app-builder

Full-stack app scaffolding from a natural language prompt is automated by detecting project type, selecting templates, and coordinating backend, frontend, and database agents to generate runnable project structures.

Multi-agent orchestration for project scaffolding coordinates specialized agents to plan database schemas, build backend APIs, and create frontend components based on a structured plan generated from your natural language input.

To generate a structured plan before building, the system creates and verifies a PLAN.md file in the project root, translating your request into task breakdowns for agent execution.

Yes, you can use natural language processing to select project templates and detect project type, as the system translates natural language requests into automated template selection and stack decisions.

App orchestration works without external dependencies, relying entirely on its internal multi-agent coordination to handle project detection, scaffolding, and full-stack generation.

The limitations of automating end-to-end app creation include relying on the initial prompt clarity for project-type detection and requiring PLAN.md verification before any execution can proceed.