reasoning-trace-optimizer
Reasoning Trace Optimizer
Debug and optimize AI agents by analyzing their reasoning traces. This skill uses MiniMax M2.1's interleaved thinking to provide deep insight into agent decision-making and generate concrete improvements.
When to Activate
- User asks to "debug agent", "analyze reasoning", or "optimize prompt"
- Agent task fails and user wants to understand why
- User mentions "context degradation", "tool confusion", or "instruction drift"
- Request to improve agent performance or reduce errors
- User wants to generate shareable learnings from debugging sessions
- After repeated failures on similar tasks
Core Concepts
Interleaved Thinking
Unlike standard reasoning models that think once at the start, interleaved thinking allows reasoning BETWEEN each tool interaction. This is critical because:
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