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prompt-improver

Rewrite ambiguous prompts into clear, specific instructions for AI models.

Updated Aug 23, 2026
Search Tags:#clarity#AI#prompt-engineering#specificity#rewrite#prompt-improvement
One-click install
npx skills add https://github.com/dragonkid/dotfiles --skill prompt-improver-dragonkid
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-improver
Source: https://github.com/dragonkid/dotfiles/tree/main/claude/skills/prompt-improver
Command: npx skills add https://github.com/dragonkid/dotfiles --skill prompt-improver-dragonkid

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps users transform vague, ambiguous prompts into clear, specific, and actionable instructions for AI models, reducing misinterpretation and the need for repeated iterations.

Core Features & Use Cases

  • Analyze the original prompt to identify task goals, missing context, and areas of ambiguity.
  • Apply an explicit optimization framework (instruction-first, role/context, conciseness, precise task definitions, and clear output formats) to rewrite prompts.
  • Verify the improved prompt for clarity and determinism, then present the updated version with guidance on how to use it in real workflows.

Quick Start

Use the prompt-improver to rewrite the following prompt into a clearer, more actionable instruction: "Explain photosynthesis in simple terms."

Frequently Asked Questions about prompt-improver

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

FAQPage Schema
How do I improve prompt clarity and specificity for AI requests?▼

To improve prompt clarity, the prompt-improver applies an optimization framework to rewrite vague instructions, adding role, context, and precise output formats. It analyzes the original prompt to identify missing context and ambiguity, yielding actionable AI instructions.

What is the best way to rewrite vague prompts for AI models?▼

The best way to rewrite vague prompts is using an instruction-first framework that adds role, context, and clear output formats. This deterministic rewriting process transforms ambiguous requests into precise task definitions, reducing misinterpretation and repeated iterations.

Can I use prompt engineering optimization for coding and data tasks?▼

Yes, prompt engineering optimization applies to coding and data tasks. The framework rewrites instructions to include precise task definitions and clear output formats, ensuring AI models receive specific guidance for writing, coding, and data processing workflows.

Why does my AI prompt return misinterpreted or irrelevant results?▼

AI prompts return misinterpreted results due to missing context, ambiguous instructions, and undefined output formats. The prompt-improver analyzes original prompts to identify these gaps, applying an explicit optimization framework to rewrite instructions for determinism.

Does prompt rewriting work without providing additional context?▼

Prompt rewriting works best when analyzing the original prompt to identify missing context and areas of ambiguity. The framework applies instruction-first design, role definition, and concise task definitions to generate clear, actionable instructions for AI workflows.

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