skills.rest
mkloz
mklozCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

reasoning-trace-optimizer

Analyze AI agent reasoning traces to detect patterns and optimize performance.

Updated Feb 23, 2026
Search Tags:#ai-agent#skill-generation#prompt-optimization#minimax-m2#reasoning-analysis
One-click install
npx skills add https://github.com/mkloz/teamforge-frontend --skill reasoning-trace-optimizer-mkloz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: reasoning-trace-optimizer
Source: https://github.com/mkloz/teamforge-frontend/tree/main/.agents/skills/interleaved-thinking
Command: npx skills add https://github.com/mkloz/teamforge-frontend --skill reasoning-trace-optimizer-mkloz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires anthropic, pydantic, rich, python-dotenv, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps you debug and optimize AI agents by analyzing their reasoning processes and identifying areas for improvement.

Core Features & Use Cases

  • Debugging: Understand and analyze the reasoning steps of AI agents.
  • Pattern Detection: Identify common issues like context degradation, tool confusion, and instruction drift.
  • Prompt Optimization: Generate improved prompts based on analysis to enhance agent performance.
  • Skill Generation: Convert learnings into reusable Agent Skills for team sharing.
  • Use Case: If your AI agent is producing unexpected results or failing to complete tasks, use this Skill to uncover the root cause and optimize its performance.

Quick Start

To get started, use the following command: /reasoning-trace-optimizer analyze-session

Frequently Asked Questions about reasoning-trace-optimizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I debug an AI agent that keeps failing tasks or producing unexpected results?▼

To debug a failing AI agent, you analyze its reasoning traces to identify root causes. This process evaluates tool usage, context degradation, and instruction drift to pinpoint exactly why your agent produces unexpected results.

What is reasoning trace analysis and how does it optimize prompt performance?▼

Reasoning trace analysis examines the step-by-step thinking process of AI agents to identify performance patterns. It optimizes prompts by detecting issues like context degradation and tool confusion, then generating improved prompts based on the deep analysis findings.

Do I need a MiniMax API key to analyze AI agent reasoning traces?▼

Yes, you need a MiniMax API key and model configuration to analyze AI agent reasoning traces. The Skill utilizes MiniMax M2.1's interleaved thinking capability to perform the deep analysis required for complex agentic tasks.

Can I convert optimized agent prompts into reusable skills for my team?▼

Yes, you can convert optimized prompts into reusable Agent Skills for team sharing. After analyzing reasoning traces and generating improved prompts, the Skill transforms these learnings into shareable skill components.

How do I start analyzing an AI agent session for instruction drift or tool confusion?▼

To start analyzing an AI agent session for instruction drift or tool confusion, run the command `/reasoning-trace-optimizer analyze-session`. This initiates the deep reasoning analysis to detect performance patterns and issues.

Related Skills

Explore More Software Engineering Skills→
marinvchmarinvch

reasoning-trace-optimizer

Analyze MiniMax M2.1 interleaved thinking traces to diagnose agent failures and generate prompt improvements.

Community
Advanced
Kushal9889Kushal9889

latent-briefing

Share relevant orchestrator reasoning state between agents to reduce token costs.

Community
Advanced
thangvawnthangvawn

claude-api

Integrate Anthropic Claude API with Python and TypeScript SDKs.

Community
Advanced
jax2730jax2730

reasoning-trace-optimizer

Analyze AI agent reasoning traces to detect failure patterns and optimize prompts.

Community
Advanced