Awesome AI Agent Skills Model Card
这是可索引项目报告证据页：它保留 Awesome AI Agent Skills Model Card 的源材料入口、机制线索和限制提醒；正文仍需 reader/editor 与 academic public-copy review 后才能当作最终结论引用。
Awesome AI Agent Skills Model Card
| Field | Value |
|---|---|
| Repository | seb1n/awesome-ai-agent-skills |
| Category | Cross-Agent Skill Index and Install Guide |
| Stars / forks snapshot | 92 / 17 |
| Language | Markdown |
| License | MIT |
| Raw capture | raw-github/seb1n_awesome-ai-agent-skills.md |
| Updated by | hourly public metadata update, 2026-05-30 01:15 +0800 |
1. Role in Self Evolve
awesome-ai-agent-skills curates reusable skill packs and installation paths across Codex, Claude, Cursor, Gemini CLI, OpenCode, and related agent runtimes. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
collect reusable agent skills in one registry -> map installation paths for multiple agent runtimes -> standardize skill formatting and metadata -> reduce bootstrapping friction for reproducible skill reuse
3. Evidence Path
web-observed GitHub page showed 92 stars, 17 forks, 4 commits, MIT license, and README framing as a curated list for reusable AI coding agent skills. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Cross-Agent Skill Index and Install Guide: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.
5. Limits
The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.