TypeScript
Zod
JSON Schema
OpenAPI (Swagger)
GraphQL
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tRPC
Prisma
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Drizzle ORM
Node.js
React
Next.js
GitHub
PostgreSQL
Docker
Join our community to see how developers are using Workik AI everyday.
Supported AI models on Workik
GPT 5.2 Codex, GPT 5.2, GPT 5.1 Codex, GPT 5.1, GPT 5 Mini, GPT 5
Gemini 3.1 Pro, Gemini 3 Flash, Gemini 3 Pro, Gemini 2.5 Pro
Claude 4.6 sonnet, Claude 4.5 Sonnet, Claude 4.5 Haiku, Claude 4 Sonnet
Deepseek Reasoner, Deepseek Chat, Deepseek R1(High)
Grok 4.1 Fast, Grok 4, Grok Code Fast 1
Models availability might vary based on your plan on Workik
Features
Generate Types
AI converts JSON, API schemas, and responses into strongly typed, reusable TypeScript definitions.
Generate API Types
Generate TypeScript definitions from OpenAPI, GraphQL, JSON Schema, Prisma, and tRPC contracts using AI.
Sync Contracts
Keep shared types aligned across APIs, services, and frontend applications with AI context.
Refactor Definitions
Update and refactor legacy interfaces, schemas, and evolving data structures across codebases with AI.
TESTIMONIALS
Real Stories, Real Results with Workik
"Workik AI is the fastest way to generate shared types across services. AI saved hours on DTO creation and keeps contracts aligned."
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Venkatesh Iyer
Full Stack Developer
"I use Workik AI everyday for request and response models. It helps refactor legacy type definitions without slowing down our release cycles."
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Marcus West
Backend Engineer
"As someone still growing in TypeScript, Workik AI makes complex interfaces much easier to build. It helps me understand how API payloads translate into reusable types."
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Dara Kamol
Junior Software Developer
What are the most popular use cases of Workik’s Type Definition Generator for developers?
Developers use Workik AI across a wide range of type definition generation and schema modeling workflows, including:
• Generate TypeScript interfaces from JSON API responses for faster frontend integration
• Convert nested objects into reusable TypeScript types for React and Next.js applications
• Create DTOs, request models, and response contracts for Node.js and backend services
• Build shared frontend and backend types to keep data contracts aligned
• Create types from Swagger or OpenAPI schemas for faster service integration
• Refactor legacy type definitions and evolving schemas as APIs change
What context options can developers use in Workik for Type Definition generation?
Adding context in Workik is completely optional. When provided, it helps the AI generate more accurate and project-specific type definitions.
• GitHub, GitLab, Azure DevOps, and Bitbucket repositories to understand existing TypeScript codebases, shared interfaces, DTO patterns, and naming conventions
• Code snippets such as interfaces, type aliases, React props, API response models, and utility types
• Sample JSON payloads for JSON to TypeScript interface generation and nested object typing
• Swagger, OpenAPI, GraphQL, and JSON schema definitions for request and response model generation
• Database schemas, ORM models, and Prisma entities to align generated types with the data layer
• Project files including technical docs, API specs, .ts files, and .d.ts definitions
Can Workik AI generate reusable generic types and schema based interfaces?
Absolutely. Beyond basic interfaces, developers often need reusable patterns like paginated responses, API wrappers, shared result types, and service level contracts. Workik AI can help generate scalable generic types such as ApiResponse<T>, reusable model abstractions, and utility types that reduce repetition across the codebase. It can also work with Swagger, OpenAPI, GraphQL, and JSON schema definitions to generate request models, response interfaces, and DTOs instead of manually recreating them.
How does Workik AI help when APIs change?
This is where Workik AI becomes extremely useful, especially when an API evolves and field names, nested structures, or response formats change, because instead of manually updating every related interface, AI can help refactor existing type definitions and suggest updated models across the project. This saves time during maintenance and reduces contract mismatches.
Is Workik AI useful beyond frontend work?
Definitely. While many developers use it for React props and API responses, backend and full-stack teams use it for DTOs, service contracts, webhook payloads, event schemas, and shared domain models. This makes it highly relevant for Node.js, microservices, and full-stack TypeScript workflows.
Does Workik AI support strict TypeScript patterns like union types, optional fields, and enums during generation?
Yes, and this goes well beyond basic interface creation. Real world API responses often include fields that accept multiple value types, properties that are not always returned, and status values mapped to fixed sets. Workik AI handles this by generating union types like "active" or "inactive", optional fields using the ? modifier, enums, and discriminated unions, producing interfaces that are strict, readable, and ready for production without requiring manual cleanup.
How does Workik AI handle runtime validation alongside TypeScript type generation?
TypeScript interfaces provide compile-time safety but do not validate data at runtime. Workik AI bridges this gap by generating TypeScript interfaces alongside matching Zod or Yup schemas, keeping z.infer<typeof Schema> in sync with the interface exactly. This makes it highly practical for applications consuming external APIs, handling user input, or processing webhook payloads where runtime validation matters as much as type safety.
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Type Definition: Question & Answer
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