What is the Prompt Optimizer skill?

Prompt Optimizer is a specialized skill for Claude Code that helps users create highly effective prompts by applying 57 different proven prompt engineering frameworks.

Can it help with image generation prompts?

Yes, the skill includes specific support for 'Atomic Prompting,' a framework specifically designed for optimizing image generation instructions.

How does it decide which framework to use?

The skill analyzes the complexity of your request (simple, medium, or complex) and the domain (such as Marketing, Coding, or Education) to match the most suitable framework for the task.

Does it work for complex reasoning tasks?

Absolutely. For complex logic or analysis, it utilizes frameworks like Chain of Thought or Tree of Thought to ensure the AI follows a step-by-step reasoning process.

Which frameworks does this skill support?

It supports a wide range of frameworks including simple ones like APE and RTF, medium complexity ones like RACE and SMART, and advanced frameworks like CRISPE, RACEF, and Chain of Thought.

Prompt Optimizer

Name: Prompt Optimizer
Author: chujianyun

bychujianyun

•

104

Productividad y Flujo de Trabajo

Optimizes AI prompts using 57 proven engineering frameworks to maximize the quality and accuracy of LLM responses.

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Prompt Optimizer is a comprehensive prompt engineering skill for Claude Code designed to transform vague or basic requests into high-performance AI instructions. By leveraging a library of 57 specialized frameworks—ranging from simple structures like APE and TAG to complex systems like CRISPE and RACEF—the skill systematically analyzes your intent, clarifies ambiguities, and selects the optimal framework for your specific domain. Whether you are drafting marketing copy, performing complex data analysis, or generating code, this skill ensures your prompts are structured for maximum clarity, context, and output quality.

Características Principales

Complexity-based framework selection from Simple to Complex (6+ elements)
Library of 57 industry-standard prompt engineering frameworks
104 GitHub stars
Domain-specific optimization for marketing, education, and development
Interactive clarification process to resolve ambiguous requirements
Iterative refinement workflow for continuous prompt improvement

Casos de Uso

Optimizing complex reasoning tasks using Chain of Thought or Tree of Thought
Crafting high-conversion marketing prompts using BAB or SPEAR frameworks
Converting brief ideas into structured, professional system prompts

Acerca de

Características Principales

Complexity-based framework selection from Simple to Complex (6+ elements)
Library of 57 industry-standard prompt engineering frameworks
104 GitHub stars
Domain-specific optimization for marketing, education, and development
Interactive clarification process to resolve ambiguous requirements
Iterative refinement workflow for continuous prompt improvement

Casos de Uso

Optimizing complex reasoning tasks using Chain of Thought or Tree of Thought
Crafting high-conversion marketing prompts using BAB or SPEAR frameworks
Converting brief ideas into structured, professional system prompts