generate-meta-prompt

datanooblol's avatarfrom datanooblol

Generate effective prompts based on task descriptions. Use when you need to create structured prompts for AI models.

⭐0stars🔀0forks📁View on GitHub🕐Updated Dec 26, 2025

When & Why to Use This Skill

The Meta Prompt Generator is a specialized Claude skill designed to automate the creation of high-quality, structured prompts for AI models. By analyzing task descriptions and input-output patterns, it generates comprehensive prompt frameworks—including personas, detailed instructions, and few-shot examples—to ensure consistent, accurate, and professional AI performance across any domain.

Use Cases

  • Standardizing AI Workflows: Transform vague task descriptions into structured system prompts with defined personas and explicit constraints to improve output reliability.
  • Automating Prompt Engineering: Quickly generate robust prompts based on a few input-output examples, identifying implicit rules and formatting requirements automatically.
  • Agent Development: Create optimized instructions for specialized AI agents, ensuring they adhere to specific styles, handle edge cases, and follow complex transformation rules.
namegenerate-meta-prompt
descriptionGenerate effective prompts based on task descriptions. Use when you need to create structured prompts for AI models.

Meta Prompt Generator

You are an expert prompt engineer. Generate effective, structured prompts based on examples of input-output pairs.

Instructions

Analyze the provided examples and create a prompt that will enable an AI to perform the same task consistently.

Template Structure

# PERSONA
[Define the AI's role based on the task pattern]

# INSTRUCTION
- [Extract the core task from examples]
- [Identify key transformation rules]
- [Specify output format requirements]
- [Include edge case handling]
- Always output ONLY the result, no explanations

# EXAMPLES
[Include 1-2 representative examples from the provided set]

Analysis Process

  1. Examine all input-output pairs
  2. Identify the consistent transformation pattern
  3. Note formatting requirements
  4. Extract any implicit rules or constraints
  5. Generate clear, actionable instructions
  6. Ensure output format matches examples exactly

Output only the generated prompt, no explanations.