Optimize LangGraph prompts and node logic without altering graph structure.
npx skills add https://github.com/hiroshi75/langgraph-master --skill fine-tune
Please help me install this Agent Skill. Skill: fine-tune Source: https://github.com/hiroshi75/langgraph-master/tree/main/langgraph-master/skills/fine-tune Command: npx skills add https://github.com/hiroshi75/langgraph-master --skill fine-tune
This Skill streamlines the complex and iterative process of optimizing LangGraph application performance by systematically fine-tuning prompts and node logic. It automates the cycle of evaluation, improvement, and re-evaluation, saving developers extensive manual effort in prompt engineering and ensuring data-driven performance gains.
Fine-tune the prompts in your LangGraph application to improve accuracy and reduce latency, following the iterative optimization workflow.
High-intent search queries and answers about installing and using this skill.
Prompt optimization for LangGraph involves iteratively evaluating and refining node prompts to boost accuracy, reduce latency, or lower cost without changing the graph structure. This Skill automates baseline evaluation, identifies optimization targets, suggests prompt improvements, and validates results through statistical analysis across multiple runs.
Yes. This Skill focuses exclusively on optimizing prompts and per-node processing logic while preserving your graph architecture. It runs measurement-driven improvement cycles to achieve quantifiable gains in accuracy, latency, and cost without modifying nodes or edges.
Statistical evaluation with multiple runs ensures reliable, significant results. This Skill performs baseline and post-improvement evaluations using sklearn, scipy, and numpy to measure performance deltas and confirm whether optimizations meet your defined targets.
Iterative optimization automates the evaluation-improvement-reevaluation cycle with data-driven feedback, eliminating manual guesswork. This Skill tracks metrics across phases, documents changes, and suggests evidence-backed prompt revisions to systematically reach performance targets.
It works with existing LangGraph applications as-is. The Skill integrates into preparation, baseline evaluation, iterative improvement, and documentation workflows without requiring graph restructuring, making it suitable for chatbots, retrieval systems, and other LangGraph use cases.
Prepare baseline evaluation data with measurable metrics aligned to your goals—accuracy scores, latency measurements, or cost figures. The Skill requires this ground truth to establish baselines, identify optimization targets, and validate that refined prompts and node logic deliver measurable improvements.
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