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Author SHA1 Message Date
Ralph Khreish
b74e4a98ef chore: improve init message 2025-10-08 14:28:45 +02:00
Ralph Khreish
efd1a91177 chore: fix format 2025-10-08 14:21:27 +02:00
Ralph Khreish
0d9939348c chore: cleanup 2025-10-08 14:11:38 +02:00
Ralph Khreish
968c38c31d chore: fix docs issue 2025-10-08 14:06:41 +02:00
Ralph Khreish
c770f10265 feat: add rpg method prd example template 2025-10-06 20:23:45 +02:00
github-actions[bot]
b9e644c556 chore: rc version bump 2025-10-06 14:06:45 +00:00
9 changed files with 1423 additions and 5 deletions

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---
"task-master-ai": minor
---
Add RPG (Repository Planning Graph) method template for structured PRD creation. The new `example_prd_rpg.txt` template teaches AI agents and developers the RPG methodology through embedded instructions, inline good/bad examples, and XML-style tags for structure. This template enables creation of dependency-aware PRDs that automatically generate topologically-ordered task graphs when parsed with Task Master.
Key features:
- Method-as-template: teaches RPG principles (dual-semantics, explicit dependencies, topological order) while being used
- Inline instructions at decision points guide AI through each section
- Good/bad examples for immediate pattern matching
- Flexible plain-text format with XML-style tags for parseability
- Critical dependency-graph section ensures correct task ordering
- Automatic inclusion during `task-master init`
- Comprehensive documentation at [docs.task-master.dev/capabilities/rpg-method](https://docs.task-master.dev/capabilities/rpg-method)
- Tool recommendations for code-context-aware PRD creation (Claude Code, Cursor, Gemini CLI, Codex/Grok)
The RPG template complements the existing `example_prd.txt` and provides a more structured approach for complex projects requiring clear module boundaries and dependency chains.

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"extension": "0.25.4" "extension": "0.25.4"
}, },
"changesets": [ "changesets": [
"brave-lions-sing",
"chore-fix-docs", "chore-fix-docs",
"cursor-slash-commands", "cursor-slash-commands",
"curvy-weeks-flow", "curvy-weeks-flow",
"easy-spiders-wave", "easy-spiders-wave",
"fix-mcp-connection-errors",
"fix-mcp-default-tasks-path",
"flat-cities-say", "flat-cities-say",
"forty-tables-invite", "forty-tables-invite",
"gentle-cats-dance", "gentle-cats-dance",

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

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# task-master-ai # task-master-ai
## 0.28.0-rc.2
### Minor Changes
- [#1273](https://github.com/eyaltoledano/claude-task-master/pull/1273) [`b43b7ce`](https://github.com/eyaltoledano/claude-task-master/commit/b43b7ce201625eee956fb2f8cd332f238bb78c21) Thanks [@ben-vargas](https://github.com/ben-vargas)! - Add Codex CLI provider with OAuth authentication
- Added codex-cli provider for GPT-5 and GPT-5-Codex models (272K input / 128K output)
- OAuth-first authentication via `codex login` - no API key required
- Optional OPENAI_CODEX_API_KEY support
- Codebase analysis capabilities automatically enabled
- Command-specific settings and approval/sandbox modes
### Patch Changes
- [#1277](https://github.com/eyaltoledano/claude-task-master/pull/1277) [`7b5a7c4`](https://github.com/eyaltoledano/claude-task-master/commit/7b5a7c4495a68b782f7407fc5d0e0d3ae81f42f5) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fix MCP connection errors caused by deprecated generateTaskFiles calls. Resolves "Cannot read properties of null (reading 'toString')" errors when using MCP tools for task management operations.
- [#1276](https://github.com/eyaltoledano/claude-task-master/pull/1276) [`caee040`](https://github.com/eyaltoledano/claude-task-master/commit/caee040907f856d31a660171c9e6d966f23c632e) Thanks [@Crunchyman-ralph](https://github.com/Crunchyman-ralph)! - Fix MCP server error when file parameter not provided - now properly constructs default tasks.json path instead of failing with 'tasksJsonPath is required' error.
