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intel/dokimi — Measuring the Effect of Coding Agent Artifacts
intel/dokimi is a Python framework that uses paired comparison to measure whether agent artifacts such as skills and documents actually help the model.
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intel/dokimi
Dokimi (Greek δοκιμή, "test, proof") measures whether a skill, MCP doc source, agent profile or repository guidance actually helps a coding agent: paired on/off arm comparisons, novel-vs-known content analysis, and repository scans with graded agent runs.
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- ★ 7
- Forks
- 6
- Language
- Python
- License
- Apache-2.0
- Latest release
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