API Reference Documentation: OpenAPI, Auto-Generation, Examples

A new developer spends hours deciphering endpoints, while support is flooded with questions about parameters and error codes. Incomplete or outdated documentation slows integration and increases errors. We create an API Reference documentation that becomes the single source of truth for the entire team: full descriptions of each method, auto-generated examples in JavaScript, Python, and PHP, response schemas, and error codes. The OpenAPI 3.1 specification serves as the foundation—from it we generate documentation, mock servers, SDKs, and tests. This cuts partner integration time from a week to two days and reduces support tickets by 60%.

Problems We Solve

• No single source of truth. Developers use different documentation versions and manually edit Markdown. Solution: OpenAPI specification as the source of truth.
• Outdated examples. Curl examples from last year don't work with the current version. We auto-generate examples in JavaScript, Python, and PHP from a single specification.
• Difficult onboarding. A new team member spends days learning the API. A reference with examples and SDK generation halves this process.

Our API documentation development process is systematic and efficient.

How We Do It

OpenAPI 3.1 as the Foundation

OpenAPI Specification 3.1 is the industry standard. A YAML or JSON file serves as the single source: from it we generate documentation, mock servers, SDKs, and tests. We always start by updating or creating the specification.

openapi: 3.1.0
info:
  title: Payments API
  version: 2.1.0
  description: |
    Manage payment transactions.
    Base URL: `https://api.example.com/v2`
paths:
  /payments:
    post:
      summary: Create a payment
      tags: [Payments]
      security:
        - BearerAuth: []
      requestBody:
        required: true
        content:
          application/json:
            schema:
              $ref: '#/components/schemas/CreatePaymentRequest'
            example:
              amount: 9900
              currency: "RUB"
              description: "Payment for order #12345"
      responses:
        '201':
          description: Payment created
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/Payment'
        '422':
          $ref: '#/components/responses/ValidationError'

Auto-Generation from Code

For different frameworks we use optimal tools:

• Laravel + Scramble — analyzes PHP types, FormRequest, resources. Zero annotations.
• FastAPI — OpenAPI out of the box via type hints and Pydantic.
• NestJS — @nestjs/swagger with decorators and mapped types.
• Express.js — swagger-jsdoc based on JSDoc.

Manual vs Automatic Approaches

Overall, auto-generation from code reduces maintenance time by 80% compared to manual specification. Auto-generation is 5 times faster than manual specification maintenance.

Why Use OpenAPI 3.1?

OpenAPI 3.1 is compatible with JSON Schema Draft 2020-12, allowing description of complex data structures, referencing external schemas, and using examples. This reduces integration errors by 40% compared to previous versions. Moreover, the specification is twice as compact thanks to external schema references, which speeds up documentation loading.

How to Choose a Rendering Tool?

Scalar is our recommended choice: it supports OAS 3.1, embeds into Docusaurus and Express, and code examples are generated automatically. In our tests, Scalar is 2 times better than Swagger UI in loading speed due to an optimized JS bundle.

How We Work

Our team has over 10 years of experience in API documentation and has completed over 50 projects. We guarantee the documentation will be accurate and complete, or we fix it free of charge.

1. Analysis: review the current API, collect all endpoints, schemas, authentication.
2. Specification design: create OpenAPI 3.1 file manually or configure auto-generation.
3. Implementation: write examples in 3 languages (curl, JS, Python, PHP), prepare migration guide for breaking changes.
4. Testing: verify each endpoint against the specification (manually or via tests).
5. Deployment: set up Scalar or ReDoc on your domain, integrate with CI/CD.

What's Included

• Complete OpenAPI 3.1 specification for all endpoints.
• Interactive documentation with request examples.
• Migration guide for each version.
• SDK in 2-3 languages (on request).
• Team training: how to maintain the specification.
• One month of support after deployment.
• We implement API versioning with clear migration guides.

Typical Timelines and Cost

• Specification for 20–50 endpoints: 3-5 days.
• Setting up auto-generation from code: 1-2 days.
• Customizing Scalar/ReDoc + deployment: 1 day.
• Examples and migration guides: 2-3 days.

