feat: add rpg method prd example template (#1285)
This commit is contained in:
Ralph Khreish
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.taskmaster/templates/example_prd_rpg.txt
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.taskmaster/templates/example_prd_rpg.txt
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<rpg-method>
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# Repository Planning Graph (RPG) Method - PRD Template
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This template teaches you (AI or human) how to create structured, dependency-aware PRDs using the RPG methodology from Microsoft Research. The key insight: separate WHAT (functional) from HOW (structural), then connect them with explicit dependencies.
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## Core Principles
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1. **Dual-Semantics**: Think functional (capabilities) AND structural (code organization) separately, then map them
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2. **Explicit Dependencies**: Never assume - always state what depends on what
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3. **Topological Order**: Build foundation first, then layers on top
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4. **Progressive Refinement**: Start broad, refine iteratively
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## How to Use This Template
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- Follow the instructions in each `<instruction>` block
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- Look at `<example>` blocks to see good vs bad patterns
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- Fill in the content sections with your project details
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- The AI reading this will learn the RPG method by following along
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- Task Master will parse the resulting PRD into dependency-aware tasks
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## Recommended Tools for Creating PRDs
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When using this template to **create** a PRD (not parse it), use **code-context-aware AI assistants** for best results:
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**Why?** The AI needs to understand your existing codebase to make good architectural decisions about modules, dependencies, and integration points.
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**Recommended tools:**
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- **Claude Code** (claude-code CLI) - Best for structured reasoning and large contexts
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- **Cursor/Windsurf** - IDE integration with full codebase context
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- **Gemini CLI** (gemini-cli) - Massive context window for large codebases
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- **Codex/Grok CLI** - Strong code generation with context awareness
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**Note:** Once your PRD is created, `task-master parse-prd` works with any configured AI model - it just needs to read the PRD text itself, not your codebase.
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</rpg-method>
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---
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<overview>
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<instruction>
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Start with the problem, not the solution. Be specific about:
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- What pain point exists?
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- Who experiences it?
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- Why existing solutions don't work?
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- What success looks like (measurable outcomes)?
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Keep this section focused - don't jump into implementation details yet.
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</instruction>
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## Problem Statement
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[Describe the core problem. Be concrete about user pain points.]
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## Target Users
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[Define personas, their workflows, and what they're trying to achieve.]
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## Success Metrics
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[Quantifiable outcomes. Examples: "80% task completion via autopilot", "< 5% manual intervention rate"]
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</overview>
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---
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<functional-decomposition>
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<instruction>
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Now think about CAPABILITIES (what the system DOES), not code structure yet.
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Step 1: Identify high-level capability domains
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- Think: "What major things does this system do?"
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- Examples: Data Management, Core Processing, Presentation Layer
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Step 2: For each capability, enumerate specific features
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- Use explore-exploit strategy:
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* Exploit: What features are REQUIRED for core value?
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* Explore: What features make this domain COMPLETE?
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Step 3: For each feature, define:
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- Description: What it does in one sentence
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- Inputs: What data/context it needs
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- Outputs: What it produces/returns
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- Behavior: Key logic or transformations
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<example type="good">
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Capability: Data Validation
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Feature: Schema validation
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- Description: Validate JSON payloads against defined schemas
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- Inputs: JSON object, schema definition
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- Outputs: Validation result (pass/fail) + error details
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- Behavior: Iterate fields, check types, enforce constraints
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Feature: Business rule validation
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- Description: Apply domain-specific validation rules
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- Inputs: Validated data object, rule set
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- Outputs: Boolean + list of violated rules
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- Behavior: Execute rules sequentially, short-circuit on failure
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</example>
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<example type="bad">
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Capability: validation.js
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(Problem: This is a FILE, not a CAPABILITY. Mixing structure into functional thinking.)
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Capability: Validation
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Feature: Make sure data is good
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(Problem: Too vague. No inputs/outputs. Not actionable.)
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</example>
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</instruction>
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## Capability Tree
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### Capability: [Name]
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[Brief description of what this capability domain covers]
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#### Feature: [Name]
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- **Description**: [One sentence]
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- **Inputs**: [What it needs]
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- **Outputs**: [What it produces]
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- **Behavior**: [Key logic]
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#### Feature: [Name]
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- **Description**:
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- **Inputs**:
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- **Outputs**:
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- **Behavior**:
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### Capability: [Name]
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...
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</functional-decomposition>
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---
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<structural-decomposition>
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<instruction>
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NOW think about code organization. Map capabilities to actual file/folder structure.
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Rules:
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1. Each capability maps to a module (folder or file)
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2. Features within a capability map to functions/classes
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3. Use clear module boundaries - each module has ONE responsibility
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4. Define what each module exports (public interface)
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The goal: Create a clear mapping between "what it does" (functional) and "where it lives" (structural).