## 0.28.0-rc.1 ## 0.28.0-rc.1
### Patch Changes ### Patch Changes

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---
title: RPG Method for PRD Creation
sidebarTitle: "RPG Method"
---
# Repository Planning Graph (RPG) Method
The RPG (Repository Planning Graph) method is an advanced approach to creating Product Requirements Documents that generate highly-structured, dependency-aware task graphs. It's based on Microsoft Research's methodology for scalable codebase generation.
## When to Use RPG
Use the RPG template (`example_prd_rpg.txt`) for:
- **Complex multi-module systems** with intricate dependencies
- **Large-scale codebases** being built from scratch
- **Projects requiring explicit architecture** and clear module boundaries
- **Teams needing dependency visibility** for parallel development
For simpler features or smaller projects, the standard `example_prd.txt` template may be more appropriate.
---
## Core Principles
### 1. Dual-Semantics
Separate **functional** thinking (WHAT) from **structural** thinking (HOW):
```
Functional: "Data Validation capability with schema checking and rule enforcement"
Structural: "src/validation/ with schema-validator.js and rule-validator.js"
```
This separation prevents mixing concerns and creates clearer module boundaries.
### 2. Explicit Dependencies
Never assume dependencies - always state them explicitly:
```
Good:
Module: data-ingestion
Depends on: [schema-validator, config-manager]
Bad:
Module: data-ingestion
(Assumes schema-validator exists somewhere)
```
Explicit dependencies enable:
- Topological ordering of implementation
- Parallel development of independent modules
- Clear build/test order
- Early detection of circular dependencies
### 3. Topological Order
Build foundation layers before higher layers:
```
Phase 0 (Foundation): error-handling, base-types, config
Phase 1 (Data): validation, ingestion (depend on Phase 0)
Phase 2 (Core): algorithms, pipelines (depend on Phase 1)
Phase 3 (API): routes, handlers (depend on Phase 2)
```
Task Master automatically orders tasks based on this dependency chain.
### 4. Progressive Refinement
Start broad, refine iteratively:
1. High-level capabilities → Main tasks
2. Features per capability → Subtasks
3. Implementation details → Expanded subtasks
---
## Template Structure
The RPG template guides you through 7 key sections:
### 1. Overview
- Problem statement
- Target users
- Success metrics
### 2. Functional Decomposition (WHAT)
- High-level capability domains
- Features per capability
- Inputs/outputs/behavior for each feature
**Example:**
```
Capability: Data Management
Feature: Schema validation
Description: Validate JSON against defined schemas
Inputs: JSON object, schema definition
Outputs: Validation result + error details
Behavior: Iterate fields, check types, enforce constraints
```
### 3. Structural Decomposition (HOW)
- Repository folder structure
- Module-to-capability mapping
- File organization
- Public interfaces/exports
**Example:**
```
Capability: Data Management
→ Maps to: src/data/
├── schema-validator.js (Schema validation feature)
├── rule-validator.js (Rule validation feature)
└── index.js (Exports)
```
### 4. Dependency Graph (CRITICAL)
- Foundation layer (no dependencies)
- Each subsequent layer's dependencies
- Explicit "depends on" declarations
**Example:**
```
Foundation Layer (Phase 0):
- error-handling: No dependencies
- base-types: No dependencies
Data Layer (Phase 1):
- schema-validator: Depends on [base-types, error-handling]
- data-ingestion: Depends on [schema-validator]
```
### 5. Implementation Roadmap
- Phases with entry/exit criteria
- Tasks grouped by phase
- Clear deliverables per phase
### 6. Test Strategy
- Test pyramid ratios
- Coverage requirements
- Critical test scenarios per module
- Guidelines for test generation
### 7. Architecture & Risks
- Technical architecture
- Data models
- Technology decisions
- Risk mitigation strategies
---
## Using RPG with Task Master
### Step 1: Create PRD with RPG Template
Use a code-context-aware tool to fill out the template:
```bash
# In Claude Code, Cursor, or similar
"Create a PRD using @.taskmaster/templates/example_prd_rpg.txt for [your project]"
```
**Why code context matters:** The AI needs to understand your existing codebase to make informed decisions about:
- Module boundaries
- Dependency relationships
- Integration points
- Naming conventions
**Recommended tools:**
- Claude Code (claude-code CLI)
- Cursor/Windsurf
- Gemini CLI (large contexts)
- Codex/Grok CLI
### Step 2: Parse PRD into Tasks
```bash
task-master parse-prd .taskmaster/docs/your-prd.txt --research
```
Task Master will:
