Agent Skill Loader Model Card
这是可索引项目报告证据页：它保留 Agent Skill Loader 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。
Agent Skill Loader Model Card
| Field | Value |
|---|---|
| Repository | back1ply/agent-skill-loader |
| Category | Runtime Agent Skill Loader |
| Stars / forks snapshot | 10 / 3 |
| Language | TypeScript |
| License | MIT |
| Raw capture | raw-github/back1ply_agent-skill-loader.md |
| Updated by | hourly public metadata update, 2026-05-29 16:12 +0800 |
1. Role in Self Evolve
agent-skill-loader provides a TypeScript loader pipeline for wiring reusable skill modules into AI 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
ingest skill bundles with uniform loader interfaces -> resolve runtime dependencies and skill metadata -> mount skills into agent execution contexts -> support iteration through modular updates
3. Evidence Path
web-observed GitHub page showed 10 stars, 3 forks, 16 commits, MIT license, and README docs on loading external skills into agents. 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 Runtime Agent Skill Loader: 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.