Create implementation plans and task breakdowns from feature requests by analyzing codebases. Generates structured documentation with requirements, numbered tasks, dependencies, and testing guidance for systematic development workflows.
Extract color variables from Figma DSL files and export them to formats like UnoCSS, TailwindCSS, or custom standards for streamlined design-to-code workflows.
Facilitates spec-driven development workflows by providing structured prompts for generating requirements in EARS format, design documents, and implementation code following a systematic approach.
Enables AI-guided spec-driven development workflow that transforms ideas into implementation through structured stages: goal collection, requirements gathering in EARS format, technical design documentation, task planning, and systematic code execution.
A proof-of-concept Model Context Protocol server that enables LLM applications to interact with Uber Eats, allowing AI agents to browse and order food through natural language.