name: prp-manager
description: Create and execute PRPs (Product Requirements Prompts) for feature implementation using Context Engineering principles. Use when planning new features, initializing PRP setup, executing existing PRPs, or when the user mentions "PRP", "feature planning", "implementation blueprint", or "context engineering". Helps achieve one-pass implementation success.
license: MIT
compatibility: Works with any agent supporting the Agent Skills specification. Requires file system access.
metadata:
author: willywg
version: "1.0"

PRP Manager Skill

Purpose

Create comprehensive PRPs (Product Requirements Prompts) that enable AI agents to implement features with sufficient context and validation loops for one-pass implementation success.

When to Use

• Initialize: Setting up PRPs for a new project (creates custom template)
• Generate: Planning a new feature or enhancement
• Execute: Implementing an existing PRP file

Core Principles

1. Context is King: Include ALL necessary documentation, examples, and caveats
2. Validation Loops: Provide executable tests/lints the AI can run and fix
3. Information Dense: Use keywords and patterns from the codebase
4. Progressive Success: Start simple, validate, then enhance
5. One-Pass Success: Goal is working code through comprehensive context

References

• Default Template: See assets/templates/prp_base.md
• Usage Examples: See references/examples.md
• Customization Guide: See references/customization.md
• Project Template: PRPs/templates/prp_base.md (generated per project)

Workflow 1: Initialize PRPs (RECOMMENDED FIRST)

Run this first in any new project to create a customized PRP template.

When to Suggest

• User asks to create a PRP but PRPs/templates/prp_base.md doesn't exist
• User explicitly asks to initialize or setup PRPs
• First time using PRPs in a project

Step 1: Analyze Project

Read these files (in order of priority):

AI Agent Configuration:
  - AGENTS.md                              # Universal AI agent guidance (agents.md standard)
  - CLAUDE.md or .claude/settings.json    # Claude-specific rules
  - GEMINI.md                              # Gemini-specific rules

Project Documentation:
  - README.md                              # Project overview
  - CONTRIBUTING.md                        # Contribution guidelines

Package/Dependencies:
  - package.json                           # Node.js projects
  - pyproject.toml or requirements.txt     # Python projects
  - Cargo.toml                             # Rust projects
  - go.mod                                 # Go projects

Code Quality:
  - .eslintrc* / biome.json               # JS/TS linting
  - ruff.toml / pyproject.toml [ruff]     # Python linting
  - mypy.ini / pyproject.toml [mypy]      # Python type checking
  - tsconfig.json                          # TypeScript config

Testing:
  - jest.config.* / vitest.config.*       # JS/TS testing
  - pytest.ini / pyproject.toml [pytest]  # Python testing
  - tests/ or __tests__/ structure        # Test patterns

Step 2: Detect Stack & Conventions

Extract from analysis:
- Language/Framework (Python/FastAPI, Node/Express, etc.)
- Package manager (uv, npm, pnpm, yarn, cargo)
- Linting tools and commands
- Type checking tools and commands
- Testing framework and commands
- Project structure conventions
- Any special rules from AGENTS.md/CLAUDE.md/GEMINI.md

Step 3: Generate Custom Template

Create directory and template:

mkdir -p PRPs/templates

Generate PRPs/templates/prp_base.md with:
- Project-specific validation commands
- Correct package manager syntax
- Actual linting/testing tools used
- Codebase tree format matching project structure
- Any gotchas from AGENTS.md/CLAUDE.md/GEMINI.md
- Test patterns from existing tests

Step 4: Confirm Setup

Output created:
- PRPs/templates/prp_base.md - Customized for this project

Summary to user:
- Stack detected
- Validation commands configured
- Any special rules applied
- Ready to generate PRPs

Workflow 2: Generate PRP

Pre-check

If PRPs/templates/prp_base.md doesn't exist:

"I notice this project doesn't have a PRP template yet. Would you like me to initialize PRPs first? This will create a customized template based on your project's stack and conventions."

Step 1: Understand the Request

• What is the feature/enhancement?
• What is the expected end state?
• Any specific patterns to follow?

Step 2: Research Phase

Codebase Analysis:
- Search for similar features/patterns
- Identify files to reference
- Note existing conventions
- Check test patterns

External Research (if needed):
- Library documentation (include URLs)
- Implementation examples
- Best practices and pitfalls

Step 3: Generate the PRP

Check existing PRPs:

ls -1 PRPs/*.md 2>/dev/null | grep -E '^PRPs/[0-9]{3}--' | sort -r | head -5

Naming: PRPs/{NNN}--{feature-name}.md
- 3-digit padding (001, 002, ...)
- kebab-case for feature name

Use template from: PRPs/templates/prp_base.md

Step 4: Quality Check

• [ ] All context included for one-pass implementation
• [ ] Validation gates are executable
• [ ] References existing patterns
• [ ] Clear implementation path
• [ ] Gotchas documented

Score (1-10): Confidence for one-pass success

Workflow 3: Execute PRP

Step 1: Load and Understand

• Read PRP completely
• Understand all context
• Extend research if gaps found

Step 2: Plan

• Think before executing
• Break into manageable steps
• Use task tracking if available
• Identify patterns from existing code

Step 3: Execute

• Follow implementation blueprint
• Implement in task order
• Mark tasks as completed

Step 4: Validate

• Run each validation command
• Fix failures
• Re-run until all pass

Step 5: Complete

• All checklist items done
• Final validation suite passed
• Re-read PRP to verify
• Report completion status

Best Practices

DO:
- Initialize PRPs first for new projects
- Include comprehensive context for AI agents
- Reference real files and patterns
- Provide executable validation commands
- Document known gotchas
- List tasks in execution order

DON'T:
- Skip initialization (generic template is less effective)
- Create new patterns when existing ones work
- Skip validation
- Ignore failing tests
- Hardcode values that should be config

Output Summary

For Initialize

✅ PRPs Initialized for [Project Name]

Stack Detected:
- Language: Python 3.11
- Framework: FastAPI
- Package Manager: uv
- Linting: ruff
- Type Checking: mypy
- Testing: pytest

Created:
- PRPs/templates/prp_base.md

Ready to generate PRPs!

For Generate

📄 PRPs/005--feature-name.md

Confidence: 8/10
Key Notes: [implementation highlights]

For Execute

✅ PRP Execution Complete

Tasks: 5/5 completed
Validation: All passing
Status: SUCCESS