task-master
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.
Best use case
task-master is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using task-master should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/task-master/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How task-master Compares
| Feature / Agent | task-master | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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
✅ **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
❌ **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 informationRelated Skills
task-master-viewer
Launch a Streamlit GUI for Task Master tasks.json editing. Use when users want a visual interface instead of CLI/MCP commands.
task-master-install
Install and initialize task-master for AI-powered task management and specification-driven development. Use this skill when users ask you to parse a new PRD, when starting a new project that needs structured task management, when users mention wanting task breakdown or project planning, or when implementing specification-driven development workflows.
streamlit-development
Developing, testing, and deploying Streamlit data applications on Snowflake. Use this skill when you're building interactive data apps, setting up local development environments, testing with pytest or Playwright, or deploying apps to Snowflake using Streamlit in Snowflake.
snowflake-connections
Configuring Snowflake connections using connections.toml (for Snowflake CLI, Streamlit, Snowpark) or profiles.yml (for dbt) with multiple authentication methods (SSO, key pair, username/password, OAuth), managing multiple environments, and overriding settings with environment variables. Use this skill when setting up Snowflake CLI, Streamlit apps, dbt, or any tool requiring Snowflake authentication and connection management.
snowflake-cli
Executing SQL, managing Snowflake objects, deploying applications, and orchestrating data pipelines using the Snowflake CLI (snow) command. Use this skill when you need to run SQL scripts, deploy Streamlit apps, execute Snowpark procedures, manage stages, automate Snowflake operations from CI/CD pipelines, or work with variables and templating.
skills-sync
Manage and synchronize AI agent skills from local SKILL.md files and remote Git repositories, generating Cursor rules with Agent Skills specification XML. This skill should be used when users need to sync skills, add/remove skill repositories, or set up the skills infrastructure.
schemachange
Deploying and managing Snowflake database objects using version control with schemachange. Use this skill when you need to manage database migrations for objects not handled by dbt, implement CI/CD pipelines for schema changes, or coordinate deployments across multiple environments.
playwright-mcp
Browser testing, web scraping, and UI validation using Playwright MCP. Use this skill when you need to test Streamlit apps, validate web interfaces, test responsive design, check accessibility, or automate browser interactions through MCP tools.
doc-scraper
Generic web scraper for extracting and organizing Snowflake documentation with intelligent caching and configurable spider depth. Scrapes any section of docs.snowflake.com controlled by --base-path.
devcontainer-setup
Create Universal DevContainers optimized for AI agentic workflows with Claude Code, Snowflake CLI, Cortex Code, and dbt. Use when setting up development containers, configuring devcontainer.json, scaffolding AI-ready environments, or when the user mentions devcontainers, containerized development, or Docker development environments.
dbt-testing
dbt testing strategies using dbt_constraints for database-level enforcement, generic tests, and singular tests. Use this skill when implementing data quality checks, adding primary/foreign key constraints, creating custom tests, or establishing comprehensive testing frameworks across bronze/silver/gold layers.
dbt-projects-snowflake-setup
Step-by-step setup guide for dbt Projects on Snowflake including prerequisites, external access integration, Git API integration, event table configuration, and automated scheduling. Use this skill when setting up dbt Projects on Snowflake for the first time or troubleshooting setup issues.