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prompt-optimizer

Select and apply an AI-prompt framework to optimize user prompts.

715|98|Updated Dec 19, 2025
Search Tags:#workflow#frameworks#optimization#clarification#prompt-engineering#prompt#domain-coverage
One-click install
npx skills add https://github.com/chujianyun/skills --skill prompt-optimizer-chujianyun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-optimizer
Source: https://github.com/chujianyun/skills/tree/main/skills/prompt-optimizer
Command: npx skills add https://github.com/chujianyun/skills --skill prompt-optimizer-chujianyun

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

The Prompt Optimizer helps users transform vague or poorly structured prompts into precise, actionable requests by selecting and applying the most suitable AI-prompt framework from a curated library of 57 frameworks, ensuring consistent, high-quality outputs across domains.

Core Features & Use Cases

  • Framework selection: choose the best-fit framework based on the task, input complexity, and domain.
  • Framework loading: load detailed guidelines from the references repository (e.g., RACE, CRISPE, ERA, etc.) to guide prompt construction.
  • Ambiguity clarifications: ask targeted questions to resolve missing details before generation.
  • Prompt generation: craft the final optimized prompt, including structure, tone, and formatting aligned with the chosen framework.
  • Iteration workflow: support multi-round refinement and scenario-based adjustments for robust outputs.
  • Domain coverage: applicable to marketing, decision analysis, education, product development, AI dialogue, writing, data analytics, and more.

Quick Start

Provide an optimized prompt by selecting the best framework for the user's task, loading the corresponding framework details from the references, asking clarifying questions if needed, and returning a ready-to-use prompt.

Frequently Asked Questions about prompt-optimizer

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

FAQPage Schema
How do I optimize a prompt using a structured framework?▼

Prompt optimization works by selecting a suitable AI-prompt framework like RACE or CRISPE, loading its detailed guidelines, asking clarifying questions, and generating a precise, ready-to-use prompt.

What is prompt engineering and when do I need a framework for it?▼

Prompt engineering frameworks are needed when transforming vague requests into precise prompts. They provide consistent guidelines for tasks across domains like marketing, data analytics, and education.

Can I use prompt frameworks for different domains like marketing and data analytics?▼

Yes, prompt frameworks support multi-domain coverage including marketing, decision analysis, education, product development, AI dialogue, writing, and data analytics for tailored prompt generation.

What's the best way to refine a prompt that produces inconsistent outputs?▼

The best way to refine inconsistent prompts is using an iterative workflow that applies structured frameworks, asks targeted clarification questions, and supports multi-round scenario adjustments.

How many prompt frameworks are available for prompt optimization?▼

A curated library of 57 prompt frameworks is available, allowing users to select the best-fit framework based on task complexity and domain for high-quality prompt optimization.

Why does my prompt fail to generate the expected output structure?▼

Prompts fail when missing structured guidelines. Loading a specific framework like ERA ensures proper structure, tone, and formatting alignment, while clarifying ambiguities resolves missing details.

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