Basecase: A Playground for Designing Buildable Robotics
An open-source platform integrating AI agents for streamlined robotics hardware design and development.
1Introducing the Basecase Platform
Basecase serves as a specialized playground dedicated to designing buildable robotics systems. The repository provides a structured environment for engineers to model hardware components and integrate them into functional assemblies. By focusing on buildability, the project aims to bridge the gap between initial conceptual design and the final physical manufacturing process.
2System Requirements and Setup
To run the application, users must have macOS and Node.js version 22 or later installed on their local machines. The installation process utilizes standard npm commands, specifically npm install followed by npm start. For active development, the project supports hot reloading through the npm run electron:dev command to accelerate iteration cycles.
3AI Agent Integration Protocol
The platform features an optional AI agent that interacts with your local environment via the Agent Client Protocol. This agent leverages Claude Code to assist in various design tasks. Developers are encouraged to review the AGENTS.md file first to understand the specific capabilities and operational boundaries of these integrated AI coding assistants.
4Automated Quality Assurance Workflow
Code integrity is maintained through strict pre-commit hooks that enforce formatting, linting rules, and automated tests. Developers must execute npm run check before pushing any changes to the repository. Additionally, the project requires running npm run test:e2e after any modifications are made to the user interface to ensure system stability.
5Extending the Robotics Catalog
Adding new components to the catalog is streamlined through the AI agent interface. Users can simply instruct the coding agent to add a specific part by providing a link. The process follows the logic defined in the .agents/skills/add-part/SKILL.md file, which also serves as a manual guide for those preferring direct configuration.
6Technical Architecture and Tooling
The repository utilizes a modern tech stack including Vite for build processes and Vitest for comprehensive testing suites. Configuration files like ruff.toml and various tsconfig files manage the project's TypeScript environment. This modular architecture allows for efficient handling of complex robotics data structures while maintaining high performance during the development phase.
7Development Lifecycle Management
The project structure includes dedicated folders for agents, bench testing, and electron-based UI components. By separating core logic from the interface, the platform allows for modular updates to the robotics design engine. The inclusion of wrangler.jsonc suggests potential compatibility with edge-based deployment or cloud-integrated services for future scalability of the platform.
8Strategic Impact on Robotics
Basecase represents a shift toward AI-assisted hardware engineering, reducing the manual overhead typically associated with component cataloging. By standardizing the design workflow through local agents and strict testing protocols, the project enables faster prototyping. This approach significantly lowers the barrier for developers looking to transition from digital designs to physical robotics builds.
Original article: Hacker News: Show HN — Basecase: A Playground for Designing Buildable Robotics