SkillRouter: Skill Routing for LLM Agents at Scale

Understand

Reusable skills let LLM agents package task-specific procedures, tool affordances, and execution guidance into modular building blocks.

• As skill ecosystems grow to tens of thousands of entries, exposing every skill at inference time becomes infeasible.
• This creates a skill-routing problem: given a user task, the system must identify relevant skills before downstream planning or execution.
• Existing agent stacks often rely on progressive disclosure, exposing only skill names and descriptions while hiding the full implementation body.