prompt-engineer

Edit, upgrade, and validate Claude prompt definitions in CLAUDE.md, SKILL.md, and slash commands.

3|Updated Sep 13, 2019
One-click install
npx skills add https://github.com/MH4GF/dotfiles --skill prompt-engineer-mh4gf
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: prompt-engineer
Source: https://github.com/MH4GF/dotfiles/tree/main/.claude/skills/prompt-engineer
Command: npx skills add https://github.com/MH4GF/dotfiles --skill prompt-engineer-mh4gf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill eliminates the guesswork and trial-and-error in crafting effective prompts for Claude. It helps users overcome challenges like vague instructions, inconsistent outputs, and inefficient AI interactions, ensuring Claude understands and executes tasks precisely.

Core Features & Use Cases

  • Prompt Optimization: Analyzes and refines existing prompts for clarity, conciseness, and adherence to Claude's best practices, leading to more accurate and efficient AI responses.
  • New Prompt Generation: Guides the creation of CLAUDE.md, SKILL.md, and custom slash commands from scratch, establishing robust AI workflows.
  • Structured Prompting: Teaches and applies techniques like XML tagging, specific constraints, and output format definitions to achieve highly predictable and desired outcomes from Claude.
  • Use Case: You're developing a new feature and need Claude to generate unit tests. Instead of struggling with a generic prompt, use this Skill to craft a highly specific prompt that includes code style guidelines, mocking instructions, and desired test coverage, ensuring the generated tests are immediately usable.

Quick Start

Help me improve the attached prompt for Claude. I want it to generate a concise summary of a technical document, focusing on key findings and action items, and output it in Markdown format.

Frequently Asked Questions about prompt-engineer

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

FAQPage Schema
How do I write better prompts for Claude to get more consistent results?

Structure prompts using XML tags like <task>, <context>, and <output_format> to define instructions clearly. Imperative language, explicit constraints, and machine-readable formatting ensure Claude understands and executes tasks precisely, reducing trial-and-error and inconsistent outputs.

What's the best way to optimize existing Claude prompts for my workflow?

Analyze prompts for clarity, conciseness, and adherence to Claude best practices. Apply standardized section tags, enforce imperative language, define output formats explicitly, and validate against Claude Code conventions to improve accuracy and integration with RAG pipelines.

How do I create a CLAUDE.md or SKILL.md file that Claude can reliably follow?

Use structured prompting with XML tagging, specific constraints, and explicit output format definitions. Document your workflow in machine-readable format with imperative language and standardized section tags to establish robust, repeatable AI interactions.

Can I automate prompt validation across multiple repositories?

Yes. Apply this Skill to CLAUDE.md, SKILL.md, and custom slash commands across repositories for editing, upgrading, and validating prompt definitions. Enforce consistent formatting, standardized tags, and Claude Code conventions to ensure seamless machine-readability across your project contexts.

What happens if my Claude prompts produce vague or poorly formatted outputs?

Inconsistent outputs typically result from vague instructions or missing output-format definitions. Define explicit formats, use XML structure tags, add constraints, and apply imperative language. This Skill eliminates guesswork by standardizing prompt documentation for predictable Claude behavior.

Do I need prior AI prompt experience to use this Skill effectively?

No. This Skill guides creation of prompts from scratch and teaches structured prompting techniques like XML tagging and constraint definition. It works with any Claude use case and includes quick-start examples for common tasks like generating unit tests or summarizing documents.