parse-prd command (#1048)
* initial cutover * update log to debug * update tracker to pass units * update test to match new base tracker format * add streamTextService mocks * remove unused imports * Ensure the CLI waits for async main() completion * refactor to reduce code duplication * update comment * reuse function * ensure targetTag is defined in streaming mode * avoid throwing inside process.exit spy * check for null * remove reference to generate * fix formatting * fix textStream assignment * ensure no division by 0 * fix jest chalk mocks * refactor for maintainability * Improve bar chart calculation logic for consistent visual representation * use custom streaming error types; fix mocks * Update streamText extraction in parse-prd.js to match actual service response * remove check - doesn't belong here * update mocks * remove streaming test that wasn't really doing anything * add comment * make parsing logic more DRY * fix formatting * Fix textStream extraction to match actual service response * fix mock * Add a cleanup method to ensure proper resource disposal and prevent memory leaks * debounce progress updates to reduce UI flicker during rapid updates * Implement timeout protection for streaming operations (60-second timeout) with automatic fallback to non-streaming mode. * clear timeout properly * Add a maximum buffer size limit (1MB) to prevent unbounded memory growth with very large streaming responses. * fix formatting * remove duplicate mock * better docs * fix formatting * sanitize the dynamic property name * Fix incorrect remaining progress calculation * Use onError callback instead of console.warn * Remove unused chalk import * Add missing custom validator in fallback parsing configuration * add custom validator parameter in fallback parsing * chore: fix package-lock.json * chore: large code refactor * chore: increase timeout from 1 minute to 3 minutes * fix: refactor and fix streaming * Merge remote-tracking branch 'origin/next' into joedanz/parse-prd-progress * fix: cleanup and fix unit tests * chore: fix unit tests * chore: fix format * chore: run format * chore: fix weird CI unit test error * chore: fix format --------- Co-authored-by: Ralph Khreish <35776126+Crunchyman-ralph@users.noreply.github.com>
Taskmaster: A task management system for AI-driven development, designed to work seamlessly with any AI chat.
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Docs
By @eyaltoledano & @RalphEcom
A task management system for AI-driven development with Claude, designed to work seamlessly with Cursor AI.
Documentation
For detailed guides, API references, and comprehensive examples, visit our documentation site.
Quick Reference
The following documentation is also available in the docs directory:
- Configuration Guide - Set up environment variables and customize Task Master
- Tutorial - Step-by-step guide to getting started with Task Master
- Command Reference - Complete list of all available commands
- Task Structure - Understanding the task format and features
- Example Interactions - Common Cursor AI interaction examples
- Migration Guide - Guide to migrating to the new project structure
Quick Install for Cursor 1.0+ (One-Click)
Note: After clicking the link, you'll still need to add your API keys to the configuration. The link installs the MCP server with placeholder keys that you'll need to replace with your actual API keys.
Requirements
Taskmaster utilizes AI across several commands, and those require a separate API key. You can use a variety of models from different AI providers provided you add your API keys. For example, if you want to use Claude 3.7, you'll need an Anthropic API key.
You can define 3 types of models to be used: the main model, the research model, and the fallback model (in case either the main or research fail). Whatever model you use, its provider API key must be present in either mcp.json or .env.
At least one (1) of the following is required:
- Anthropic API key (Claude API)
- OpenAI API key
- Google Gemini API key
- Perplexity API key (for research model)
- xAI API Key (for research or main model)
- OpenRouter API Key (for research or main model)
- Claude Code (no API key required - requires Claude Code CLI)
Using the research model is optional but highly recommended. You will need at least ONE API key (unless using Claude Code). Adding all API keys enables you to seamlessly switch between model providers at will.
Quick Start
Option 1: MCP (Recommended)
MCP (Model Control Protocol) lets you run Task Master directly from your editor.
1. Add your MCP config at the following path depending on your editor
| Editor | Scope | Linux/macOS Path | Windows Path | Key |
|---|---|---|---|---|
| Cursor | Global | ~/.cursor/mcp.json |
%USERPROFILE%\.cursor\mcp.json |
mcpServers |
| Project | <project_folder>/.cursor/mcp.json |
<project_folder>\.cursor\mcp.json |
mcpServers |
|
| Windsurf | Global | ~/.codeium/windsurf/mcp_config.json |
%USERPROFILE%\.codeium\windsurf\mcp_config.json |
mcpServers |
| VS Code | Project | <project_folder>/.vscode/mcp.json |
<project_folder>\.vscode\mcp.json |
servers |
Manual Configuration
Cursor & Windsurf (mcpServers)
{
"mcpServers": {
"task-master-ai": {
"command": "npx",
"args": ["-y", "--package=task-master-ai", "task-master-ai"],
"env": {
"ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
"PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
"OPENAI_API_KEY": "YOUR_OPENAI_KEY_HERE",
"GOOGLE_API_KEY": "YOUR_GOOGLE_KEY_HERE",
"MISTRAL_API_KEY": "YOUR_MISTRAL_KEY_HERE",
"GROQ_API_KEY": "YOUR_GROQ_KEY_HERE",
"OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY_HERE",
"XAI_API_KEY": "YOUR_XAI_KEY_HERE",
"AZURE_OPENAI_API_KEY": "YOUR_AZURE_KEY_HERE",
"OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY_HERE"
}
}
}
}
🔑 Replace
YOUR_…_KEY_HEREwith your real API keys. You can remove keys you don't use.
