reasoning-trace-optimizer
CommunityDebug AI agents by analyzing reasoning.
Software Engineering#debugging#prompt optimization#ai agents#reasoning traces#interleaved thinking#m2.1
AuthorCxxxxDxxxF
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps developers debug and optimize AI agents by analyzing their reasoning traces, identifying failure patterns, and suggesting prompt improvements.
Core Features & Use Cases
- Trace Capture: Records detailed thinking blocks and tool calls from M2.1 agent interactions.
- Pattern Analysis: Detects common issues like context degradation, tool confusion, and instruction drift.
- Prompt Optimization: Iteratively refines prompts to improve agent performance and reliability.
- Use Case: An agent is failing to follow complex instructions. Use this Skill to analyze its reasoning trace, discover it's losing context, and automatically generate an improved prompt that reinforces goal adherence.
Quick Start
Use the reasoning trace optimizer skill to analyze the agent's last task failure.
Dependency Matrix
Required Modules
anthropicpydanticrichpython-dotenv
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: reasoning-trace-optimizer Download link: https://github.com/CxxxxDxxxF/project-blackout/archive/main.zip#reasoning-trace-optimizer Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
Agent Skills Search Helper
Install a tiny helper to your Agent, search and equip skill from 223,000+ vetted skills library on demand.