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UtakataKyosui
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poml-guide

Explain POML syntax, tags, design patterns, and CLI validation.

Updated Aug 27, 2026
Search Tags:#developer tools#prompt engineering#ai#llm#poml#markup language
One-click install
npx skills add https://github.com/UtakataKyosui/C2Lab --skill poml-guide
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: poml-guide
Source: https://github.com/UtakataKyosui/C2Lab/tree/main/plugins/poml-assist/skills/poml-guide
Command: npx skills add https://github.com/UtakataKyosui/C2Lab --skill poml-guide

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps users understand and effectively use Microsoft's Prompt Orchestration Markup Language (POML) for designing and managing AI prompts.

Core Features & Use Cases

  • POML Syntax & Reference: Provides detailed explanations of POML tags, attributes, and structure.
  • Prompt Design Patterns: Offers practical examples and templates for common AI tasks like summarization, classification, and data extraction.
  • Validation & Rendering: Guides users on how to validate and render POML files using the CLI.
  • Use Case: A developer needs to create a complex prompt for an AI agent. They can use this Skill to quickly look up the correct POML tags for defining roles, tasks, and output formats, and apply pre-built patterns for efficiency.

Quick Start

Use the poml-guide skill to learn about the <role> tag in POML.

Frequently Asked Questions about poml-guide

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

FAQPage Schema
What is POML and what is it used for in prompt engineering?▼

POML is Microsoft's Prompt Orchestration Markup Language used to design and manage AI prompts. It provides a structured syntax with tags for defining roles, tasks, and output formats to orchestrate AI agent instructions.

How do I validate and render POML files?▼

You validate and render POML files using the POML CLI. The CLI processes the markup language files, checking the tag structure and generating the final rendered prompt output for your AI workflows.

What design patterns are available for AI tasks in POML?▼

POML offers practical design patterns and templates for common AI tasks like summarization, classification, and data extraction. These pre-built patterns provide structured examples to efficiently build effective prompts.

Can I define specific AI agent roles and output formats using POML tags?▼

Yes, you can use POML tags to define specific roles, tasks, and output formats for AI agents. The markup language provides specific tag attributes to structure these elements within your prompt design.

Do I need prior knowledge of markup languages to use POML?▼

Familiarity with markup languages helps when using POML. The guide provides comprehensive syntax references and structured examples, making it accessible for developers learning prompt engineering workflows.

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