1. Extract capabilities → Main tasks
2. Extract features → Subtasks
3. Parse dependencies → Task dependencies
4. Order by phases → Task priorities
**Result:** A dependency-aware task graph ready for topological execution.
### Step 3: Analyze Complexity
```bash
task-master analyze-complexity --research
```
Review the complexity report to identify tasks that need expansion.
### Step 4: Expand Tasks
```bash
task-master expand --all --research
```
Break down complex tasks into manageable subtasks while preserving dependency chains.
---
## RPG Benefits
### For Solo Developers
- Clear roadmap for implementing complex features
- Prevents architectural mistakes early
- Explicit dependency tracking avoids integration issues
- Enables resuming work after interruptions
### For Teams
- Parallel development of independent modules
- Clear contracts between modules (explicit dependencies)
- Reduced merge conflicts (proper module boundaries)
- Onboarding aid (architectural overview in PRD)
### For AI Agents
- Structured context for code generation
- Clear scope boundaries per task
- Dependency awareness prevents incomplete implementations
- Test strategy guidance for TDD workflows
---
## RPG vs Standard Template
| Aspect | Standard Template | RPG Template |
|--------|------------------|--------------|
| **Best for** | Simple features | Complex systems |
| **Dependency handling** | Implicit | Explicit graph |
| **Structure guidance** | Minimal | Step-by-step |
| **Examples** | Few | Inline good/bad examples |
| **Module boundaries** | Vague | Precise mapping |
| **Task ordering** | Manual | Automatic (topological) |
| **Learning curve** | Low | Medium |
| **Resulting task quality** | Good | Excellent |
---
## Tips for Best Results
### 1. Spend Time on Dependencies
The dependency graph section is the most valuable. List all dependencies explicitly, even if they seem obvious.
### 2. Keep Features Atomic
Each feature should be independently testable. If a feature description is vague ("handle data"), break it into specific features.
### 3. Progressive Refinement
Don't try to get everything perfect on the first pass:
1. Fill out high-level sections
2. Review and refine
3. Add detail where needed
4. Let `task-master expand` break down complex tasks further
### 4. Use Research Mode
```bash
task-master parse-prd --research
```
The `--research` flag leverages AI to enhance task generation with domain knowledge.
### 5. Validate Early
```bash
task-master validate-dependencies
```
Check for circular dependencies or orphaned modules before starting implementation.
---
## Common Pitfalls
### ❌ Mixing Functional and Structural
```
Bad: "Capability: validation.js"
Good: "Capability: Data Validation" → maps to "src/validation/"
```
### ❌ Vague Module Boundaries
```
Bad: "Module: utils"
Good: "Module: string-utilities" with clear exports
```
### ❌ Implicit Dependencies
```
Bad: "Module: API handlers (needs validation)"
Good: "Module: API handlers, Depends on: [validation, error-handling]"
```
### ❌ Skipping Test Strategy
Without test strategy, the AI won't know what to test during implementation.
