EvalMonkey Model Card

这是可索引项目报告证据页：它保留 EvalMonkey 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。

EvalMonkey Model Card

1. Role in Self Evolve

EvalMonkey provides a lightweight evaluation harness for LLM agents with regression workflows and reusable benchmark checks. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.

2. Working Principle

define task-level agent evaluation suites -> run LLM-based and deterministic regression checks -> aggregate quality metrics into repeatable reports -> feed benchmark regressions back into skill/harness improvement loops

3. Evidence Path

web-observed GitHub page showed 36 stars, 4 forks, 30 commits, Apache-2.0 license, and README focus on evaluating LLM agent performance. 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 Agent Evaluation Harness and Regression Pipeline: 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.