home / skills / sfc-gh-dflippo / snowflake-dbt-demo / task-master
This skill helps manage complex development projects by converting PRDs into actionable tasks, tracking dependencies, and aligning work with feature branches.
npx playbooks add skill sfc-gh-dflippo/snowflake-dbt-demo --skill task-masterReview the files below or copy the command above to add this skill to your agents.
---
name: task-master
description:
AI-powered task management for structured, specification-driven development. Use this skill when
you need to manage complex projects with PRDs, break down tasks into subtasks, track dependencies,
and maintain organized development workflows across features and branches.
---
# Task Master AI
An AI-powered task management system that integrates seamlessly with AI Agents to manage
specification-driven development workflows.
## Quick Start
**Three Ways to Use Task Master:**
1. **MCP Tools** (Recommended) - Direct integration via Model Context Protocol
2. **CLI Commands** - Terminal-based task management
3. **Tagged Contexts** - Multi-branch/feature task isolation
## Core Capabilities
### Task Management
- Parse PRDs into actionable tasks automatically
- Break down complex tasks into manageable subtasks
- Track task dependencies and status
- Support for multiple task contexts (tags) for features/branches
### AI-Powered Features
- Complexity analysis with recommendations
- Research-backed task expansion
- Intelligent task updates based on implementation drift
- Fresh information gathering beyond knowledge cutoff
### Development Workflow
- Specification-driven development (SDD) support
- Iterative subtask implementation logging
- Git branch-aligned task contexts
- Team collaboration with isolated task lists
## When to Use This Skill
ā
**Use Task Master when:**
- Starting a new project from a PRD
- Managing complex multi-step features
- Working on feature branches with isolated tasks
- Need to track task dependencies and priorities
- Want AI-assisted task breakdown and planning
- Collaborating with team members on shared codebase
- Need to log implementation progress iteratively
ā **Skip Task Master for:**
- Simple single-file changes
- Quick bug fixes
- Trivial tasks with no dependencies
- Projects without formal requirements
## Setup
### Prerequisites
- Node.js installed
- API keys for AI providers (Anthropic, Perplexity, etc.)
- Git repository (optional, for branch-based workflows)
### Installation
**Global Installation:**
```bash
npm install -g task-master-ai
```
**Project-Local:**
```bash
npm install task-master-ai
```
### MCP Configuration
Add to your MCP config file (`.cursor/mcp.json`, `.vscode/mcp.json`, etc.):
```json
{
"mcpServers": {
"task-master-ai": {
"command": "npx",
"args": ["-y", "task-master-ai"],
"env": {
"ANTHROPIC_API_KEY": "YOUR_KEY_HERE",
"PERPLEXITY_API_KEY": "YOUR_KEY_HERE"
}
}
}
}
```
For complete setup details, see `references/SETUP.md`.
## Basic Workflow
### 1. Initialize Project
```sql
Initialize taskmaster-ai in my project
```
### 2. Create PRD
Create your Product Requirements Document at `.taskmaster/docs/prd.txt`
### 3. Parse PRD
```sql
Parse my PRD at .taskmaster/docs/prd.txt
```
### 4. View Tasks
```sql
Show me the task list
```
### 5. Work on Tasks
```sql
What's the next task I should work on?
Can you help me implement task 3?
```
### 6. Track Progress
```sql
Mark task 3 as done
Update subtask 3.2 with my implementation findings
```
## Key Concepts
### Tagged Task Lists
Organize tasks into separate contexts (tags) for:
- Feature branches (`feature-auth`, `feature-dashboard`)
- Experiments (`experiment-zustand`)
- Team collaboration (`alice-work`, `bob-work`)
- Versions (`v1.0`, `v2.0`, `mvp`)
### Task Structure
- **ID**: Unique identifier (e.g., `1`, `1.2`)
- **Title**: Brief description
- **Description**: What needs to be done
- **Status**: `pending`, `in-progress`, `done`, `deferred`
- **Dependencies**: Prerequisites (e.g., `[1, 2.1]`)
- **Priority**: `high`, `medium`, `low`
- **Details**: Implementation notes
- **Subtasks**: Breakdown of complex tasks
### Complexity Analysis
AI analyzes task complexity (1-10 scale) and recommends:
- Number of subtasks needed
- Areas requiring research
- Implementation approach
## Common Commands
### Task Viewing
```sql
List all tasks
Show me task 5
Show me tasks 1, 3, and 5
What's the next task?
```
### Task Creation & Modification
```sql
Add a task to implement user authentication
Expand task 4 into subtasks
Update task 5 with new requirements
Mark task 3 as done
```
### Task Organization
```sql
Move task 5 to become subtask 7.3
Add dependency: task 8 depends on task 5
Create a new tag called feature-auth
Switch to the feature-auth tag
```
### Research & Analysis
```sql
Research the latest best practices for JWT authentication
Analyze task complexity for all pending tasks
Expand all pending tasks based on complexity
```
## Advanced Workflows
### PRD-Driven Feature Development
1. Create dedicated tag for feature
2. Write comprehensive PRD
3. Parse PRD into tag
4. Analyze complexity
5. Expand complex tasks
6. Implement iteratively
### Team Collaboration
1. Create personal tag for your work
2. Copy tasks from master
3. Work in isolation
4. Merge back when ready
### Branch-Based Development
1. Create git branch
2. Create matching tag from branch
3. Develop feature with isolated tasks
4. Merge code and tasks together
## Integration with Development
### Iterative Implementation
1. View subtask details
2. Plan implementation approach
3. Log plan to subtask
4. Begin coding
5. Log progress and findings
6. Mark complete
7. Commit changes
### Specification-Driven Development
Task Master supports full SDD workflow:
- Requirements gathering
- PRD creation
- Task generation
- Complexity analysis
- Implementation tracking
- Progress documentation
## Resources
- `references/SETUP.md` - Complete installation and configuration
- `references/WORKFLOW.md` - Detailed development workflows
- `references/COMMANDS.md` - Comprehensive command reference
- `references/BEST_PRACTICES.md` - Tips and patterns
## References
- [Task Master GitHub](https://github.com/eyaltoledano/claude-task-master)
- [Task Master Website](https://task-master.dev)
- [MCP Documentation](https://modelcontextprotocol.io)
---
**Quick Tips:**
- Always start with a detailed PRD
- Use complexity analysis before expanding tasks
- Log implementation findings to subtasks
- Leverage tags for feature isolation
- Use research tool for fresh information
This skill provides AI-powered task management for specification-driven development workflows. It parses PRDs into structured tasks, breaks complex items into subtasks, tracks dependencies and status, and aligns tasks with feature branches or isolated tags. Use it to maintain organized, repeatable development planning and execution across teams.
The skill ingests a Product Requirements Document (PRD) or natural-language input and extracts actionable tasks with IDs, descriptions, priorities, dependencies, and estimated complexity. It analyzes each task for complexity (1-10), suggests subtasks and research needs, and keeps task lists separated by tags that map to branches, experiments, or team members. Commands let you view, create, modify, and log progress on tasks; the AI updates task structure when implementation drift is detected and can fetch fresh research to inform decisions.
Can I use this without a formal PRD?
Yes. The skill accepts informal descriptions, but richer PRDs yield higher-quality, better-structured tasks.
How do tags relate to Git branches?
Tags are intended to mirror branches: create a tag per branch so tasks stay isolated and easily merged when code is merged.
What integrations are available for AI and research?
The skill supports configurable AI providers and a fresh-information research tool so it can fetch up-to-date guidance beyond static knowledge.