---
## Example Workflow
1. **Discuss idea with AI**: Explain your project concept
2. **Reference RPG template**: Show AI the `example_prd_rpg.txt`
3. **Co-create PRD**: Work through each section with AI guidance
4. **Save to docs**: Place in `.taskmaster/docs/your-project.txt`
5. **Parse PRD**: `task-master parse-prd .taskmaster/docs/your-project.txt --research`
6. **Analyze**: `task-master analyze-complexity --research`
7. **Expand**: `task-master expand --all --research`
8. **Start work**: `task-master next`
---
## Further Reading
- [PRD Creation and Parsing Guide](/getting-started/quick-start/prd-quick)
- [Task Structure Documentation](/capabilities/task-structure)
- [Microsoft Research RPG Paper](https://arxiv.org/abs/2410.21376) (Original methodology)
---
<Tip>
The RPG template includes inline `<instruction>` and `<example>` blocks that teach the method as you use it. Read these sections carefully - they provide valuable guidance at each decision point.
</Tip>

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@@ -32,7 +32,11 @@ The more context you give the model, the better the breakdown and results.
## Writing a PRD for Task Master ## Writing a PRD for Task Master
<Note>An example PRD can be found in .taskmaster/templates/example_prd.txt</Note> <Note>
Two example PRD templates are available in `.taskmaster/templates/`:
- `example_prd.txt` - Simple template for straightforward projects
- `example_prd_rpg.txt` - Advanced RPG (Repository Planning Graph) template for complex projects with dependencies
</Note>
You can co-write your PRD with an LLM model using the following workflow: You can co-write your PRD with an LLM model using the following workflow:
@@ -43,6 +47,29 @@ You can co-write your PRD with an LLM model using the following workflow:
This approach works great in Cursor, or anywhere you use a chat-based LLM. This approach works great in Cursor, or anywhere you use a chat-based LLM.
### Choosing Between Templates
**Use `example_prd.txt` when:**
- Building straightforward features
- Working on smaller projects
- Dependencies are simple and obvious
**Use `example_prd_rpg.txt` when:**
- Building complex systems with multiple modules
- Need explicit dependency management
- Want structured guidance on architecture decisions
- Planning a large codebase from scratch
The RPG template teaches you to think about:
1. **Functional decomposition** (WHAT the system does)
2. **Structural decomposition** (HOW it's organized in code)
3. **Explicit dependencies** (WHAT depends on WHAT)
4. **Topological ordering** (build foundation first, then layers)
<Tip>
For complex projects, using the RPG template with a code-context-aware ai agent produces the best results because the AI can understand your existing codebase structure. [Learn more about the RPG method →](/capabilities/rpg-method)
</Tip>
--- ---
## Where to Save Your PRD ## Where to Save Your PRD

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assets/example_prd_rpg.txt Normal file
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@@ -0,0 +1,511 @@
<rpg-method>
# Repository Planning Graph (RPG) Method - PRD Template
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.
## Core Principles
1. **Dual-Semantics**: Think functional (capabilities) AND structural (code organization) separately, then map them
2. **Explicit Dependencies**: Never assume - always state what depends on what
3. **Topological Order**: Build foundation first, then layers on top
4. **Progressive Refinement**: Start broad, refine iteratively
## How to Use This Template
- Follow the instructions in each `<instruction>` block
- Look at `<example>` blocks to see good vs bad patterns
- Fill in the content sections with your project details
- The AI reading this will learn the RPG method by following along
- Task Master will parse the resulting PRD into dependency-aware tasks
## Recommended Tools for Creating PRDs
When using this template to **create** a PRD (not parse it), use **code-context-aware AI assistants** for best results:
**Why?** The AI needs to understand your existing codebase to make good architectural decisions about modules, dependencies, and integration points.
**Recommended tools:**
- **Claude Code** (claude-code CLI) - Best for structured reasoning and large contexts
- **Cursor/Windsurf** - IDE integration with full codebase context
- **Gemini CLI** (gemini-cli) - Massive context window for large codebases
- **Codex/Grok CLI** - Strong code generation with context awareness
**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.
</rpg-method>
---
<overview>
<instruction>
Start with the problem, not the solution. Be specific about:
- What pain point exists?
- Who experiences it?
- Why existing solutions don't work?
- What success looks like (measurable outcomes)?
Keep this section focused - don't jump into implementation details yet.
</instruction>
## Problem Statement
[Describe the core problem. Be concrete about user pain points.]