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<example type="good">
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Capability: Data Validation
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→ Maps to: src/validation/
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├── schema-validator.js (Schema validation feature)
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├── rule-validator.js (Business rule validation feature)
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└── index.js (Public exports)
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Exports:
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- validateSchema(data, schema)
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- validateRules(data, rules)
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</example>
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<example type="bad">
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Capability: Data Validation
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→ Maps to: src/utils.js
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(Problem: "utils" is not a clear module boundary. Where do I find validation logic?)
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Capability: Data Validation
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→ Maps to: src/validation/everything.js
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(Problem: One giant file. Features should map to separate files for maintainability.)
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</example>
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</instruction>
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## Repository Structure
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```
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project-root/
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├── src/
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│ ├── [module-name]/ # Maps to: [Capability Name]
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│ │ ├── [file].js # Maps to: [Feature Name]
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│ │ └── index.js # Public exports
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│ └── [module-name]/
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├── tests/
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└── docs/
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```
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## Module Definitions
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### Module: [Name]
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- **Maps to capability**: [Capability from functional decomposition]
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- **Responsibility**: [Single clear purpose]
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- **File structure**:
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```
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module-name/
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├── feature1.js
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├── feature2.js
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└── index.js
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```
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- **Exports**:
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- `functionName()` - [what it does]
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- `ClassName` - [what it does]
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</structural-decomposition>
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---
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<dependency-graph>
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<instruction>
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This is THE CRITICAL SECTION for Task Master parsing.
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Define explicit dependencies between modules. This creates the topological order for task execution.
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Rules:
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1. List modules in dependency order (foundation first)
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2. For each module, state what it depends on
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3. Foundation modules should have NO dependencies
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4. Every non-foundation module should depend on at least one other module
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5. Think: "What must EXIST before I can build this module?"
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<example type="good">
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Foundation Layer (no dependencies):
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- error-handling: No dependencies
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- config-manager: No dependencies
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- base-types: No dependencies
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Data Layer:
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- schema-validator: Depends on [base-types, error-handling]
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- data-ingestion: Depends on [schema-validator, config-manager]
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Core Layer:
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- algorithm-engine: Depends on [base-types, error-handling]
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- pipeline-orchestrator: Depends on [algorithm-engine, data-ingestion]
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</example>
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<example type="bad">
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- validation: Depends on API
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- API: Depends on validation
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(Problem: Circular dependency. This will cause build/runtime issues.)
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- user-auth: Depends on everything
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(Problem: Too many dependencies. Should be more focused.)
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</example>
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</instruction>
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## Dependency Chain
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### Foundation Layer (Phase 0)
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No dependencies - these are built first.
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- **[Module Name]**: [What it provides]
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- **[Module Name]**: [What it provides]
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### [Layer Name] (Phase 1)
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- **[Module Name]**: Depends on [[module-from-phase-0], [module-from-phase-0]]
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- **[Module Name]**: Depends on [[module-from-phase-0]]
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### [Layer Name] (Phase 2)
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- **[Module Name]**: Depends on [[module-from-phase-1], [module-from-foundation]]
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[Continue building up layers...]
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</dependency-graph>
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---
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<implementation-roadmap>
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<instruction>
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Turn the dependency graph into concrete development phases.
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Each phase should:
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1. Have clear entry criteria (what must exist before starting)
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2. Contain tasks that can be parallelized (no inter-dependencies within phase)
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3. Have clear exit criteria (how do we know phase is complete?)
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4. Build toward something USABLE (not just infrastructure)
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Phase ordering follows topological sort of dependency graph.
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<example type="good">
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Phase 0: Foundation
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Entry: Clean repository
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Tasks:
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- Implement error handling utilities
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- Create base type definitions
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- Setup configuration system
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Exit: Other modules can import foundation without errors
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Phase 1: Data Layer
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Entry: Phase 0 complete
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Tasks:
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- Implement schema validator (uses: base types, error handling)
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- Build data ingestion pipeline (uses: validator, config)
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Exit: End-to-end data flow from input to validated output
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</example>
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<example type="bad">
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Phase 1: Build Everything
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Tasks:
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- API
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- Database
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- UI
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- Tests
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(Problem: No clear focus. Too broad. Dependencies not considered.)
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</example>
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</instruction>
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## Development Phases
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### Phase 0: [Foundation Name]
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**Goal**: [What foundational capability this establishes]
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**Entry Criteria**: [What must be true before starting]
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**Tasks**:
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- [ ] [Task name] (depends on: [none or list])
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- Acceptance criteria: [How we know it's done]
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- Test strategy: [What tests prove it works]
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- [ ] [Task name] (depends on: [none or list])
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**Exit Criteria**: [Observable outcome that proves phase complete]
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**Delivers**: [What can users/developers do after this phase?]
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---
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### Phase 1: [Layer Name]
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**Goal**:
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**Entry Criteria**: Phase 0 complete
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**Tasks**:
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- [ ] [Task name] (depends on: [[tasks-from-phase-0]])
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- [ ] [Task name] (depends on: [[tasks-from-phase-0]])
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**Exit Criteria**:
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**Delivers**:
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---
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[Continue with more phases...]
