

Repo Prompt
Overview :
Repo Prompt is a native application designed for macOS that aims to reduce friction when interacting with powerful language models while using local files. It allows users to select files and folders as prompts for context, guiding the AI's output through saved prompts and repository mappings to either iterate files or understand their workings. Key benefits include increased development efficiency, precise control over context, and thorough review of changes made by AI. Background information reveals that this tool is targeted at developers and technical personnel, optimized to enhance code and file processing workflows by integrating the latest AI technologies. The product currently offers a free trial, though specific pricing details are not provided on the page.
Target Users :
Target audience includes developers, programmers, and technical professionals, especially those who frequently handle code and files. Repo Prompt integrates AI technology to help them iterate and review code more efficiently, thereby enhancing productivity and code quality.
Use Cases
Developers use Repo Prompt to quickly iterate project code, enhancing development efficiency.
Technical teams utilize Repo Prompt to review code changes, ensuring code quality.
Individual developers employ Repo Prompt to learn about code functionality, improving their programming skills.
Features
- Select files and folders to provide context for AI output.
- Use saved prompts and repository mappings to guide AI.
- Iterate files or understand their functionality.
- Maintain complete control over context.
- Review changes made by AI file by file.
- Approve changes one by one or in bulk.
- Supports the macOS platform.
How to Use
1. Visit the Repo Prompt official website and download the macOS application.
2. Install and launch the Repo Prompt application.
3. Select the files and folders you wish to process and set them as context for the AI.
4. Use saved prompts or create new ones to guide the AI's output.
5. Iterate through the files or learn how they function as needed.
6. Review changes made by the AI and approve them one by one or in batches.
7. Save the changes or conduct further edits as required.
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