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prompt-optimizer

Optimize Claude Code agent system prompts through phased analysis and human approval.

898|134|Updated Jul 28, 2025
Search Tags:#best practices#workflow automation#prompt engineering#Claude#system prompt#agent development#AI optimization
One-click install
npx skills add https://github.com/solatis/claude-config --skill prompt-optimizer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-optimizer
Source: https://github.com/solatis/claude-config/tree/main/skills/prompt-engineer
Command: npx skills add https://github.com/solatis/claude-config --skill prompt-optimizer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Crafting effective AI prompts is challenging and time-consuming, often leading to suboptimal AI performance. This Skill eliminates the guesswork, ensuring your Claude agents receive optimal instructions for peak performance, saving you effort and improving AI reliability.

Core Features & Use Cases

  • Pattern-Driven Optimization: Systematically applies industry-proven prompt engineering patterns to enhance clarity, safety, and efficiency.
  • Two-Phase Analysis: Deconstructs prompts section-by-section, then integrates changes for global coherence and consistency.
  • Transparent Attribution: Every modification is explicitly linked to a specific pattern, rationale, and expected impact, providing an auditable trail.
  • Use Case: A software engineer is developing a complex Claude Code agent for automated code refactoring. They use this Skill to refine the agent's system prompt, ensuring it adheres to best practices for tool use, error handling, and output formatting, leading to more reliable and accurate refactoring suggestions.

Quick Start

Optimize this system prompt for my Claude agent: You are a helpful coding assistant. Your task is to refactor Python code. Always prioritize readability and maintain PEP8 standards.

Frequently Asked Questions about prompt-optimizer

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

FAQPage Schema
How do I optimize system prompts for Claude agents?▼

Optimize system prompts by systematically applying prompt engineering patterns to enhance clarity, safety, and efficiency. This Skill deconstructs your prompt section-by-section, applies industry-proven patterns, and provides transparent attribution for every change, ensuring your Claude agent receives optimal instructions for peak performance.

What's the best way to refine Claude agent instructions for better behavior?▼

Refine agent instructions through a phase-based analysis workflow: triage the prompt, understand its structure and intent, then plan and integrate improvements. Pattern-driven optimization ensures changes align with best practices for tool use, error handling, and output formatting across both single-shot and multi-turn contexts.

Can I improve my AI agent's performance through prompt engineering?▼

Yes. Prompt engineering directly improves agent performance by clarifying instructions, reducing ambiguity, and aligning behavior with best practices. This Skill automates that refinement process, eliminating guesswork and ensuring your Claude agent operates reliably with enhanced clarity and consistency.

How do I know which parts of my agent prompt need improvement?▼

A two-phase analysis deconstructs your prompt to identify gaps in clarity, safety, and efficiency. Each modification links explicitly to a specific pattern, rationale, and expected impact, providing an auditable trail so you understand exactly why and where improvements apply.

What should I do after optimizing my system prompt?▼

After optimization, integrate the refined prompt into your agent workflow. Human approval is required before integration to ensure the changes align with your specific use case, tool requirements, and operational context.

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