## Target Users
[Define personas, their workflows, and what they're trying to achieve.]
## Success Metrics
[Quantifiable outcomes. Examples: "80% task completion via autopilot", "< 5% manual intervention rate"]
</overview>
---
<functional-decomposition>
<instruction>
Now think about CAPABILITIES (what the system DOES), not code structure yet.
Step 1: Identify high-level capability domains
- Think: "What major things does this system do?"
- Examples: Data Management, Core Processing, Presentation Layer
Step 2: For each capability, enumerate specific features
- Use explore-exploit strategy:
* Exploit: What features are REQUIRED for core value?
* Explore: What features make this domain COMPLETE?
Step 3: For each feature, define:
- Description: What it does in one sentence
- Inputs: What data/context it needs
- Outputs: What it produces/returns
- Behavior: Key logic or transformations
<example type="good">
Capability: Data Validation
Feature: Schema validation
- Description: Validate JSON payloads against defined schemas
- Inputs: JSON object, schema definition
- Outputs: Validation result (pass/fail) + error details
- Behavior: Iterate fields, check types, enforce constraints
Feature: Business rule validation
- Description: Apply domain-specific validation rules
- Inputs: Validated data object, rule set
- Outputs: Boolean + list of violated rules
- Behavior: Execute rules sequentially, short-circuit on failure
</example>
<example type="bad">
Capability: validation.js
(Problem: This is a FILE, not a CAPABILITY. Mixing structure into functional thinking.)
Capability: Validation
Feature: Make sure data is good
(Problem: Too vague. No inputs/outputs. Not actionable.)
</example>
</instruction>
## Capability Tree
### Capability: [Name]
[Brief description of what this capability domain covers]
#### Feature: [Name]
- **Description**: [One sentence]
- **Inputs**: [What it needs]
- **Outputs**: [What it produces]
- **Behavior**: [Key logic]
#### Feature: [Name]
- **Description**:
- **Inputs**:
- **Outputs**:
- **Behavior**:
### Capability: [Name]
...
</functional-decomposition>
---
<structural-decomposition>
<instruction>
NOW think about code organization. Map capabilities to actual file/folder structure.
Rules:
1. Each capability maps to a module (folder or file)
2. Features within a capability map to functions/classes
3. Use clear module boundaries - each module has ONE responsibility
4. Define what each module exports (public interface)
The goal: Create a clear mapping between "what it does" (functional) and "where it lives" (structural).
<example type="good">
Capability: Data Validation
→ Maps to: src/validation/
├── schema-validator.js (Schema validation feature)
├── rule-validator.js (Business rule validation feature)
└── index.js (Public exports)
Exports:
- validateSchema(data, schema)
- validateRules(data, rules)
</example>
<example type="bad">
Capability: Data Validation
→ Maps to: src/utils.js
(Problem: "utils" is not a clear module boundary. Where do I find validation logic?)
Capability: Data Validation
→ Maps to: src/validation/everything.js
(Problem: One giant file. Features should map to separate files for maintainability.)
</example>
</instruction>
## Repository Structure
```
project-root/
├── src/
│ ├── [module-name]/ # Maps to: [Capability Name]
│ │ ├── [file].js # Maps to: [Feature Name]
│ │ └── index.js # Public exports
│ └── [module-name]/
├── tests/
└── docs/
```
## Module Definitions
### Module: [Name]
- **Maps to capability**: [Capability from functional decomposition]
- **Responsibility**: [Single clear purpose]
- **File structure**:
```
module-name/
├── feature1.js
├── feature2.js
└── index.js
```
- **Exports**:
- `functionName()` - [what it does]
- `ClassName` - [what it does]
</structural-decomposition>
---
<dependency-graph>
<instruction>
This is THE CRITICAL SECTION for Task Master parsing.
Define explicit dependencies between modules. This creates the topological order for task execution.
