PRP Generator

Overview

Generates comprehensive Product Requirement Plans (PRPs) that enable AI agents to implement features in a single pass. Combines systematic codebase analysis with external research to create detailed, context-rich implementation blueprints.

When to Use

• User requests a PRP, PRD, or detailed implementation plan
• User asks to "plan out" or "design" a complex feature
• Beginning significant feature development that benefits from structured planning
• User provides a feature description file and asks for implementation guidance

Core Principle

Context is Everything: The implementing agent only receives the PRP content, training data knowledge, codebase access, and WebSearch. Your PRP must be self-contained with all necessary context, specific references, and executable validation gates.

Workflow

Phase 1: Understand the Feature

1. Read the feature request - if a file path is given, read it completely; if verbal, clarify requirements
2. Clarify ambiguities - use AskUserQuestion for unclear requirements, confirm tech stack, verify integration points
3. Identify the core problem being solved and acceptance criteria

Phase 2: Codebase Analysis (Mandatory)

Goal: Understand existing patterns, conventions, and integration points.

Systematically analyse the codebase across five dimensions:

For detailed sub-steps, examples, and documentation templates, see references/codebase-analysis-guide.md.

Also refer to references/research_methodology.md for the full research process.

Phase 3: External Research (Mandatory)

Goal: Find best practices, documentation, examples, and gotchas.

Research across four areas:

Always document exact URLs, versions, and specific sections. See references/research_methodology.md for detailed guidance.

Phase 4: Ultra-Thinking (Critical)

STOP AND THINK DEEPLY BEFORE WRITING THE PRP.

Analyse integration points, implementation ordering, validation strategy, and context completeness. Verify the PRP will enable one-pass implementation without questions.

For the full set of analysis questions and the quality checklist, see references/quality-assessment.md.

Phase 5: Generate the PRP

Use assets/prp_template.md as the base structure. Populate all sections:

1. Metadata - feature name, timeline, confidence score (1-10), date
2. Executive Summary - 2-3 sentences with core value proposition
3. Research Findings - codebase analysis (file:line refs) and external research (URLs, versions)
4. Technical Specification - architecture, components, data models, API endpoints
5. Implementation Blueprint - prerequisites, step-by-step with pseudocode, file changes, error handling, edge cases
6. Testing Strategy - unit, integration, and manual testing approaches
7. Validation Gates - must be EXECUTABLE commands (e.g. npm run test && npm run build)
8. Success Criteria - clear, measurable checklist

Phase 6: Quality Scoring

Score the PRP for one-pass implementation success:

If score is below 7: Go back and improve the PRP before delivering.

Phase 7: Save and Deliver

1. Save the PRP to PRPs/[feature-name].md (kebab-case, create directory if needed)
2. Deliver summary to user with: brief feature summary, file location, confidence score with rationale, and next steps

Common Pitfalls

Example Usage

User: "Create a PRP for adding dark mode support to the application"

1. Clarify: "Should dark mode preference persist across sessions? Should it respect system preferences?"
2. Research codebase for theme-related code
3. Research external resources (dark mode best practices, library options)
4. Ultra-think about implementation approach
5. Generate comprehensive PRP using template
6. Score the PRP
7. Save to PRPs/dark-mode-support.md
8. Deliver summary with confidence score

Resources

Key Reminders

• Research is mandatory - never skip codebase or external research
• Be specific - always include file paths, line numbers, URLs, versions
• Think deeply - Phase 4 (Ultra-Thinking) is critical for success
• Validate everything - all validation gates must be executable
• Score honestly - if confidence is below 7, improve the PRP
• Context is king - the implementer only has what you put in the PRP