Unified experience representation for agent skills

Determine which unified representation of agent experience achieves both plug-and-play usability and consistent effectiveness across diverse and complex tool-use scenarios for large language model agents.

Background

The paper surveys three major paradigms for encoding agent experience—case-based trajectories, strategy-based insights/workflows, and skill-based abstractions—and notes that different representations trade off transferability, retrieval efficiency, and executability.

Despite proposing a hybrid approach (high-level planning plus textual skills), the authors explicitly state that it remains unclear which unified experience representation would be broadly pluggable and consistently effective across heterogeneous, tool-intensive environments.