Rules:
1. List modules in dependency order (foundation first)
2. For each module, state what it depends on
3. Foundation modules should have NO dependencies
4. Every non-foundation module should depend on at least one other module
5. Think: "What must EXIST before I can build this module?"
<example type="good">
Foundation Layer (no dependencies):
- error-handling: No dependencies
- config-manager: No dependencies
- base-types: No dependencies
Data Layer:
- schema-validator: Depends on [base-types, error-handling]
- data-ingestion: Depends on [schema-validator, config-manager]
Core Layer:
- algorithm-engine: Depends on [base-types, error-handling]
- pipeline-orchestrator: Depends on [algorithm-engine, data-ingestion]
</example>
<example type="bad">
- validation: Depends on API
- API: Depends on validation
(Problem: Circular dependency. This will cause build/runtime issues.)
- user-auth: Depends on everything
(Problem: Too many dependencies. Should be more focused.)
</example>
</instruction>
## Dependency Chain
### Foundation Layer (Phase 0)
No dependencies - these are built first.
- **[Module Name]**: [What it provides]
- **[Module Name]**: [What it provides]
### [Layer Name] (Phase 1)
- **[Module Name]**: Depends on [[module-from-phase-0], [module-from-phase-0]]
- **[Module Name]**: Depends on [[module-from-phase-0]]
### [Layer Name] (Phase 2)
- **[Module Name]**: Depends on [[module-from-phase-1], [module-from-foundation]]
[Continue building up layers...]
</dependency-graph>
---
<implementation-roadmap>
<instruction>
Turn the dependency graph into concrete development phases.
Each phase should:
1. Have clear entry criteria (what must exist before starting)
2. Contain tasks that can be parallelized (no inter-dependencies within phase)
3. Have clear exit criteria (how do we know phase is complete?)
4. Build toward something USABLE (not just infrastructure)
Phase ordering follows topological sort of dependency graph.
<example type="good">
Phase 0: Foundation
Entry: Clean repository
Tasks:
- Implement error handling utilities
- Create base type definitions
- Setup configuration system
Exit: Other modules can import foundation without errors
Phase 1: Data Layer
Entry: Phase 0 complete
Tasks:
- Implement schema validator (uses: base types, error handling)
- Build data ingestion pipeline (uses: validator, config)
Exit: End-to-end data flow from input to validated output
</example>
<example type="bad">
Phase 1: Build Everything
Tasks:
- API
- Database
- UI
- Tests
(Problem: No clear focus. Too broad. Dependencies not considered.)
</example>
</instruction>
## Development Phases
### Phase 0: [Foundation Name]
**Goal**: [What foundational capability this establishes]
**Entry Criteria**: [What must be true before starting]
**Tasks**:
- [ ] [Task name] (depends on: [none or list])
- Acceptance criteria: [How we know it's done]
- Test strategy: [What tests prove it works]
- [ ] [Task name] (depends on: [none or list])
**Exit Criteria**: [Observable outcome that proves phase complete]
**Delivers**: [What can users/developers do after this phase?]
---
### Phase 1: [Layer Name]
**Goal**:
**Entry Criteria**: Phase 0 complete
**Tasks**:
- [ ] [Task name] (depends on: [[tasks-from-phase-0]])
- [ ] [Task name] (depends on: [[tasks-from-phase-0]])
**Exit Criteria**:
**Delivers**:
---
[Continue with more phases...]
</implementation-roadmap>
---
<test-strategy>
<instruction>
Define how testing will be integrated throughout development (TDD approach).
Specify:
1. Test pyramid ratios (unit vs integration vs e2e)
2. Coverage requirements
3. Critical test scenarios
4. Test generation guidelines for Surgical Test Generator
This section guides the AI when generating tests during the RED phase of TDD.
