pith:JFWDTT5N
SkillMOO: Multi-Objective Optimization of Agent Skills for Software Engineering
SkillMOO evolves skill bundles for LLM coding agents by combining LLM-proposed edits with NSGA-II selection to raise pass rates while lowering cost.
arxiv:2604.09297 v2 · 2026-04-10 · cs.SE · cs.AI
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Claims
On three SkillsBench software engineering tasks, SkillMOO improves pass rate by up to 131% while reducing cost up to 32% relative to the best baseline per task at low optimization overhead.
That LLM-proposed edits guided by failure analysis combined with NSGA-II survivor selection will reliably discover superior skill bundles without overfitting to the specific benchmark tasks or introducing hidden costs not captured in the reported metrics.
SkillMOO automatically evolves skill bundles for LLM coding agents via LLM-proposed edits and NSGA-II, achieving up to 131% higher pass rates and 32% lower costs on three SkillsBench tasks.
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| First computed | 2026-05-20T00:03:10.907210Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
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Aliases
· · · · ·Agent API
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/JFWDTT5N2R3SLTIJFAQK3P2B5N \
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Canonical record JSON
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