Why Agents Are Ignoring Your Skills (Literally)
Understanding the Limitations of Skills in Agent Context
Introduction to Skills and Their Purpose
- The concept of skills was introduced by Enthropic, aiming for progressive disclosure to enhance agent context.
- Despite their design, agents often ignore these skills, undermining their intended purpose.
Performance Issues with Skills
- Research indicates that when using MCPS (Multi-Context Processing Server), irrelevant information clutters the context window before any interaction occurs.
- Agents must invoke skills to access additional information; however, they frequently fail to do so—56% of the time in certain evaluations.
Application Scenarios for Skills
- Skills are particularly beneficial during updates or conflicting documentation scenarios, allowing agents to reference specific skills without overwhelming context windows.
- The challenge remains that agents do not trigger these skills effectively due to a lack of training on this abstraction compared to tool usage.
Training and Reinforcement Learning
- While some models like those from Anthropic have undergone reinforcement learning for skill usage, others may not be adequately trained.
- An example is Kimmy's Agent Swarm which utilized parallel agent reinforcement learning for improved performance across multiple sub-agents.
Findings on Skill Implementation
- Adding skills did not enhance performance in certain evaluations; instead, simpler methods like using agents.md yielded better results.
- Two approaches were tested: indexing information versus consolidating everything into agents.md. The latter proved more effective as a grounding document.
Best Practices for Using Skills
- Explicitly instructing agents on when to use skills can improve invocation rates but requires careful prompt engineering.
- Compressing skill context from 40 kilobytes down to 8 kilobytes through summarization still maintained effectiveness while avoiding context rot issues.
Recommendations for Building Agent Systems
- When developing systems utilizing skills, consider the model being used; post-trained models may handle skill integration better.
- Summarizing available skills and linking them within a grounding document like agents.md or clot.md is recommended for optimal functionality.