
prp-manager
by willywg
Agent Skill for creating and executing PRPs (Product Requirements Prompts) using Context Engineering principles. Works with Claude Code, Cursor, Windsurf, and other compatible agents.
SKILL.md
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
- Context is King: Include ALL necessary documentation, examples, and caveats
- Validation Loops: Provide executable tests/lints the AI can run and fix
- Information Dense: Use keywords and patterns from the codebase
- Progressive Success: Start simple, validate, then enhance
- 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.mddoesn'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
Score
Total Score
Based on repository quality metrics
SKILL.mdファイルが含まれている
ライセンスが設定されている
100文字以上の説明がある
GitHub Stars 100以上
1ヶ月以内に更新
10回以上フォークされている
オープンIssueが50未満
プログラミング言語が設定されている
1つ以上のタグが設定されている
Reviews
Reviews coming soon