<example type="good">
Critical Test Scenarios for Data Validation module:
- Happy path: Valid data passes all checks
- Edge cases: Empty strings, null values, boundary numbers
- Error cases: Invalid types, missing required fields
- Integration: Validator works with ingestion pipeline
</example>
</instruction>
## Test Pyramid
```
/\
/E2E\ ← [X]% (End-to-end, slow, comprehensive)
/------\
/Integration\ ← [Y]% (Module interactions)
/------------\
/ Unit Tests \ ← [Z]% (Fast, isolated, deterministic)
/----------------\
```
## Coverage Requirements
- Line coverage: [X]% minimum
- Branch coverage: [X]% minimum
- Function coverage: [X]% minimum
- Statement coverage: [X]% minimum
## Critical Test Scenarios
### [Module/Feature Name]
**Happy path**:
- [Scenario description]
- Expected: [What should happen]
**Edge cases**:
- [Scenario description]
- Expected: [What should happen]
**Error cases**:
- [Scenario description]
- Expected: [How system handles failure]
**Integration points**:
- [What interactions to test]
- Expected: [End-to-end behavior]
## Test Generation Guidelines
[Specific instructions for Surgical Test Generator about what to focus on, what patterns to follow, project-specific test conventions]
</test-strategy>
---
<architecture>
<instruction>
Describe technical architecture, data models, and key design decisions.
Keep this section AFTER functional/structural decomposition - implementation details come after understanding structure.
</instruction>
## System Components
[Major architectural pieces and their responsibilities]
## Data Models
[Core data structures, schemas, database design]
## Technology Stack
[Languages, frameworks, key libraries]
**Decision: [Technology/Pattern]**
- **Rationale**: [Why chosen]
- **Trade-offs**: [What we're giving up]
- **Alternatives considered**: [What else we looked at]
</architecture>
---
<risks>
<instruction>
Identify risks that could derail development and how to mitigate them.
Categories:
- Technical risks (complexity, unknowns)
- Dependency risks (blocking issues)
- Scope risks (creep, underestimation)
</instruction>
## Technical Risks
**Risk**: [Description]
- **Impact**: [High/Medium/Low - effect on project]
- **Likelihood**: [High/Medium/Low]
- **Mitigation**: [How to address]
- **Fallback**: [Plan B if mitigation fails]
## Dependency Risks
[External dependencies, blocking issues]
## Scope Risks
[Scope creep, underestimation, unclear requirements]
</risks>
---
<appendix>
## References
[Papers, documentation, similar systems]
## Glossary
[Domain-specific terms]
## Open Questions
[Things to resolve during development]
</appendix>
---
<task-master-integration>
# How Task Master Uses This PRD
When you run `task-master parse-prd <file>.txt`, the parser:
1. **Extracts capabilities** → Main tasks
- Each `### Capability:` becomes a top-level task
2. **Extracts features** → Subtasks
- Each `#### Feature:` becomes a subtask under its capability
3. **Parses dependencies** → Task dependencies
- `Depends on: [X, Y]` sets task.dependencies = ["X", "Y"]
