EVOHARNESSBENCH: Can Your Agents Keep Pace with an Evolving Harness?
3.80T1 sourcearXiv cs.MA
Source record
Published by arXiv cs.MA (T1 source). The original is at https://arxiv.org/abs/2609.04280.
Pipeline notes
The summary and note below are generated by the signal pipeline — they are Beyond Desk’s reading, not quotations from the source.
SummaryIntroduces EVOHARNESSBENCH, a benchmark for evaluating LLM-based agents under controlled harness evolution across tools, skills, and agents. Comprises 802 tasks, 520 tools, 42 skills, and 62 agents. Results show harness expansion can degrade performance on previously solved tasks, and that retention and adaptation can conflict.
Why it mattersSurfaces harness-induced forgetting as a concrete failure mode. Relevant for anyone building agent tool stacks where capabilities are added over time.
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