Generalization of SkillReducer to Other Agent Platforms

Determine whether the SkillReducer framework—and its routing-layer description compression and Stage 2 progressive disclosure restructuring—generalizes beyond the Anthropic skill protocol to other LLM agent platforms such as Cursor and Windsurf, preserving or improving routing behavior and task performance under their distinct skill mechanisms, tool registries, and system prompts.

Background

The paper evaluates SkillReducer on 600 skills that all conform to the Anthropic/Claude Code skill protocol, and also tests transfer to an independent agent framework (OpenCode), finding strong retention and a less-is-more effect. However, the authors note that platform diversity (e.g., Cursor, Windsurf) may involve different routing strategies, tool ecosystems, and system prompts, which could affect whether description compression and progressive disclosure retain performance.

Thus, while cross-framework evidence suggests some transferability, the authors explicitly flag that broader platform generalization has not yet been tested, leaving open whether SkillReducer’s gains persist across agent platforms with different skill interfaces.