Agents4h ago
AI Agent Skills Fail In Real-World Tests
A study of 34,000 real-world skills reveals that modular instructions barely improve agent performance under realistic conditions. Weaker models actually perform worse when using these enhancements. This gap suggests current benchmarks overstate the utility of skill-based architectures for AI agents. Practitioners should prioritize core model reasoning over complex skill libraries.