uploads.sh is a command-line tool that serves as an upload command for coding agents. It addresses the lack of a built-in way for agents to demonstrate their work on GitHub by capturing screenshots during development. These screenshots are staged automatically for the current branch and appear in a single tidy attachments comment once a pull request opens.
The tool provides several commands for managing screenshots and related assets. A bare put command on a branch stages files automatically without requiring a branch flag or an open pull request. The uploads screenshot command captures and hosts an image in one step. Users can check queued items with uploads staged, attach files immediately to an existing pull request or issue with uploads attach, and tag uploads using the --meta key=value option for later retrieval via uploads find. Setup can occur with --state before or after, and the tool supports installation through npm as a global package with the command npm install -g @buildinternet/uploads.
Integration with GitHub occurs through the optional uploads-sh GitHub App, which requires installation by a repository owner. With the app, comments post as the uploads-sh bot account and staged screenshots promote automatically when a pull request opens. The tool also recommends updating files such as AGENTS.md or CLAUDE.md to ensure screenshots are captured at milestones during UI changes. It is intended for use by coding agents and developers working with GitHub pull requests.
uploads.sh is a Developer Tools project. It focuses on coding agents and AI developers having no easy way to visually document their work and attach screenshots to pull requests. uploads.sh is an open-source project aimed at developers. The project is open source (Apache-2.0). uploads.sh is available on the command line.
Behind uploads.sh is buildinternet, and it first shipped in 2026. Development happens publicly on GitHub with 395 commits in the last 90 days. Key capabilities include Screenshot Capture, PR Attachments, and Staged Uploads.
Summary written by a language model from the project’s public pages.
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