4. **Orders by phases** → Task priorities
- Phase 0 tasks = highest priority
- Phase N tasks = lower priority, properly sequenced
5. **Uses test strategy** → Test generation context
- Feeds test scenarios to Surgical Test Generator during implementation
**Result**: A dependency-aware task graph that can be executed in topological order.
## Why RPG Structure Matters
Traditional flat PRDs lead to:
- ❌ Unclear task dependencies
- ❌ Arbitrary task ordering
- ❌ Circular dependencies discovered late
- ❌ Poorly scoped tasks
RPG-structured PRDs provide:
- ✅ Explicit dependency chains
- ✅ Topological execution order
- ✅ Clear module boundaries
- ✅ Validated task graph before implementation
## Tips for Best Results
1. **Spend time on dependency graph** - This is the most valuable section for Task Master
2. **Keep features atomic** - Each feature should be independently testable
3. **Progressive refinement** - Start broad, use `task-master expand` to break down complex tasks
4. **Use research mode** - `task-master parse-prd --research` leverages AI for better task generation
</task-master-integration>

View File

@@ -1,6 +1,6 @@
{ {
"name": "task-master-ai", "name": "task-master-ai",
"version": "0.28.0-rc.1", "version": "0.28.0-rc.2",
"description": "A task management system for ambitious AI-driven development that doesn't overwhelm and confuse Cursor.", "description": "A task management system for ambitious AI-driven development that doesn't overwhelm and confuse Cursor.",
"main": "index.js", "main": "index.js",
"type": "module", "type": "module",

View File

@@ -628,6 +628,12 @@ function createProjectStructure(
// Copy example_prd.txt to NEW location // Copy example_prd.txt to NEW location
copyTemplateFile('example_prd.txt', path.join(targetDir, EXAMPLE_PRD_FILE)); copyTemplateFile('example_prd.txt', path.join(targetDir, EXAMPLE_PRD_FILE));
// Copy example_prd_rpg.txt to templates directory
copyTemplateFile(
'example_prd_rpg.txt',
path.join(targetDir, TASKMASTER_TEMPLATES_DIR, 'example_prd_rpg.txt')
);
// Initialize git repository if git is available // Initialize git repository if git is available
try { try {
if (initGit === false) { if (initGit === false) {
@@ -856,10 +862,10 @@ function createProjectStructure(
)}\n${chalk.white(' ├─ ')}${chalk.dim('Models: Use `task-master models` commands')}\n${chalk.white(' └─ ')}${chalk.dim( )}\n${chalk.white(' ├─ ')}${chalk.dim('Models: Use `task-master models` commands')}\n${chalk.white(' └─ ')}${chalk.dim(
'Keys: Add provider API keys to .env (or inside the MCP config file i.e. .cursor/mcp.json)' 'Keys: Add provider API keys to .env (or inside the MCP config file i.e. .cursor/mcp.json)'
)}\n${chalk.white('2. ')}${chalk.yellow( )}\n${chalk.white('2. ')}${chalk.yellow(
'Discuss your idea with AI and ask for a PRD using example_prd.txt, and save it to scripts/PRD.txt' 'Discuss your idea with AI and ask for a PRD, and save it to .taskmaster/docs/prd.txt'
)}\n${chalk.white('3. ')}${chalk.yellow( )}\n${chalk.white(' ├─ ')}${chalk.dim('Simple projects: Use ')}${chalk.cyan('example_prd.txt')}${chalk.dim(' template')}\n${chalk.white(' └─ ')}${chalk.dim('Complex systems: Use ')}${chalk.cyan('example_prd_rpg.txt')}${chalk.dim(' template (for dependency-aware task graphs)')}\n${chalk.white('3. ')}${chalk.yellow(
'Ask Cursor Agent (or run CLI) to parse your PRD and generate initial tasks:' 'Ask Cursor Agent (or run CLI) to parse your PRD and generate initial tasks:'
)}\n${chalk.white(' └─ ')}${chalk.dim('MCP Tool: ')}${chalk.cyan('parse_prd')}${chalk.dim(' | CLI: ')}${chalk.cyan('task-master parse-prd scripts/prd.txt')}\n${chalk.white('4. ')}${chalk.yellow( )}\n${chalk.white(' └─ ')}${chalk.dim('MCP Tool: ')}${chalk.cyan('parse_prd')}${chalk.dim(' | CLI: ')}${chalk.cyan('task-master parse-prd .taskmaster/docs/prd.txt')}\n${chalk.white('4. ')}${chalk.yellow(
'Ask Cursor to analyze the complexity of the tasks in your PRD using research' 'Ask Cursor to analyze the complexity of the tasks in your PRD using research'
)}\n${chalk.white(' └─ ')}${chalk.dim('MCP Tool: ')}${chalk.cyan('analyze_project_complexity')}${chalk.dim(' | CLI: ')}${chalk.cyan('task-master analyze-complexity')}\n${chalk.white('5. ')}${chalk.yellow( )}\n${chalk.white(' └─ ')}${chalk.dim('MCP Tool: ')}${chalk.cyan('analyze_project_complexity')}${chalk.dim(' | CLI: ')}${chalk.cyan('task-master analyze-complexity')}\n${chalk.white('5. ')}${chalk.yellow(
'Ask Cursor to expand all of your tasks using the complexity analysis' 'Ask Cursor to expand all of your tasks using the complexity analysis'