A task management system for AI-driven development with DeepSeek, designed to work seamlessly with Cursor AI.
- Node.js 14.0.0 or higher
- DeepSeek API key
- OpenAI SDK (for DeepSeek and Perplexity API integration)
The script can be configured through environment variables in a .env
file at the root of the project:
DEEPSEEK_API_KEY
: Your DeepSeek API key
MODEL
: Specify which DeepSeek model to use (default: "deepseek-chat")MAX_TOKENS
: Maximum tokens for model responses (default: 4000)TEMPERATURE
: Temperature for model responses (default: 0.7)PERPLEXITY_API_KEY
: Your Perplexity API key for research-backed subtask generationPERPLEXITY_MODEL
: Specify which Perplexity model to use (default: "sonar-medium-online")DEBUG
: Enable debug logging (default: false)LOG_LEVEL
: Log level - debug, info, warn, error (default: info)DEFAULT_SUBTASKS
: Default number of subtasks when expanding (default: 3)DEFAULT_PRIORITY
: Default priority for generated tasks (default: medium)PROJECT_NAME
: Override default project name in tasks.jsonPROJECT_VERSION
: Override default version in tasks.json
# Install globally
npm install -g task-master-ai
# OR install locally within your project
npm install task-master-ai
# If installed globally
task-master init
# If installed locally
npx task-master-init
This will prompt you for project details and set up a new project with the necessary files and structure.
- This package uses ES modules. Your package.json should include
"type": "module"
. - The DeepSeek SDK version should be 0.39.0 or higher.
After installing the package globally, you can use these CLI commands from any directory:
# Initialize a new project
task-master init
# Parse a PRD and generate tasks
task-master parse-prd your-prd.txt
# List all tasks
task-master list
# Show the next task to work on
task-master next
# Generate task files
task-master generate
Try running it with Node directly:
node node_modules/claude-task-master/scripts/init.js
Or clone the repository and run:
git clone https://github.com/eyaltoledano/claude-task-master.git
cd claude-task-master
node scripts/init.js
Tasks in tasks.json have the following structure:
id
: Unique identifier for the task (Example:1
)title
: Brief, descriptive title of the task (Example:"Initialize Repo"
)description
: Concise description of what the task involves (Example:"Create a new repository, set up initial structure."
)status
: Current state of the task (Example:"pending"
,"done"
,"deferred"
)dependencies
: IDs of tasks that must be completed before this task (Example:[1, 2]
)- Dependencies are displayed with status indicators (✅ for completed, ⏱️ for pending)
- This helps quickly identify which prerequisite tasks are blocking work
priority
: Importance level of the task (Example:"high"
,"medium"
,"low"
)details
: In-depth implementation instructions (Example:"Use GitHub client ID/secret, handle callback, set session token."
)testStrategy
: Verification approach (Example:"Deploy and call endpoint to confirm 'Hello World' response."
)subtasks
: List of smaller, more specific tasks that make up the main task (Example:[{"id": 1, "title": "Configure OAuth", ...}]
)
Claude Task Master is designed to work seamlessly with Cursor AI, providing a structured workflow for AI-driven development.
- After initializing your project, open it in Cursor
- The
.cursor/rules/dev_workflow.mdc
file is automatically loaded by Cursor, providing the AI with knowledge about the task management system - Place your PRD document in the
scripts/
directory (e.g.,scripts/prd.txt
) - Open Cursor's AI chat and switch to Agent mode
To enable enhanced task management capabilities directly within Cursor using the Model Control Protocol (MCP):
- Go to Cursor settings
- Navigate to the MCP section
- Click on "Add New MCP Server"
- Configure with the following details:
- Name: "Task Master"
- Type: "Command"
- Command: "npx -y --package task-master-ai task-master-mcp"
- Save the settings
Once configured, you can interact with Task Master's task management commands directly through Cursor's interface, providing a more integrated experience.
In Cursor's AI chat, instruct the agent to generate tasks from your PRD:
Please use the task-master parse-prd command to generate tasks from my PRD. The PRD is located at scripts/prd.txt.
The agent will execute:
task-master parse-prd scripts/prd.txt
This will:
- Parse your PRD document
- Generate a structured
tasks.json
file with tasks, dependencies, priorities, and test strategies - The agent will understand this process due to the Cursor rules
Next, ask the agent to generate individual task files:
Please generate individual task files from tasks.json
The agent will execute:
task-master generate
This creates individual task files in the tasks/
directory (e.g., task_001.txt
, task_002.txt
), making it easier to reference specific tasks.
