에이전트 지능을 위한 대규모 코드 기반의 접지된 기술 합성
본 논문은 소스 코드를 활용하여 에이전트의 재사용 가능한 skill을 자동으로 생성하는 Code2Skill 파이프라인을 제안합니다. 이 시스템은 코드 유닛을 atomic operations, composite workflows, recurring patterns 형태의 구현 기반 레코드로 변환하며, source-body-blind reconstruction과 source-aware comparison을 통해 각 레코드를 검증합니다. 이를 통해 19,769개의 GitHub 저장소로부터 1,006,822개의 검증된 레코드를 포함하는 CodeSkillBank를 구축하였습니다.
Reusable skills give agents transferable procedural knowledge, making scalable acquisition essential for extending agents beyond prior experience. Existing methods face two limitations: trajectory-based synthesis requires interactions with specific environments, while document-derived skills may lack executable evidence and verification. Source code offers a complementary path: it requires no prior agent experience yet provides executable evidence for grounding abstractions. We present Code2Skill, a fully automated pipeline that transforms selected code units into implementation-anchored records of atomic operations, composite workflows, and recurring patterns, then verifies each record through source-body-blind reconstruction and source-aware comparison. Applied to 19,769 popular, actively maintained GitHub repositories, Code2Skill produces CodeSkillBank, a grounded bank of 1,006,822 accepted records with workflow, boundary, provenance, and source-evidence metadata. Across 72 protocol