prompt-improver

Analyze AI prompts for clarity and generate refined versions.

1|Updated Feb 13, 2026
One-click install
npx skills add https://github.com/vuthuonghai-steve/KLTN-By_Thuong_Hai-Steve --skill prompt-improver-vuthuonghai-steve
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: prompt-improver
Source: https://github.com/vuthuonghai-steve/KLTN-By_Thuong_Hai-Steve/tree/main/.codex/skills/prompt-improver
Command: npx skills add https://github.com/vuthuonghai-steve/KLTN-By_Thuong_Hai-Steve --skill prompt-improver-vuthuonghai-steve

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps you overcome the challenge of poorly performing AI prompts that lead to misunderstandings, incorrect outputs, or wasted time. It refines your prompts to ensure AI agents understand and execute your requests accurately and efficiently.

Core Features & Use Cases

  • Prompt Analysis: Identifies ambiguity, missing context, and structural issues in existing prompts.
  • Improvement Suggestions: Offers concrete ways to enhance prompts using frameworks like CRISPE and context layering.
  • Template Generation: Provides structured templates for creating high-quality, new prompts.
  • Use Case: If an AI agent consistently misunderstands your instructions for code generation, use this Skill to analyze your prompt, identify the flaws, and generate an optimized version that leads to correct and efficient code.

Quick Start

Use the prompt-improver skill to analyze and improve the prompt: "Make the code better".

Frequently Asked Questions about prompt-improver

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

FAQPage Schema
How do I optimize AI prompts to fix incorrect code generation outputs?

To optimize AI prompts for code generation, you analyze existing prompts for ambiguity and missing context, then apply structured frameworks like CRISPE and context layering to generate refined versions that yield accurate results.

What is prompt analysis and how does it improve LLM interaction?

Prompt analysis improves LLM interaction by identifying structural issues, missing information, and complex requirements in your instructions, allowing you to apply actionable techniques that ensure the AI agent understands and executes requests accurately.

What's the best way to structure AI prompts for complex software engineering requirements?

The best way to structure complex AI prompts is using generated prompt templates and context layering techniques, which provide clear instructions and structured requirements that prevent AI agents from misunderstanding your software engineering requests.

Can I use prompt templates for new AI agent interactions without starting from scratch?

Yes, you can use generated prompt templates for new AI agent interactions. The skill provides structured templates designed to create high-quality prompts, ensuring clear context and minimizing wasted time from poorly performing instructions.

Why does an AI agent consistently misunderstand my instructions despite clear requirements?

An AI agent misunderstands instructions when prompts contain hidden ambiguity, missing context, or structural flaws. Analyzing the prompt identifies these specific issues and generates an optimized version for better AI interaction.