The Cursor agent is pre-configured (via the rules file) to follow this workflow:
Ask the agent to list available tasks:
What tasks are available to work on next?
The agent will:
- Run
task-master list
to see all tasks - Run
task-master next
to determine the next task to work on - Analyze dependencies to determine which tasks are ready to be worked on
- Prioritize tasks based on priority level and ID order
- Suggest the next task(s) to implement
When implementing a task, the agent will:
- Reference the task's details section for implementation specifics
- Consider dependencies on previous tasks
- Follow the project's coding standards
- Create appropriate tests based on the task's testStrategy
You can ask:
Let's implement task 3. What does it involve?
Before marking a task as complete, verify it according to:
- The task's specified testStrategy
- Any automated tests in the codebase
- Manual verification if required
When a task is completed, tell the agent:
Task 3 is now complete. Please update its status.
The agent will execute:
task-master set-status --id=3 --status=done
If during implementation, you discover that:
- The current approach differs significantly from what was planned
- Future tasks need to be modified due to current implementation choices
- New dependencies or requirements have emerged
Tell the agent:
We've changed our approach. We're now using Express instead of Fastify. Please update all future tasks to reflect this change.
The agent will execute:
task-master update --from=4 --prompt="Now we are using Express instead of Fastify."
This will rewrite or re-scope subsequent tasks in tasks.json while preserving completed work.
For complex tasks that need more granularity:
Task 5 seems complex. Can you break it down into subtasks?
The agent will execute:
task-master expand --id=5 --num=3
You can provide additional context:
Please break down task 5 with a focus on security considerations.
The agent will execute:
task-master expand --id=5 --prompt="Focus on security aspects"
You can also expand all pending tasks:
Please break down all pending tasks into subtasks.
The agent will execute:
task-master expand --all
For research-backed subtask generation using Perplexity AI:
Please break down task 5 using research-backed generation.
The agent will execute:
task-master expand --id=5 --research
Here's a comprehensive reference of all available commands:
# Parse a PRD file and generate tasks
task-master parse-prd <prd-file.txt>
# Limit the number of tasks generated
task-master parse-prd <prd-file.txt> --num-tasks=10
# List all tasks
task-master list
# List tasks with a specific status
task-master list --status=<status>
# List tasks with subtasks
task-master list --with-subtasks
# List tasks with a specific status and include subtasks
task-master list --status=<status> --with-subtasks
# Show the next task to work on based on dependencies and status
task-master next
# Show details of a specific task
task-master show <id>
# or
task-master show --id=<id>
# View a specific subtask (e.g., subtask 2 of task 1)
task-master show 1.2
# Update tasks from a specific ID and provide context
task-master update --from=<id> --prompt="<prompt>"
# Generate individual task files from tasks.json
task-master generate
# Set status of a single task
task-master set-status --id=<id> --status=<status>
# Set status for multiple tasks
task-master set-status --id=1,2,3 --status=<status>
# Set status for subtasks
task-master set-status --id=1.1,1.2 --status=<status>
When marking a task as "done", all of its subtasks will automatically be marked as "done" as well.
# Expand a specific task with subtasks
task-master expand --id=<id> --num=<number>
# Expand with additional context
task-master expand --id=<id> --prompt="<context>"
# Expand all pending tasks
task-master expand --all
# Force regeneration of subtasks for tasks that already have them
task-master expand --all --force
# Research-backed subtask generation for a specific task
task-master expand --id=<id> --research
# Research-backed generation for all tasks
task-master expand --all --research
# Clear subtasks from a specific task
task-master clear-subtasks --id=<id>
# Clear subtasks from multiple tasks
task-master clear-subtasks --id=1,2,3
# Clear subtasks from all tasks
task-master clear-subtasks --all
# Analyze complexity of all tasks
task-master analyze-complexity
# Save report to a custom location
task-master analyze-complexity --output=my-report.json
# Use a specific LLM model
task-master analyze-complexity --model=claude-3-opus-20240229
# Set a custom complexity threshold (1-10)
task-master analyze-complexity --threshold=6
# Use an alternative tasks file
task-master analyze-complexity --file=custom-tasks.json
# Use Perplexity AI for research-backed complexity analysis
task-master analyze-complexity --research
# Display the task complexity analysis report
task-master complexity-report
# View a report at a custom location
task-master complexity-report --file=my-report.json
# Add a dependency to a task
task-master add-dependency --id=<id> --depends-on=<id>
# Remove a dependency from a task
task-master remove-dependency --id=<id> --depends-on=<id>
# Validate dependencies without fixing them
task-master validate-dependencies
# Find and fix invalid dependencies automatically
task-master fix-dependencies