LangGraph Application Fine-Tuning Skill

A skill for iteratively optimizing prompts and processing logic in each node of a LangGraph application based on evaluation criteria.

📋 Overview

This skill executes the following process to improve the performance of existing LangGraph applications:

1. Load Objectives: Retrieve optimization goals and evaluation criteria from .langgraph-architect/fine-tune.md (if this file doesn't exist, help the user create it based on their requirements)
2. Identify Optimization Targets: Extract nodes containing LLM prompts using Serena MCP (if Serena MCP is unavailable, investigate the codebase using ls, read, etc.)
3. Baseline Evaluation: Measure current performance through multiple runs
4. Implement Improvements: Identify the most effective improvement areas and optimize prompts and processing logic
5. Re-evaluation: Measure performance after improvements
6. Iteration: Repeat steps 4-5 until goals are achieved

Important Constraint: Only optimize prompts and processing logic within each node without modifying the graph structure (nodes, edges configuration).

🎯 When to Use This Skill