Hugging Face Daily PapersRun-Ze Fan, Zihao Zhang, Simin Ma2 min readpaperadvanced
An Empirical Study of Harness Design for Coding Agents
Summary
This empirical study dissects coding agent harness components like planning, action space, and context management. It finds context management is critical for tight windows, rule-based elision is efficient, and planning shifts from accuracy to cost savings for stronger models.
- Context management is vital for tight context windows, primarily by preventing context-overflow failures.
- Staging rule-based elision before LLM-based summarization provides the strongest overall efficiency for context management.
- Planning improves accuracy for weaker models and reduces cost for stronger models with little change in accuracy.
- Bash-proficient models can operate effectively with a bash-only interface for substantially lower cost on command-line tasks.
Engineers building or evaluating autonomous coding agents can use these findings to design more efficient and effective harnesses tailored to specific LLM capabilities and budget constraints.
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