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Prompt Refiner

Analyze vague prompts and rewrite them with explanations for each change.

9|1|Updated Mar 15, 2026
Search Tags:#ai#llm#clarification#explanation#multi-environment#prompt-engineering#prompt-refinement
One-click install
npx skills add https://github.com/Notysoty/openagentskills --skill prompt-refiner-notysoty
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Prompt Refiner
Source: https://github.com/Notysoty/openagentskills/tree/main/skills/prompt-refiner
Command: npx skills add https://github.com/Notysoty/openagentskills --skill prompt-refiner-notysoty

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps you rewrite rough or underperforming AI prompts to be clearer, more specific, and more likely to produce consistent, high-quality output from a language model. It identifies the root causes of vague or ineffective prompts — missing context, absent output format specs, ambiguous instructions — and systematically addresses each one. It also explains every change so you can learn the principles, not just get a one-time fix.

Core Features & Use Cases

  • Prompt refinement: Transforms vague prompts into precise, actionable instructions.
  • Educational: Explains every change to teach underlying principles.
  • Cross-environment support: Works with multiple agent ecosystems (Claude Code, Cursor, Codex).
  • Use cases: Improves system prompts, user prompts, and instruction prompts across development, testing, and production contexts.

Quick Start

Copy this file to the appropriate skill directory in your project and paste your prompt to refine, then request a refinement from the Prompt Refiner.

Frequently Asked Questions about Prompt Refiner

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

FAQPage Schema
How do I make my vague LLM prompts clearer and more specific?▼

Prompt refinement analyzes vague instructions to identify missing context, ambiguous phrasing, and absent output formats, rewriting them into precise directives that produce consistent, high-quality outputs from language models.

What is the best way to fix inconsistent AI outputs from my system prompts?▼

Fixing inconsistent AI outputs involves prompt refinement to systematically address missing context, ambiguous instructions, and absent output formats, rewriting your prompts to produce reliable, high-quality results across language models.

How do I refine a prompt for use across multiple agent environments like Claude Code and Cursor?▼

Refining a prompt for multiple agent environments involves systematically addressing missing context and ambiguous instructions to ensure consistent outputs across platforms like Claude Code, Cursor, and Codex.

Can I learn prompt engineering principles while improving my underperforming prompts?▼

Yes, you can learn prompt engineering principles while improving underperforming prompts because the refinement process provides detailed explanations for every change made, teaching the underlying reasoning rather than just offering a one-time fix.

Does prompt refinement work for development, testing, and production contexts?▼

Yes, prompt refinement works for development, testing, and production contexts by systematically analyzing and rewriting vague prompts to ensure consistent, high-quality outputs across various stages of your workflow.

Why does my AI prompt produce unreliable outputs even with detailed instructions?▼

Your AI prompt may produce unreliable outputs due to missing context, absent output formats, or ambiguous instructions, which prompt refinement systematically identifies and rewrites to ensure consistent, high-quality results.

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