🛠️ Agent Tools

A community-driven collection of tools for LangChain/LangGraph agents. Build smarter agents by plugging in ready-to-use tools or contribute your own.

Quick Start

# Clone the repository
git clone https://github.com/yourusername/agent-tools.git
cd agent-tools

# Create virtual environment with uv
uv venv
source .venv/bin/activate

# Install dependencies
uv pip install -r todo/requirements.txt

# Set up environment variables
cp .env.example .env
# Add your API keys to .env

Available Tools

Tool	Description	Status
Todo Manager	Track progress during multi-step agent tasks	✅ Ready

Usage

Using the Todo Tools

from langchain.agents import create_agent
from langchain_google_genai import ChatGoogleGenerativeAI
from todo.tools import TODO_TOOLS

model = ChatGoogleGenerativeAI(model="gemini-2.5-flash")

agent = create_agent(
    model=model,
    tools=TODO_TOOLS,
    system_prompt=open("todo/prompt.md").read()
)

for chunk in agent.stream({
    "messages": [("user", "Build a Next.js app with Tailwind")]
}, stream_mode="values"):
    chunk["messages"][-1].pretty_print()

Available Todo Operations

• create_todo(title, task_group) - Create a trackable task
• list_todos(task_group) - View all tasks in a group
• update_todo(task_group, todo_id, status) - Mark as completed/cancelled
• delete_todo(task_group, todo_id) - Remove a task

Contributing

We welcome contributions! Here's how to add your own tools:

Adding a New Tool

1. Fork & Clone

   git clone https://github.com/yourusername/agent-tools.git
   cd agent-tools

2. Create a new tool directory

   mkdir my_tool
   cd my_tool

3. Structure your tool

   my_tool/
   ├── __init__.py
   ├── tools.py          # Your tool implementations
   ├── prompt.md         # System prompt for the agent
   └── requirements.txt  # Tool-specific dependencies
   

4. Implement your tools in tools.py:

   from langchain_core.tools import tool
   from typing import Annotated
   
   @tool
   def my_awesome_tool(
       param: Annotated[str, "Description of the parameter"]
   ) -> str:
       """Clear docstring explaining what the tool does.
       
       Include:
       - When to use this tool
       - What it returns
       - Example usage
       """
       # Your implementation
       return "result"
   
   MY_TOOLS = [my_awesome_tool]

5. Write a system prompt in prompt.md explaining how the agent should use your tools

6. Submit a Pull Request

Tool Guidelines

• ✅ Use clear, descriptive tool names
• ✅ Write comprehensive docstrings (agents read these!)
• ✅ Use Annotated types for parameter descriptions
• ✅ Include a prompt.md with usage guidelines
• ✅ Add tool-specific dependencies to a local requirements.txt
• ✅ Include example usage in your PR description

Pull Request Process

1. Ensure your tool works with the latest LangChain/LangGraph
2. Update the README table with your new tool
3. Add any new dependencies
4. Submit PR with a clear description and example usage

Project Structure

agent-tools/
├── README.md
├── .env.example
├── .gitignore
├── todo/                    # Todo management tools
│   ├── __init__.py
│   ├── agent.py            # Example agent implementation
│   ├── tools.py            # Tool definitions
│   ├── prompt.md           # System prompt
│   └── requirements.txt    # Dependencies
└── your_tool/              # Your contribution here!
    ├── __init__.py
    ├── tools.py
    ├── prompt.md
    └── requirements.txt

Environment Variables

Create a .env file with your API keys:

GOOGLE_API_KEY=your_google_api_key
OPENAI_API_KEY=your_openai_api_key
# Add other provider keys as needed

Requirements

• Python 3.10+
• LangChain 1.0+
• LangGraph 1.0+

License

MIT License - see LICENSE for details.

Show Your Support

Give a ⭐ if this project helped you build better agents!

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