Repo Connect - Build and Run code end-to-end on Runloop
Next level with low-touch, automatic devbox setup from a github respository. Intelligent discovery of build commands, dependencies, and project structure
Repo Connect revolutionizes how AI agents interact with your codebase by automatically analyzing and understanding your repository’s structure, dependencies, and build processes.
This enables your AI agent to work with existing projects just like a human developer would - with the ability to build, test, and run your code without manual prompting.
Repo Connect uses a GitHub token to securely access your repository and employs a combination of semantic analysis and AI agents to intelligently discover:
Setup and build commands
Test execution procedures
Package managers and dependency installation
Environment initialization requirements
Available project commands and scripts
When successful, Repo Connect generates a Runloop blueprint that can then be used to create new Devboxes that are immediately ready for your AI agent to operate on your code, enabling features like running specific code paths, tracing and debugging, and making informed changes.
If Repo Connect cannot fully analyze your repository, it generates a partial inspection with discovered information pre-filled. You can then edit and complete the missing details to achieve a working state for your AI agent.The analysis results follow this structure:
Once Repo Connect has analyzed your repository, you can create Devboxes that are immediately ready for AI agent interaction:
Copy
Ask AI
import osfrom runloop_api_client import Runloopclient = Runloop( bearer_token=os.environ.get("RUNLOOP_API_KEY"), # This is the default and can be omitted)list_inspections = runloop_client.repositories.list_inspections(id='')inspection = next((inspection for inspection in list_inspections.inspections if inspection.status == "image_build_success"), None)if inspection: dbx = await runloop_client.devboxes.create_and_await_running( name='devbox-name', blueprint_id=inspection.blueprint_id ) print(dbx.id)
Your AI agent can now:
Execute discovered build and test commands
Navigate and understand your codebase structure
Make informed changes based on project conventions
This allows you to see the progression of your development environment and ensure your AI agent always has the most current understanding of your project.
Clear Documentation: Well-documented README.md or AGENTS.md files help Repo Connect understand your project structure
Standard Build Files: Use conventional build files (package.json, requirements.txt, Makefile) when possible
Environment Files: Include .env.example or similar files to help identify required environment variables. Repo Connect will ask for secret values if required
Review generated blueprints to ensure they capture your project’s requirements accurately
Version your blueprints alongside your code to maintain consistency
Test blueprints with fresh Devbox instances to verify completeness
Repo Connect works best with repositories that follow standard project conventions and include clear build instructions. For complex or non-standard setups, review the partial analysis results and add any missing configuration details.