lark 是怎么评估skill执行的效率的？
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domain/core
- Dominant language
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Description
怎么保证迭代和优化能适配所有的agent？
怎么保证新的提交是收益正向的？
有评估或者评测标准规范么？
有对应的评测工具么？
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points. Start by clarifying which skill and agent evaluation surfaces already exist, then document the proposed criteria and tool scope. Done should include an agreed evaluation standard and a clearly identified implementation path.
Written by the indexing model from the issue text.
Assessment
- Domain
- ai, testing-qa
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100