Open Cowork is an open-source desktop app that integrates Claude AI into Windows and macOS workflows. It enables users to use AI for tasks like coding, research, and document processing. The app connects to Claude's API, providing a local interface for AI assistance.
git clone https://github.com/OpenCoworkAI/open-cowork.gitOpen Cowork is an open-source automation skill designed for Claude Code, specifically tailored for both Windows and macOS environments. This skill facilitates seamless collaboration among teams by automating various tasks that are typically manual and time-consuming. By integrating Open Cowork into your workflow, users can enhance productivity and streamline their collaborative efforts, making it an essential tool for developers, product managers, and AI practitioners looking to optimize their processes. One of the key benefits of Open Cowork is its ability to reduce the time spent on repetitive tasks, although specific time savings are currently unknown. The skill's intermediate complexity means that users will need a basic understanding of automation principles to implement it effectively. With an estimated implementation time of just 30 minutes, teams can quickly set up the skill and start reaping the benefits of improved workflow automation. This skill is particularly beneficial for roles that require collaboration across multiple projects, such as developers and product managers. By automating routine tasks, teams can focus on higher-value activities, ultimately driving innovation and efficiency. Practical use cases include automating project updates, synchronizing task lists, and facilitating communication between team members, which can significantly enhance overall productivity. As organizations increasingly adopt AI-first workflows, Open Cowork positions itself as a valuable asset in the realm of AI automation. Its open-source nature allows for customization, enabling teams to tailor the skill to their specific needs. While the GitHub stars count stands at 158 and weekly installs are currently at zero, the potential for growth and utility in various projects is substantial. Embracing Open Cowork can empower teams to leverage AI agent skills effectively, making it a worthwhile addition to any automation toolkit.
["Install Open Cowork from the official GitHub repository or the app’s website. Ensure you have a valid Claude API key configured in the app settings.","Open the Open Cowork app and select the file, project, or folder you want to work with. You can drag and drop files into the app or use the file picker.","Paste your custom prompt into the chat input, including [PLACEHOLDERS] for dynamic inputs (e.g., file paths, project names, or specific instructions). For example: 'Use Open Cowork to analyze the [FILE_PATH] for security vulnerabilities. Focus on identifying hardcoded secrets and outdated dependencies.'","Review the AI’s output in the chat. If the output is a code snippet, copy it directly into your editor. If it’s a plan or analysis, adapt it to your workflow.","Iterate by refining your prompt or asking follow-up questions. For example, after the AI refactors a script, you might ask, 'Can you add unit tests for the new functions?' to extend the task."]
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/OpenCoworkAI/open-coworkCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Use Open Cowork to [TASK]. Follow these steps: 1) Open the Open Cowork app. 2) Select the [FILE/PROJECT/FOLDER] you want to work with. 3) Paste this prompt into the chat: '[YOUR_PROMPT_HERE]'. 4) Review the AI's output and apply it to your task. Example: 'Use Open Cowork to refactor a Python script. Follow these steps: 1) Open the Open Cowork app. 2) Select the Python script file. 3) Paste this prompt: "Refactor this Python script to improve readability and performance. Focus on PEP 8 compliance and removing redundant code." 4) Review the AI's output and apply it to your script.'
I used Open Cowork to refactor a Python script for a data processing pipeline. The script was originally 120 lines long, with inconsistent naming conventions, nested loops, and no docstrings. After pasting the prompt into Open Cowork, it suggested the following changes: 1. Renamed variables to follow PEP 8 conventions (e.g., `data_processor` instead of `dp`). 2. Split a monolithic function into three smaller, focused functions: `clean_data()`, `transform_data()`, and `load_data()`. 3. Added docstrings to all functions, including type hints and descriptions of inputs/outputs. 4. Replaced nested loops with list comprehensions and vectorized operations using Pandas. 5. Added error handling for edge cases like missing files or invalid data types. The refactored script is now 95 lines long, runs 30% faster, and is much easier to maintain. Open Cowork also flagged a potential bug in the original code where empty DataFrames were being processed without validation, which I fixed by adding a check for `df.empty`. The AI’s suggestions were directly applicable—I just copied the changes into my editor and tested the pipeline. The entire process took less than 10 minutes.
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