Skills on the Fly: Test-Time Adaptive Skill Synthesis for LLM Agents
Additional test-time compute can give LLM agents access to more past experience, yet expanding the context or adding rollouts does not necessarily yield greater agent capability. We call this challenge test-time compute-to-capability conversion and propose SkillTTA, which retrieves task-relevant training trajectories and synthesizes a temporary skill conditioned on the visible target context for a solver with fixed parameters. To pursue a higher performance ceiling, SkillTTA further uses meta prompt optimization (MPO) to adapt the policy that writes these skills. MPO evaluates candidate prompts on paired tasks and emphasizes informative transitions. It also confines updates to benchmark-s...
| Authors | Jingxing Wang, Chenyu Zhou, Zhihui Fu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 16 May 2026 |
| Last updated at source | 29 July 2026 |
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