome claude notes 提供已经打磨过的 agents、skills、commands、rules、hooks、 MCP configs 和跨平台脚本，帮助你更快搭起一套可落地的 agent harness，而不是从零 拼装目录、提示词和自动化流程。
| Stars | 267 |
| Forks | 13 |
| Language | JavaScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 61.7563527656543/100 |
| Open Issues | 12 |
| Last Updated | 2026-08-25 |
| Created | 2026-03-17 |
| Platforms | claude-code, codex, node |
| Est. Tokens | ~14k |
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awesome-claude-notes is Community-maintained distribution of reusable AI coding agents, commands, skills, hooks, and cross-harness workflows.. It is categorized as a Codex Skill with 267 GitHub stars.
awesome-claude-notes is primarily written in JavaScript. It covers topics such as agent-skills, ai-agents, ai-coding.
You can find installation instructions and usage details in the awesome-claude-notes GitHub repository at github.com/loulanyue/awesome-claude-notes. The project has 267 stars and 13 forks, indicating an active community.
awesome-claude-notes is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to awesome-claude-notes on Agent Skills Hub include agent-skills, quint-code, OpenContext. 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: