Reasoning Trace Optimizer

概要

The Reasoning Trace Optimizer is a specialized tool designed to debug and enhance AI agent behavior by analyzing 'interleaved thinking' patterns. By examining the reasoning steps between tool interactions, it identifies common failure modes like tool confusion, instruction drift, and goal abandonment. It provides developers with an automated optimization loop to refine system prompts and generate reusable agent skills, ensuring long-horizon tasks remain focused and accurate across complex, multi-turn workflows.

主な機能

• Iterative prompt optimization loops to improve agent performance
• Interleaved thinking analysis for deep insight into agent decision-making
• 7,304 GitHub stars
• Automated pattern detection for context degradation and tool confusion
• Automated skill generation based on successful optimization artifacts
• Universal session analysis for Claude, GPT, and other agent architectures

ユースケース

• Capturing and sharing organizational best practices as reusable Agent Skills
• Debugging failed agentic workflows to understand why specific tool errors occurred
• Optimizing system prompts for complex, multi-step AI research tasks