PRD Mastery: Context-Aware, Expert-Driven, and Token-Efficient Refinement

Generate context-aware PRDs with MoSCoW-style structured requirements.

Updated Mar 26, 2026
One-click install
npx skills add https://github.com/moughamir/justwaitit-review --skill prd-mastery-context-aware-expert-driven-and-token-efficient-refinement-moughamir
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: PRD Mastery: Context-Aware, Expert-Driven, and Token-Efficient Refinement
Source: https://github.com/moughamir/justwaitit-review/tree/main/.agents/skills/prd-mastery-context-aware-expert-driven-and-token-efficient-refinement
Command: npx skills add https://github.com/moughamir/justwaitit-review --skill prd-mastery-context-aware-expert-driven-and-token-efficient-refinement-moughamir

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill prevents vague, output-focused PRDs by guiding you to produce context-aware, expert-informed, token-efficient Product Requirements Documents that are easy for teams and AI systems to read, review, and implement.

Core Features & Use Cases

  • Context-aware PRD creation: Runs repository reconnaissance to determine whether the project is new or existing, detect the tech stack, and capture architecture and integration context.
  • Expert-driven requirement discovery: Uses questioning frameworks inspired by Marty Cagan, Teresa Torres, and George Biddle to move from problem to outcomes to scoped requirements.
  • Token-efficient PRD structure: Produces an AI-friendly MoSCoW-style requirements layout with concise, scannable sections (targeting ~600–1200 tokens for the PRD body).
  • PRD organization and templates: Establishes a consistent folder structure plus reusable templates for PRD, research, and technical specifications.

Core use cases:

  • Creating a PRD for a new feature with the right scope, outcomes, risks, and success metrics.
  • Refining requirements for an existing feature by aligning with current architecture and constraints.
  • Driving architecture or workflow changes with traceable decisions and supporting research.

Quick Start

Use the PRD Mastery workflow to run repository reconnaissance and then generate a new PRD folder pre-filled with a token-efficient template for your chosen feature.

Frequently Asked Questions about PRD Mastery: Context-Aware, Expert-Driven, and Token-Efficient Refinement

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

FAQPage Schema
How do I write a product requirements document that AI systems can easily parse?

Writing a product requirements document for AI systems requires a token-efficient MoSCoW-style structure with concise, scannable sections. This ensures the PRD body stays between 600–1200 tokens, making it easy for AI and human reviewers to parse outcomes, requirements, and risks.

What's the best way to create a PRD for an existing software feature?

The best way to create a PRD for an existing feature is to run repository reconnaissance to capture current architecture and integration context. This allows you to apply expert-driven questioning frameworks that align stakeholder requirements with technical constraints.

Do I need to run repository reconnaissance before generating a PRD?

Yes, repository reconnaissance is required to generate a prelim_summary.md file capturing the tech stack and architecture context. This preliminary summary provides the foundational project insights needed to produce context-aware and expert-driven product requirements.

How does the MoSCoW method apply to product discovery and feature refinement?

The MoSCoW method structures product discovery by categorizing requirements into Must-have, Should-have, Could-have, and Won't-have tiers. This creates a token-efficient layout that moves from problem definition to scoped outcomes, ensuring clear feature refinement.

Can I use this approach to document architecture and workflow changes?

Yes, you can document architecture changes by generating a structured PRD folder with reusable templates for technical specifications and research. This approach ensures workflow changes are captured with traceable decisions, clear risks, and success metrics.