gh-hiroshi75-protografico-protografico/skills/fine-tune/prompt_optimization.md

Prompt Optimization Guide

A comprehensive guide for effectively optimizing prompts in LangGraph nodes.

📚 Table of Contents

This guide is divided into the following sections:

1. Prompt Optimization Principles

Learn the fundamental principles for designing prompts.

2. Prompt Optimization Techniques

Provides a collection of practical optimization techniques (10 techniques).

3. Optimization Priorities

Explains how to apply optimization techniques in order of improvement impact.

🎯 Quick Start

First-Time Optimization

1. Understand the Principles - Learn the basics of clarity, structure, and specificity
2. Start with High-Impact Techniques - Few-Shot Examples, output format structuring, parameter tuning
3. Review Technique Details - Implementation methods and effects of each technique

Improving Existing Prompts

1. Measure Baseline - Record current performance
2. Refer to Priority Guide - Select the most impactful improvements
3. Apply Techniques - Implement one at a time and measure effects
4. Iterate - Repeat the cycle of measure, implement, validate

📖 Related Documentation

• Prompt Optimization Examples - Before/After comparison examples and code templates
• SKILL.md - Overview and usage of the Fine-tune skill
• evaluation.md - Evaluation criteria design and measurement methods

💡 Best Practices

For effective prompt optimization:

1. ✅ Measurement-Driven: Evaluate all changes quantitatively
2. ✅ Incremental Improvement: One change at a time, measure, validate
3. ✅ Cost-Conscious: Optimize with model selection, caching, max_tokens
4. ✅ Task-Appropriate: Select techniques based on task complexity
5. ✅ Iterative Approach: Maintain continuous improvement cycles

🔍 Troubleshooting

Low Prompt Quality

→ Review Prompt Optimization Principles

Insufficient Accuracy

→ Apply Few-Shot Examples or Chain-of-Thought

High Latency

→ Implement Temperature/Max Tokens Adjustment or Output Format Structuring

High Cost

→ Introduce Model Selection Optimization or Prompt Caching

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💡 Tip: For before/after prompt comparison examples and code templates, refer to examples.md.