# Prompt Auto-Optimizer

> Use this tool when you need to optimize prompts for large language models (LLMs) to improve performance and user experience in applications like customer service chatbots and content creation systems. It solves problems of suboptimal prompt quality by automatically evolving and adapting prompts through genetic algorithms and multi-objective optimization. The tool takes in initial prompts and performance feedback as inputs and outputs optimized prompts that can be used in production environments.

Canonical page: https://skillsregistry.net/skills/prompt-auto-optimizer  
JSON: https://api.skillsregistry.net/v1/skills/prompt-auto-optimizer

## Description

GEPA (Genetic Evolutionary Prompt Adaptation) MCP Server provides AI-powered prompt optimization through genetic algorithms, enabling automatic evolution and improvement of prompts across multiple generations. The implementation features multi-objective optimization using Pareto frontiers, trajectory recording for execution analysis, reflection-based failure diagnosis, and automated mutation strategies that adapt prompts based on performance feedback. Built for developers and researchers working with LLM applications, it's particularly valuable for optimizing prompts in production environments where prompt quality directly impacts user experience, such as customer service chatbots, code generation tools, and content creation systems.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-25

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/prompt-auto-optimizer)
- **Repository:** <https://github.com/sloth-wq/prompt-auto-optimizer-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "prompt-auto-optimizer"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/prompt-auto-optimizer` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/prompt-auto-optimizer/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt