Can I use this for writing agent instructions?

Yes, it is specifically designed for writing agent instructions, system prompts, SKILL.md files, and any LLM-to-LLM communication.

Does this skill work for all AI models?

While optimized for the Claude Code ecosystem, the principles of clarity, structural tagging, and goal-orientation are universal best practices for all modern Large Language Models.

Does this skill show what 'not' to do in prompts?

No, it follows a strict principle of showing correct patterns only. This avoids the risk of the model accidentally mimicking anti-patterns even when they are labeled as 'wrong'.

Why does this skill emphasize XML tags?

XML tags provide clear structural boundaries and hierarchy within a prompt, which helps LLMs parse complex instructions and context more accurately.

What is the primary focus of the Writing for LLMs skill?

It focuses on standardizing prompt engineering practices to ensure AI models receive clear, structured, and goal-oriented instructions that improve reasoning and performance.

LLM Prompt Engineering & Writing

Name: LLM Prompt Engineering & Writing
Author: TechNickAI

byTechNickAI

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Data Science & ML

Optimizes the creation of prompts and agent instructions by applying advanced prompt engineering standards and structural patterns.

About

The Writing for LLMs skill is a specialized meta-utility for Claude Code that enforces high-performance prompt engineering standards across all AI-to-AI communications. By focusing on goal-oriented instructions, XML-based structuring, and the elimination of anti-patterns, it enables developers to create more reliable agents, system prompts, and task instructions. This skill is essential for anyone looking to maximize the reasoning capabilities and output quality of large language models by providing them with the clearest possible context and requirements.

Key Features

Enforces strict prompt engineering standards for high-quality outputs
16 GitHub stars
Standardizes terminology and few-shot example formatting for consistency
Prioritizes goal-oriented instructions over over-prescribed processes
Automates XML structural tagging for complex instruction sets
Eliminates anti-patterns by focusing exclusively on correct implementation examples

Use Cases

Drafting system prompts for new LLM-integrated tools or applications
Refining SKILL.md files to ensure high-performance execution within the marketplace
Creating robust agent instructions for specialized Claude Code agents

About

Key Features

Enforces strict prompt engineering standards for high-quality outputs
16 GitHub stars
Standardizes terminology and few-shot example formatting for consistency
Prioritizes goal-oriented instructions over over-prescribed processes
Automates XML structural tagging for complex instruction sets
Eliminates anti-patterns by focusing exclusively on correct implementation examples

Use Cases

Drafting system prompts for new LLM-integrated tools or applications
Refining SKILL.md files to ensure high-performance execution within the marketplace
Creating robust agent instructions for specialized Claude Code agents