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</implementation-roadmap>
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---
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<test-strategy>
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<instruction>
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Define how testing will be integrated throughout development (TDD approach).
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Specify:
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1. Test pyramid ratios (unit vs integration vs e2e)
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2. Coverage requirements
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3. Critical test scenarios
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4. Test generation guidelines for Surgical Test Generator
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This section guides the AI when generating tests during the RED phase of TDD.
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<example type="good">
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Critical Test Scenarios for Data Validation module:
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- Happy path: Valid data passes all checks
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- Edge cases: Empty strings, null values, boundary numbers
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- Error cases: Invalid types, missing required fields
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- Integration: Validator works with ingestion pipeline
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</example>
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</instruction>
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## Test Pyramid
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```
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/\
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/E2E\ ← [X]% (End-to-end, slow, comprehensive)
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/------\
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/Integration\ ← [Y]% (Module interactions)
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/------------\
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/ Unit Tests \ ← [Z]% (Fast, isolated, deterministic)
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/----------------\
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```
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## Coverage Requirements
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- Line coverage: [X]% minimum
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- Branch coverage: [X]% minimum
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- Function coverage: [X]% minimum
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- Statement coverage: [X]% minimum
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## Critical Test Scenarios
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### [Module/Feature Name]
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**Happy path**:
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- [Scenario description]
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- Expected: [What should happen]
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**Edge cases**:
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- [Scenario description]
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- Expected: [What should happen]
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**Error cases**:
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- [Scenario description]
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- Expected: [How system handles failure]
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**Integration points**:
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- [What interactions to test]
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- Expected: [End-to-end behavior]
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## Test Generation Guidelines
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[Specific instructions for Surgical Test Generator about what to focus on, what patterns to follow, project-specific test conventions]
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</test-strategy>
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---
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<architecture>
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<instruction>
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Describe technical architecture, data models, and key design decisions.
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Keep this section AFTER functional/structural decomposition - implementation details come after understanding structure.
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</instruction>
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## System Components
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[Major architectural pieces and their responsibilities]
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## Data Models
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[Core data structures, schemas, database design]
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## Technology Stack
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[Languages, frameworks, key libraries]
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**Decision: [Technology/Pattern]**
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- **Rationale**: [Why chosen]
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- **Trade-offs**: [What we're giving up]
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- **Alternatives considered**: [What else we looked at]
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</architecture>
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---
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<risks>
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<instruction>
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Identify risks that could derail development and how to mitigate them.
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Categories:
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- Technical risks (complexity, unknowns)
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- Dependency risks (blocking issues)
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- Scope risks (creep, underestimation)
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</instruction>
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## Technical Risks
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**Risk**: [Description]
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- **Impact**: [High/Medium/Low - effect on project]
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- **Likelihood**: [High/Medium/Low]
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- **Mitigation**: [How to address]
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- **Fallback**: [Plan B if mitigation fails]
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## Dependency Risks
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[External dependencies, blocking issues]
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## Scope Risks
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[Scope creep, underestimation, unclear requirements]
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</risks>
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---
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<appendix>
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## References
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[Papers, documentation, similar systems]
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## Glossary
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[Domain-specific terms]
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## Open Questions
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[Things to resolve during development]
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</appendix>
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---
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<task-master-integration>
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# How Task Master Uses This PRD
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When you run `task-master parse-prd <file>.txt`, the parser:
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1. **Extracts capabilities** → Main tasks
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- Each `### Capability:` becomes a top-level task
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2. **Extracts features** → Subtasks
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- Each `#### Feature:` becomes a subtask under its capability
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3. **Parses dependencies** → Task dependencies
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- `Depends on: [X, Y]` sets task.dependencies = ["X", "Y"]
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4. **Orders by phases** → Task priorities
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- Phase 0 tasks = highest priority
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- Phase N tasks = lower priority, properly sequenced
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5. **Uses test strategy** → Test generation context
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- Feeds test scenarios to Surgical Test Generator during implementation
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**Result**: A dependency-aware task graph that can be executed in topological order.
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## Why RPG Structure Matters
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Traditional flat PRDs lead to:
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- ❌ Unclear task dependencies
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- ❌ Arbitrary task ordering
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- ❌ Circular dependencies discovered late
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- ❌ Poorly scoped tasks
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RPG-structured PRDs provide:
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- ✅ Explicit dependency chains
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- ✅ Topological execution order
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- ✅ Clear module boundaries
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- ✅ Validated task graph before implementation
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## Tips for Best Results
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1. **Spend time on dependency graph** - This is the most valuable section for Task Master
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2. **Keep features atomic** - Each feature should be independently testable
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3. **Progressive refinement** - Start broad, use `task-master expand` to break down complex tasks
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4. **Use research mode** - `task-master parse-prd --research` leverages AI for better task generation
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</task-master-integration>
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Reference in New Issue
Block a user