This project provides a framework for transforming a coding agent into a personal work assistant, enabling 10x productivity across an organization without complex IT integration. It targets all user roles, from executives to developers, by allowing agents to securely connect to and automate tasks across existing work tools, leveraging institutional knowledge and compounding automation capabilities.

How It Works

The core philosophy is to leverage the user's existing laptop environment as the platform, with the agent acting as a smarter version of the user. It adheres to four principles: local agent as the universal client, security by locality (mirroring user threat models), identity equals accountability (using personal tokens), and zero friction for setup. Unlike traditional AI integrations requiring middleware and new permissions, this approach uses existing surfaces like browsers, CLIs, and REST APIs. A key differentiator is its "read + write + act" capability, allowing the agent not just to retrieve information but to actively update tickets, post summaries, and open pull requests, making the output the completed action rather than just text.

Quick Start & Requirements

1. Install Cursor: Download from cursor.com/download (Windows/macOS).
2. Clone the repository: git clone https://github.com/ZhixiangLuo/10xProductivity.git
3. Open the cloned folder in Cursor.
4. Ensure Python 3.12 is installed (or follow setup-python.md for guided installation, which also sets up a virtual environment and Playwright).
5. Point your agent at setup.md within the repository to configure tool connections. The agent will guide the process of selecting tools, handling credentials, and verifying connections.

Highlighted Details

• Connected Knowledge: Enables querying across multiple systems (e.g., Slack, Jira, GitHub, Confluence) simultaneously for synthesized answers.
• Cross-Tool Reasoning: Facilitates complex queries that span different tools, such as identifying PagerDuty incidents with outstanding, inactive Jira follow-ups.
• Compound Automation: Transforms repetitive, multi-step tasks into single agent instructions.
• Enterprise Search: A built-in workflow to query all connected tools (Slack, Confluence, Jira, Linear, Notion, GitHub, etc.) in a single request.
• Read + Write + Act: Agents can perform actions like updating Jira tickets or posting Slack summaries, not just retrieving information.

Maintenance & Community

Contributions are welcomed for new tools, authentication variants, deployment variants, or improvements to existing connections. The process involves using the agent to load add-new-tool.md, researching authentication, validating snippets, and optionally submitting a Pull Request. Community contributions can be placed in staging/, while core contributions require multi-environment validation. Issues can be opened for problems or feature requests.

Licensing & Compatibility

The project is released under the MIT license. However, users must consult LEGAL_NOTICE.md as automating actions on external platforms may violate their respective Terms of Service.

Limitations & Caveats

The project explicitly states it "won't work out of the box" and requires user setup. A significant caveat is that organizational rewards may not scale with individual productivity gains from automation, potentially leading to increased workloads rather than compensation. Automation of external platforms carries a risk of violating Terms of Service.