How does it improve my original prompt?

The skill adds persona context, identifies missing requirements, organizes the task into logical sections, and applies advanced techniques like chain-of-thought reasoning to improve output accuracy.

What makes an 'optimized' prompt better?

Optimized prompts reduce AI hallucinations, ensure consistent formatting, and provide the model with the necessary context to complete complex tasks correctly on the first try.

What does the Prompt Improver skill do?

It is a specialized capability for Claude Code that takes unrefined user inputs and transforms them into structured, high-quality AI prompts using industry best practices.

Do I need to be a prompt engineer to use this?

Not at all. This skill is designed specifically to help users without technical prompt engineering experience generate professional-grade instructions.

Can I use the output prompts with other AI models?

Yes. While the skill is optimized for Claude's specific strengths (like XML tag usage), the resulting prompts follow general best practices that improve performance on GPT-4, Gemini, and other LLMs.

Prompt Improver

Name: Prompt Improver
Author: dazuck

bydazuck

•

Productividad y Flujo de Trabajo

Transforms rough task descriptions into optimized, high-performance AI instructions using proven prompt engineering frameworks.

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The Prompt Improver skill streamlines the process of communicating with AI by converting vague or unstructured requests into clear, effective instructions. By applying strategic structures—such as persona context, XML delimiters, and step-by-step reasoning—it ensures that Claude delivers more accurate and relevant outputs. This skill is ideal for operators and developers who want to move beyond basic chatting and build repeatable, high-quality AI workflows by leveraging professional-grade prompting techniques automatically.

Características Principales

Uses advanced techniques like XML tagging and chain-of-thought reasoning
Identifies and prompts for missing context or ambiguous requirements
Provides a standardized template for consistent AI performance across tasks
Automatically injects relevant persona and domain expertise context
Converts single-sentence tasks into detailed, structured instruction sets
7 GitHub stars

Casos de Uso

Refining vague content requests into detailed creative briefs with specific constraints
Converting business requirements into technical specification prompts for coding tasks
Transforming rough data analysis goals into structured analytical frameworks

Acerca de

Características Principales

Uses advanced techniques like XML tagging and chain-of-thought reasoning
Identifies and prompts for missing context or ambiguous requirements
Provides a standardized template for consistent AI performance across tasks
Automatically injects relevant persona and domain expertise context
Converts single-sentence tasks into detailed, structured instruction sets
7 GitHub stars

Casos de Uso

Refining vague content requests into detailed creative briefs with specific constraints
Converting business requirements into technical specification prompts for coding tasks
Transforming rough data analysis goals into structured analytical frameworks