Compact Documentation for Coding Agents: A Benchmark, an Optimizer, and Why It Does Not Transfer

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Compact Documentation for Coding Agents: A Benchmark, an Optimizer, and Why It Does Not Transfer

We investigate whether natural-language documentation helps coding agents resolve software issues, and we build the tools to construct and evaluate it. We introduce a roundtrip benchmark that scores code descriptions by whether code regenerated from them passes the original tests, and show that completeness, not length, drives a description's fidelity. Using the benchmark as an optimization signal, we discover a description-writing prompt that reaches full fidelity and generalizes to unseen file

Source: ArXiv AI