BUILD-AND-FIND: An Effort-Aware Protocol for Evaluating Agent-Managed Codebases
📰 ArXiv cs.AI
Learn to evaluate agent-managed codebases with BUILD-AND-FIND, a protocol that considers effort awareness in repository-level engineering
Action Steps
- Implement BUILD-AND-FIND protocol to evaluate agent-managed codebases
- Run experiments to compare the performance of different agents in managing codebases
- Configure effort-aware metrics to assess the quality of generated repositories
- Test the protocol on various coding tasks and repository sizes
- Apply BUILD-AND-FIND to real-world scenarios and refine the protocol based on feedback
Who Needs to Know This
Software engineers, DevOps teams, and AI researchers can benefit from this protocol to improve the evaluation of agent-managed codebases and enhance collaboration between humans and agents
Key Insight
💡 Evaluating agent-managed codebases requires considering not only correctness but also effort awareness and repository-level engineering
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🚀 Introducing BUILD-AND-FIND: an effort-aware protocol for evaluating agent-managed codebases 🤖💻
Key Takeaways
Learn to evaluate agent-managed codebases with BUILD-AND-FIND, a protocol that considers effort awareness in repository-level engineering
Full Article
Title: BUILD-AND-FIND: An Effort-Aware Protocol for Evaluating Agent-Managed Codebases
Abstract:
arXiv:2605.06136v1 Announce Type: cross Abstract: Most coding-agent benchmarks ask whether generated code behaves correctly. That remains essential, but repository-level engineering is increasingly agent-managed: one agent writes a repository, and later agents inspect, audit, or extend it as working context. In that setting, a generated repository is not only an answer to a task but also a communication artifact for future work. Even when strong agents nearly satisfy the visible behavioral objec
Abstract:
arXiv:2605.06136v1 Announce Type: cross Abstract: Most coding-agent benchmarks ask whether generated code behaves correctly. That remains essential, but repository-level engineering is increasingly agent-managed: one agent writes a repository, and later agents inspect, audit, or extend it as working context. In that setting, a generated repository is not only an answer to a task but also a communication artifact for future work. Even when strong agents nearly satisfy the visible behavioral objec
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