claude-task-master/README-task-master.md

# Claude Task Master

A task management system for AI-driven development with Claude, designed to work seamlessly with Cursor AI.

## Requirements

- Node.js 14.0.0 or higher
- Anthropic API key (Claude API)
- Anthropic SDK version 0.39.0 or higher
- OpenAI SDK (for Perplexity API integration, optional)

## Configuration

The script can be configured through environment variables in a `.env` file at the root of the project:

### Required Configuration
- `ANTHROPIC_API_KEY`: Your Anthropic API key for Claude

### Optional Configuration
- `MODEL`: Specify which Claude model to use (default: "claude-3-7-sonnet-20250219")
- `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 generation
- `PERPLEXITY_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.json
- `PROJECT_VERSION`: Override default version in tasks.json

## Installation

```bash
npm install claude-task-master
```

## Usage

### Initialize a new project

```bash
npx claude-task-init
```

This will prompt you for project details and set up a new project with the necessary files and structure.

### Important Notes

1. This package uses ES modules. Your package.json should include `"type": "module"`.
2. The Anthropic SDK version should be 0.39.0 or higher.

## Troubleshooting

### If `npx claude-task-init` doesn't respond:

Try running it with Node directly:

```bash
node node_modules/claude-task-master/scripts/init.js
```

Or clone the repository and run:

```bash
git clone https://github.com/eyaltoledano/claude-task-master.git
cd claude-task-master
node scripts/init.js
```

## Integrating with Cursor AI

Claude Task Master is designed to work seamlessly with [Cursor AI](https://www.cursor.so/), providing a structured workflow for AI-driven development.

### Setup with Cursor

1. After initializing your project, open it in Cursor
2. The `.cursor/rules/dev_workflow.mdc` file is automatically loaded by Cursor, providing the AI with knowledge about the task management system
3. Place your PRD document in the `scripts/` directory (e.g., `scripts/prd.txt`)
4. Open Cursor's AI chat and switch to Agent mode

### Initial Task Generation

In Cursor's AI chat, instruct the agent to generate tasks from your PRD:

```
Please use the dev.js script to parse my PRD and generate tasks. The PRD is located at scripts/prd.txt.
```

The agent will execute:
```bash
node scripts/dev.js parse-prd --input=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

### Generate Individual Task Files

Next, ask the agent to generate individual task files:

```
Please generate individual task files from tasks.json
```

The agent will execute:
```bash
node scripts/dev.js 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.

## AI-Driven Development Workflow

The Cursor agent is pre-configured (via the rules file) to follow this workflow:

### 1. Task Discovery and Selection

Ask the agent to list available tasks:

```
What tasks are available to work on next?
```

The agent will:
- Run `node scripts/dev.js list` to see all tasks
- Run `node scripts/dev.js list --with-subtasks` to see tasks with their subtasks
- 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

### 2. Task Implementation

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?
```

### 3. Task Verification

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

### 4. Task Completion

When a task is completed, tell the agent:

```
Task 3 is now complete. Please update its status.
```

The agent will execute:
```bash
node scripts/dev.js set-status --id=3 --status=done
```

### 5. Handling Implementation Drift

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:
```bash
node scripts/dev.js 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.

### 6. Breaking Down Complex Tasks

For complex tasks that need more granularity:

```
Task 5 seems complex. Can you break it down into subtasks?
```

The agent will execute:
```bash
node scripts/dev.js expand --id=5 --subtasks=3
```

You can provide additional context:
```
Please break down task 5 with a focus on security considerations.
```

The agent will execute:
```bash
node scripts/dev.js 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:
```bash
node scripts/dev.js expand --all
```

For research-backed subtask generation using Perplexity AI:
```
Please break down task 5 using research-backed generation.
```

The agent will execute:
```bash
node scripts/dev.js expand --id=5 --research
```

You can also apply research-backed generation to all tasks:
```
Please break down all pending tasks using research-backed generation.
```

The agent will execute:
```bash
node scripts/dev.js expand --all --research
```

## Manual Command Reference

While the Cursor agent will handle most commands for you, you can also run them manually:

### Parse PRD
```bash
npm run parse-prd -- --input=<prd-file.txt>
```

### List Tasks
```bash
npm run list
```

# List tasks with a specific status
```bash
npm run dev -- list --status=<status>
```

# List tasks with subtasks
```bash
npm run dev -- list --with-subtasks
```

# List tasks with a specific status and include subtasks
```bash
npm run dev -- list --status=<status> --with-subtasks
```

### Update Tasks
```bash
npm run dev -- update --from=<id> --prompt="<prompt>"
```

### Generate Task Files
```bash
npm run generate
```

### Set Task Status
```bash
npm run dev -- set-status --id=<id> --status=<status>
```

When marking a task as "done", all of its subtasks will automatically be marked as "done" as well.

### Expand Tasks
```bash
npm run dev -- expand --id=<id> --subtasks=<number> --prompt="<context>"
```
or
```bash
npm run dev -- expand --all
```

For research-backed subtask generation:
```bash
npm run dev -- expand --id=<id> --research
```
or
```bash
npm run dev -- expand --all --research
```

### Clear Subtasks
```bash
# Clear subtasks from a specific task
npm run dev -- clear-subtasks --id=<id>

