Awesome Omni Skills Runtime Model Card
这是可索引项目报告证据页：它保留 Awesome Omni Skills Runtime 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 Omni Skills Runtime Model Card
| Field | Value |
|---|---|
| Repository | diegosouzapw/awesome-omni-skills |
| Category | Omni Skills CLI API MCP A2A Runtime |
| Stars / forks snapshot | 42 / 11 |
| Language | Python/JavaScript/Shell |
| License | MIT / CC-BY-4.0 content |
| Raw capture | raw-github/diegosouzapw_awesome-omni-skills.md |
| Updated by | hourly public metadata update, 2026-05-25 |
1. Role in Self Evolve
Awesome Omni Skills 是可安装的 AI coding skills 目录与运行时，把 SKILL.md、CLI、API、MCP、A2A、bundle、验证和多客户端安装统一成一个发布面。
2. Working Principle
native skill intake -> validation and curation -> CLI/API/MCP/A2A runtime surfaces -> multi-client skill installation
3. Evidence Path
web GitHub page observed 467 commits, 42 stars and 11 forks, MIT code license with CC BY 4.0 content license, 15 releases with v0.12.9 latest on 2026-04-25, Python/JavaScript/Shell/HTML/TypeScript stack; README claims 4,671 native skills, 7 bundles, 9 install clients, 16 MCP clients, 4 runtime surfaces, validation 4,037 passed / 634 warn / 0 errors, plus CLI/API/MCP/A2A surfaces, Codex CLI install path, static security gates, release checks, checksums and signed artifacts. Shell GitHub API access remained blocked by DNS and local gh auth was invalid in this run, so this card treats the current snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Omni Skills CLI API MCP A2A Runtime in the raw -> classification -> project card -> site/report pipeline. The reading path is: raw capture -> classification row -> public site card -> project report -> aggregate GitHub analysis.
5. Limits
当前未克隆源码，未运行 benchmark、skill install flows、memory experiments、MCP servers、agent evolution loops、security scanners 或 production deployments；star/fork/commit/release 快照来自公开 GitHub 页面文本或可见页面片段。