open-computer-use

🥈Silver

Open Computer Use enables AI agents to autonomously control computers at scale. It is an open-source platform for browser-based computer control, suitable for operations teams. It connects to Claude and other LLM agents, allowing them to perform tasks like GUI automation and CLI operations.

412350Updated 3w ago

Intermediate30min to implementautomation

Saves ~480 min per use

Quick InstallView Source

git clone https://github.com/LLmHub-dev/open-computer-use.git

Works with:

Claude

Overview

About This Skill

How to Use

[{"step":"Install Open Computer Use on the target computer. Follow the [official installation guide](https://github.com/open-computer-use/docs) to set up the browser extension and CLI tools. Ensure the target computer has the necessary permissions to perform the task.","tip":"Use the CLI tool `ocu-setup` to configure the agent’s access level. For GUI automation, enable the browser extension and grant it the required permissions."},{"step":"Connect the AI agent (e.g., Claude) to Open Computer Use. Use the agent’s configuration to specify the target computer’s IP/hostname and authentication method (e.g., SSH, RDP, or local session).","tip":"For remote computers, ensure the agent has a persistent connection (e.g., via SSH tunnel or RDP). Test the connection with a simple command like `ocu-ping` before proceeding."},{"step":"Define the task using the prompt template. Replace [TASK] with the specific automation steps (e.g., downloading files, filling forms, or running scripts). Include any required inputs like file paths or credentials.","tip":"Break down complex tasks into smaller steps. For example, separate file downloads from post-processing tasks to improve reliability."},{"step":"Execute the task and monitor the output. Use the agent’s logs or the Open Computer Use dashboard to track progress. Verify the results match expectations.","tip":"For long-running tasks, use the `ocu-watch` command to monitor progress in real-time. If an error occurs, review the logs and adjust the task definition accordingly."},{"step":"Integrate the automation into your workflow. For example, schedule the task to run monthly using a cron job or Windows Task Scheduler. Store outputs in a shared drive or database for further processing.","tip":"Test the automation in a staging environment before deploying it to production. Use the `ocu-dry-run` flag to simulate the task without making changes."}]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/LLmHub-dev/open-computer-use

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Use Open Computer Use to automate [TASK] on [TARGET_COMPUTER]. For example: 'Automate the process of downloading monthly sales reports from [WEBSITE_URL], saving them to [LOCAL_PATH], and renaming files with the current date.' Include any specific steps or tools needed, such as browser extensions or CLI commands.

Example Output

I’ve successfully automated the monthly sales report download process on the target computer. Here’s what happened:

1. **Browser Automation**: The AI agent opened Google Chrome and navigated to the sales reports portal at `https://reports.company.com/monthly`. It logged in using the stored credentials (username: `sales_team`, password: `*****`).

2. **File Handling**: The agent downloaded the report for July 2024, which was a 12MB Excel file named `monthly_sales_july_2024.xlsx`. It saved the file to `C:\Users\Public\Downloads\` and then moved it to the designated folder at `D:\Reports\2024\July\`.

3. **Renaming and Logging**: The file was renamed to `Sales_Report_July_2024.xlsx` to standardize the naming convention. A log entry was created in `D:\Reports\download_log.txt` with the timestamp `2024-08-01 14:32:10`, noting the successful download and file path.

4. **CLI Verification**: The agent ran a PowerShell command to verify the file’s integrity: `Get-FileHash D:\Reports\2024\July\Sales_Report_July_2024.xlsx -Algorithm SHA256` and confirmed the hash matched the expected value.

The entire process took 2 minutes and 45 seconds, with no manual intervention required. The report is now ready for further processing or distribution.