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prompt-refiner

Transform vague prompts into structured prompts with objectives, constraints, and acceptance criteria.

5|5|Updated Jan 18, 2019
Search Tags:#workflow#templates#refinement#ai#instruction#prompt-engineering#prompt
One-click install
npx skills add https://github.com/AzureAD/android-complete --skill prompt-refiner-azuread
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-refiner
Source: https://github.com/AzureAD/android-complete/tree/main/.github/skills/prompt-refiner
Command: npx skills add https://github.com/AzureAD/android-complete --skill prompt-refiner-azuread

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill helps transform vague prompts into precise, actionable prompts with clear objectives, constraints, and acceptance criteria, reducing back-and-forth and increasing response quality.

Core Features & Use Cases

  • Prompt refinement: Convert rough requests into structured prompts suitable for AI systems.
  • Template guidance: Provide reference templates for common task types (exploration, feature, bugfix, telemetry).
  • Use Case: A designer describes a task vaguely, and this skill returns a structured prompt ready for use in an AI assistant.

Quick Start

Refine a vague prompt into a structured prompt with clear objectives, constraints, and acceptance criteria.

Frequently Asked Questions about prompt-refiner

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

FAQPage Schema
How do I refine a vague prompt into a structured prompt with clear objectives?▼

Convert rough requests into structured prompts by applying defined objectives, constraints, and acceptance criteria, reducing back-and-forth and increasing response quality.

What is the best way to structure prompts for AI-assisted feature planning and bug fixes?▼

The best way to structure prompts for feature planning and bug fixes is using reference templates that enforce predictable prompt structures, ensuring consistent results across exploration and telemetry scenarios.

Why does my AI assistant return low-quality responses to my rough requests?▼

Low-quality responses often occur because vague prompts lack defined objectives, constraints, and acceptance criteria. Transforming them into structured prompts ensures consistent, high-quality AI outputs.

Can I use prompt templates for exploration and telemetry scenarios?▼

Yes, you can use provided reference templates for exploration, feature planning, bugfix, and telemetry scenarios to ensure consistent AI-assisted prompting workflows.

Does prompt refinement work without writing manual acceptance criteria?▼

Yes, prompt refinement automatically generates acceptance criteria, transforming ill-posed requests into high-quality prompts by defining the necessary constraints and objectives without manual input.

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