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system-prompts

Generate structured system prompts and agent definitions using XML-like tags.

Updated Aug 23, 2026
Search Tags:#prompt engineering#llm#ai agent#system prompts#tool documentation#xml tags
One-click install
npx skills add https://github.com/thiagobutignon/nooa-the-pragmatic --skill system-prompts-thiagobutignon
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: system-prompts
Source: https://github.com/thiagobutignon/nooa-the-pragmatic/tree/main/.agent/skills/system-prompts
Command: npx skills add https://github.com/thiagobutignon/nooa-the-pragmatic --skill system-prompts-thiagobutignon

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you write clear, effective system prompts, tool documentation, and agent definitions, leveraging research-backed techniques to improve AI performance and consistency.

Core Features & Use Cases

  • Prompt Engineering: Apply validated techniques for higher AI accuracy and reliability.
  • Structured Documentation: Generate well-formatted documentation for tools and agents using XML-like tags.
  • Use Case: You need to define a new AI agent that can analyze code. Use this Skill to structure its role, capabilities, and constraints using the provided templates and tag hierarchy.

Quick Start

Use the system-prompts skill to generate a template for a new agent definition.

Frequently Asked Questions about system-prompts

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

FAQPage Schema
How do I write effective system prompts for an AI agent?▼

Effective system prompts require structured instructions using XML-like tags and empirically validated techniques. This approach reduces ambiguity and provides clear constraints, improving AI accuracy and consistency across various tasks.

What is the best way to structure tool documentation for LLMs?▼

The best way to structure tool documentation is by using a defined XML-like tag hierarchy. This structured format creates clear, concise agent definitions, reducing hallucinations and improving tool invocation reliability.

Why does my AI agent fail to follow complex instructions consistently?▼

AI agents fail when instructions lack structured formatting and validated prompt engineering techniques. Generating prompts with an XML-like tag hierarchy organizes capabilities and constraints, directly resolving consistency issues.

When do I need to use XML tags in prompt engineering?▼

You need XML tags in prompt engineering when defining structured agent roles, capabilities, and constraints. This hierarchical format separates complex instructions clearly, ensuring the LLM processes distinct sections without confusion.

Can I use this to generate definitions for a code analysis AI agent?▼

Yes, you can generate agent definitions for code analysis. It structures the agent's role, capabilities, and constraints using provided templates and a tag hierarchy, ensuring clear and effective instructions for the task.

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