# Clear subtasks from multiple tasks
npm run dev -- clear-subtasks --id=1,2,3

# Clear subtasks from all tasks
npm run dev -- clear-subtasks --all
```

## Task Structure

Tasks in tasks.json have the following structure:

- `id`: Unique identifier for the task
- `title`: Brief, descriptive title of the task
- `description`: Concise description of what the task involves
- `status`: Current state of the task (pending, done, deferred)
- `dependencies`: IDs of tasks that must be completed before this task
- `priority`: Importance level of the task (high, medium, low)
- `details`: In-depth instructions for implementing the task
- `testStrategy`: Approach for verifying the task has been completed correctly
- `subtasks`: List of smaller, more specific tasks that make up the main task

## Best Practices for AI-Driven Development

1. **Start with a detailed PRD**: The more detailed your PRD, the better the generated tasks will be.

2. **Review generated tasks**: After parsing the PRD, review the tasks to ensure they make sense and have appropriate dependencies.

3. **Follow the dependency chain**: Always respect task dependencies - the Cursor agent will help with this.

4. **Update as you go**: If your implementation diverges from the plan, use the update command to keep future tasks aligned with your current approach.

5. **Break down complex tasks**: Use the expand command to break down complex tasks into manageable subtasks.

6. **Regenerate task files**: After any updates to tasks.json, regenerate the task files to keep them in sync.

7. **Communicate context to the agent**: When asking the Cursor agent to help with a task, provide context about what you're trying to achieve.

## Example Cursor AI Interactions

### Starting a new project
```
I've just initialized a new project with Claude Task Master. I have a PRD at scripts/prd.txt. 
Can you help me parse it and set up the initial tasks?
```

### Working on tasks
```
What's the next task I should work on? Please consider dependencies and priorities.
```

### Implementing a specific task
```
I'd like to implement task 4. Can you help me understand what needs to be done and how to approach it?
```

### Managing subtasks
```
I need to regenerate the subtasks for task 3 with a different approach. Can you help me clear and regenerate them?
```

### Handling changes
```
We've decided to use MongoDB instead of PostgreSQL. Can you update all future tasks to reflect this change?
```

### Completing work
```
I've finished implementing the authentication system described in task 2. All tests are passing. 
Please mark it as complete and tell me what I should work on next.
```

## Documentation

For more detailed documentation on the scripts and command-line options, see the [scripts/README.md](scripts/README.md) file in your initialized project.

## License

MIT 

### Analyzing Task Complexity

To analyze the complexity of tasks and automatically generate expansion recommendations:

```bash
npm run dev -- analyze-complexity
```

This command:
- Analyzes each task using AI to assess its complexity
- Recommends optimal number of subtasks based on configured DEFAULT_SUBTASKS
- Generates tailored prompts for expanding each task
- Creates a comprehensive JSON report with ready-to-use commands
- Saves the report to scripts/task-complexity-report.json by default

Options:
```bash
# Save report to a custom location
npm run dev -- analyze-complexity --output=my-report.json

# Use a specific LLM model
npm run dev -- analyze-complexity --model=claude-3-opus-20240229

# Set a custom complexity threshold (1-10)
npm run dev -- analyze-complexity --threshold=6

# Use an alternative tasks file
npm run dev -- analyze-complexity --file=custom-tasks.json

# Use Perplexity AI for research-backed complexity analysis
npm run dev -- analyze-complexity --research
```

The generated report contains:
- Complexity analysis for each task (scored 1-10)
- Recommended number of subtasks based on complexity
- AI-generated expansion prompts customized for each task
- Ready-to-run expansion commands directly within each task analysis

### Smart Task Expansion

The `expand` command now automatically checks for and uses the complexity report:

```bash
# Expand a task, using complexity report recommendations if available
npm run dev -- expand --id=8

# Expand all tasks, prioritizing by complexity score if a report exists
npm run dev -- expand --all
```

When a complexity report exists:
- Tasks are automatically expanded using the recommended subtask count and prompts
- When expanding all tasks, they're processed in order of complexity (highest first)
- Research-backed generation is preserved from the complexity analysis
- You can still override recommendations with explicit command-line options

Example workflow:
```bash
# Generate the complexity analysis report with research capabilities
npm run dev -- analyze-complexity --research

# Review the report in scripts/task-complexity-report.json

# Expand tasks using the optimized recommendations
npm run dev -- expand --id=8
# or expand all tasks
npm run dev -- expand --all
```

This integration ensures that task expansion is informed by thorough complexity analysis, resulting in better subtask organization and more efficient development.