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product-documenter

Transform raw product context into RAG-ready Markdown documentation with YAML metadata.

Updated Apr 5, 2026
Search Tags:#documentation#context#rag#product#summaries#documenter
One-click install
npx skills add https://github.com/joleques/northstar-ai --skill product-documenter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: product-documenter
Source: https://github.com/joleques/northstar-ai/tree/main/.codex/skills/product-documenter
Command: npx skills add https://github.com/joleques/northstar-ai --skill product-documenter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Transforms raw product context into canonical, RAG-ready documentation for AI agents.

Core Features & Use Cases

  • Loads interview context and consolidated artifacts
  • Generates structured Markdown docs with YAML frontmatter for each section
  • Produces a README index and per-section summaries
  • Supports Mermaid diagrams for architecture where possible

Quick Start

Provide the product title and context, then trigger the skill to generate the docs at /documentacao/{titulo}/docs.

Frequently Asked Questions about product-documenter

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

FAQPage Schema
How do I generate RAG-ready product documentation from raw context?▼

To generate RAG-ready product documentation, provide your raw product context and title, then trigger the skill to output canonical Markdown files with YAML metadata and per-section summaries at /documentacao/{titulo}/docs.

How do I structure product docs for AI agents using RAG?▼

Structuring product docs for AI agents requires applying a standard Markdown format with YAML frontmatter, separating Theory and Practical sections, and generating a README index with per-section summaries.

Does the product documenter require interview outcomes and consolidated artifacts before generating docs?▼

Yes, generating documentation requires existing interview outcomes and consolidated artifacts as input context to transform them into the canonical RAG format with structured Markdown and YAML metadata.

Can I include architecture diagrams in the generated product documentation?▼

Yes, the documentation generation supports optional Mermaid diagrams for architecture visualization directly within the structured Markdown output to enhance context for AI agents.

What is the best way to transform raw product context into canonical Markdown for AI retrieval?▼

The best way to transform raw context into canonical Markdown is enforcing strict adherence to the Documentador RAG format, generating structured docs with Theory/Practical sections and YAML metadata for optimal AI retrieval.

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