Note
: If you see
0 tools enabledin the MCP settings, try removing the--package=task-master-aiflag fromargs.
VS Code (servers + type)
{
"servers": {
"task-master-ai": {
"command": "npx",
"args": ["-y", "--package=task-master-ai", "task-master-ai"],
"env": {
"ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
"PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
"OPENAI_API_KEY": "YOUR_OPENAI_KEY_HERE",
"GOOGLE_API_KEY": "YOUR_GOOGLE_KEY_HERE",
"MISTRAL_API_KEY": "YOUR_MISTRAL_KEY_HERE",
"GROQ_API_KEY": "YOUR_GROQ_KEY_HERE",
"OPENROUTER_API_KEY": "YOUR_OPENROUTER_KEY_HERE",
"XAI_API_KEY": "YOUR_XAI_KEY_HERE",
"AZURE_OPENAI_API_KEY": "YOUR_AZURE_KEY_HERE",
"OLLAMA_API_KEY": "YOUR_OLLAMA_API_KEY_HERE"
},
"type": "stdio"
}
}
}
🔑 Replace
YOUR_…_KEY_HEREwith your real API keys. You can remove keys you don't use.
2. (Cursor-only) Enable Taskmaster MCP
Open Cursor Settings (Ctrl+Shift+J) ➡ Click on MCP tab on the left ➡ Enable task-master-ai with the toggle
3. (Optional) Configure the models you want to use
In your editor's AI chat pane, say:
Change the main, research and fallback models to <model_name>, <model_name> and <model_name> respectively.
For example, to use Claude Code (no API key required):
Change the main model to claude-code/sonnet
Table of available models | Claude Code setup
4. Initialize Task Master
In your editor's AI chat pane, say:
Initialize taskmaster-ai in my project
5. Make sure you have a PRD (Recommended)
For new projects: Create your PRD at .taskmaster/docs/prd.txt
For existing projects: You can use scripts/prd.txt or migrate with task-master migrate
An example PRD template is available after initialization in .taskmaster/templates/example_prd.txt.
Note
While a PRD is recommended for complex projects, you can always create individual tasks by asking "Can you help me implement [description of what you want to do]?" in chat.
Always start with a detailed PRD.
The more detailed your PRD, the better the generated tasks will be.
6. Common Commands
Use your AI assistant to:
- Parse requirements:
Can you parse my PRD at scripts/prd.txt? - Plan next step:
What's the next task I should work on? - Implement a task:
Can you help me implement task 3? - View multiple tasks:
Can you show me tasks 1, 3, and 5? - Expand a task:
Can you help me expand task 4? - Research fresh information:
Research the latest best practices for implementing JWT authentication with Node.js - Research with context:
Research React Query v5 migration strategies for our current API implementation in src/api.js
More examples on how to use Task Master in chat
Option 2: Using Command Line
Installation
# Install globally
npm install -g task-master-ai
# OR install locally within your project
npm install task-master-ai
Initialize a new project
# If installed globally
task-master init
# If installed locally
npx task-master init
# Initialize project with specific rules
task-master init --rules cursor,windsurf,vscode
This will prompt you for project details and set up a new project with the necessary files and structure.
Common Commands
# 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
# Show specific task(s) - supports comma-separated IDs
task-master show 1,3,5
# Research fresh information with project context
task-master research "What are the latest best practices for JWT authentication?"
# Move tasks between tags (cross-tag movement)
task-master move --from=5 --from-tag=backlog --to-tag=in-progress
task-master move --from=5,6,7 --from-tag=backlog --to-tag=done --with-dependencies
task-master move --from=5 --from-tag=backlog --to-tag=in-progress --ignore-dependencies
# Generate task files
task-master generate
# Add rules after initialization
task-master rules add windsurf,roo,vscode
Claude Code Support
Task Master now supports Claude models through the Claude Code CLI, which requires no API key:
- Models:
claude-code/opusandclaude-code/sonnet - Requirements: Claude Code CLI installed
- Benefits: No API key needed, uses your local Claude instance
Learn more about Claude Code setup
Troubleshooting
If task-master init doesn't respond
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
Contributors
Star History
Licensing
Task Master is licensed under the MIT License with Commons Clause. This means you can:
✅ Allowed:
- Use Task Master for any purpose (personal, commercial, academic)
- Modify the code
- Distribute copies
- Create and sell products built using Task Master
❌ Not Allowed:
- Sell Task Master itself
- Offer Task Master as a hosted service
- Create competing products based on Task Master
See the LICENSE file for the complete license text and licensing details for more information.
