AI RESEARCH
Skill-as-Pseudocode: Refactoring Skill Libraries to Pseudocode for LLM Agents
arXiv CS.CL
•
ArXi:2605.27955v1 Announce Type: cross Markdown skill libraries for LLM agents ship as free-form prose, forcing the agent to re-derive both the input schema and the concrete invocation syntax on every retrieval. We observe that this often produces a "confused -> re-retrieve -> still confused" loop in which the agent issues a partially-correct action, receives uninformative environment feedback, and re-retrieves the same prose. We propose Skill-as-Pseudocode (SaP), an automatic conversion of markdown skill libraries into typed pseudocode with deterministic quality control.