AgentSkillOS Model Card
这是可索引项目报告证据页：它保留 AgentSkillOS 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。
AgentSkillOS Model Card
| Field | Value |
|---|---|
| Repository | ynulihao/AgentSkillOS |
| Category | Agent Skill Retrieval and Orchestration OS |
| Stars / forks snapshot | 415 / 49 |
| Language | HTML/Python |
| License | MIT |
| Raw capture | raw-github/ynulihao_agentskillos.md |
| Updated by | hourly public metadata update, 2026-05-25 |
1. Role in Self Evolve
AgentSkillOS 把 200,000+ public skills 做成检索、组合和编排系统，并提供 30 个多格式 creative tasks 的 benchmark。
2. Working Principle
large skill ecosystem -> retrieval -> orchestration/composition -> batch execution -> benchmarked skill workflows
3. Evidence Path
web GitHub page observed 14 commits, MIT license, HTML/Python stack, 415 stars and 49 forks; README states 200,000+ skills, retrieval and orchestration, March 2026 benchmark with 30 multi-format creative tasks across 5 categories, and modular architecture. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the current snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Agent Skill Retrieval and Orchestration OS 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、SDK examples、skill install flows、memory experiments、agent evolution loops 或 production deployments；star/fork/commit 快照来自公开 GitHub 页面文本或可见页面片段。