Expert prompt engineering for AI systems. Use when the user wants to write or review prompts for AI, create instructions for AI systems, build system prompts, review or improve existing prompts, optimize AI instructions, or create any form of written communication intended for AI consumption (Claude, GPT, or other LLMs).
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# Prompt Engineer
This skill helps create high-quality prompts and instructions for AI systems by treating AI as a genius human teammate who needs clear, context-rich communication.
## Core Philosophy
This skill is built on two foundational principles:
1. **The Genius Intern Framework**: Treat AI like a brilliant generalist who can figure things out but needs context about what "good" looks like in your specific situation
2. **Async Remote Teammate**: Write for AI the way you'd write for a smart remote colleague—clear, comprehensive, and decisively opinionated
Modern AI models have both high intelligence and high emotional intelligence. They don't need tricks or "prompt engineering hacks"—they need what any smart remote teammate needs: clear written communication with sufficient context.
## Reference Materials
This skill includes three core reference documents. Read them in full as needed:
### Always Load First
**[Writing for AI Teammates](./reference/writing_for_ai_teammates.md)** - Core philosophy covering:
- Why "prompt engineering" is about clear writing, not tricks
- The 37signals parallel (async remote culture)
- Brevity-clarity balance
…
The line at the top of this page pins the label git:20260303.cf416f2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
A 17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (5154 bytes)
pass: No zero-width or bidi control characters
pass: No instruction hidden inside an HTML comment
pass: No link to an exfiltration or paste host
pass: No credential-shaped string
pass: No instruction to send local credentials anywhere
pass: No text hidden with inline styles
pass: No prompt-injection phrasing
pass: No curl or wget piped into a shell
pass: No recursive delete of root, home or parent
pass: No instruction to read or print local credentials
pass: No base64 blob over 200 characters
pass: No link to a raw IP address
pass: No script tag
Source
GitHub
szoloth/skill-pack · 14 stars · license MIT · pushed 2026-09-09 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_zquqiwgtvj52rnzv
GET https://markdownregistry.com/api/v1/resolve?ref=szoloth/skill-pack/prompt-engineer
GET https://markdownregistry.com/api/v1/blob/9769dc6eb4ee1dccd674da0112e9901669e7f558718868bcd24aef288e963d72
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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