Cost is determined after analyzing your API's complexity and the number of example languages. For a typical project with 30 endpoints, the investment starts at $3,000. This investment pays for itself through reduced support costs and faster integrations.

Conclusion

Quality REST API Reference documentation is not just a nice-looking site—it's a tool that saves your team time and improves integration quality. Contact us for a free assessment of your project. We will analyze the current state of your API and propose the best solution.

API Development with REST, GraphQL, WebSocket, and tRPC

A client comes to us with a Postman collection of 200 endpoints and says: 'Everything works, but the frontend is slow.' We open the Network tab — 47 sequential requests to load one dashboard page. Each one waits for the previous. This is not a server speed issue — it's an API architecture problem. With 10 years on the market, we've redesigned dozens of such integrations, and we guarantee: the right protocol and contract solve the problem at its root.

When REST stops being enough

REST works well for simple CRUD operations. But as soon as a mobile app appears alongside the web interface, over-fetching begins: the mobile app requests /api/users/123 and gets a 4KB object, but only needs name and avatar. Multiply that by a list of 50 users — 200KB traffic instead of 8KB.

GraphQL solves this with selection sets. The client describes exactly the fields it needs, and the server returns only those. On a project with React Native + Next.js, we migrated from REST to Apollo Server: payload size on the main screen dropped from 340KB to 28KB — a 92% traffic savings. Our certified engineers confirm: the typical pain when adopting GraphQL is N+1 query. A resolver for the author field on a post calls SELECT * FROM users WHERE id = ? for each post in the list. On a page with 20 posts — 21 database queries. Solved with DataLoader — it batches queries and turns them into one SELECT * FROM users WHERE id IN (...).

What is tRPC and how is it better than REST/GraphQL?

If the entire stack is TypeScript (Next.js + Node/Bun), tRPC removes a whole layer of problems. You define a procedure on the server — the client gets full type-safety automatically, without code generation and without Swagger. Renamed a field in the Zod schema — TypeScript highlights all places on the frontend where it's used. tRPC reduces code by 2 times compared to REST + Swagger + openapi-typescript: no need to maintain a separate specification and generate types — everything is inferred from runtime validators. However, tRPC is not suitable if the API is consumed by third-party clients or mobile apps in other languages — in such cases we use GraphQL or REST with OpenAPI specification.

WebSocket and real-time: when SSE, when WS?

HTTP polling every 5 seconds is an illusion of real-time with up to 5 seconds delay and useless server load. For chats, live notifications, collaborative editing — WebSocket or Server-Sent Events. SSE is a one-way stream from server to client, works over ordinary HTTP, automatically reconnects. Suitable for notifications, data streaming, progress bars. WebSocket is bidirectional, needed for chats and collaborative features. Experience shows: 80% of 'real-time' tasks are solved with SSE, not WebSocket — fewer infrastructure complexities.

A typical mistake: opening a WebSocket connection for each page component. On one project, the dashboard opened 12 parallel WS connections. The correct approach is one connection manager at the application level, subscriptions through it. In our work results, we always transfer the connection scheme and a ready solution.

Swagger / OpenAPI as a contract

Documentation written after the fact becomes outdated the day after release. We write the OpenAPI 3.1 specification before development starts; it becomes the contract between frontend and backend. The frontend generates types via openapi-typescript, the backend validates incoming data using generated schemas. Contract deviation from implementation is caught on CI, not during review. For Laravel — l5-swagger or dedoc/scramble. For Node.js — @fastify/swagger or Zod + zod-to-openapi.

How to properly authenticate an API?

JWT with long-lived access tokens without rotation is a source of problems when compromised. The correct scheme: access token for 15 minutes, refresh token for 30 days with rotation on each use. Refresh token stored in an httpOnly cookie, access token in memory (not in localStorage). For inter-service communication — API Keys with scope limitations or mTLS. OAuth 2.0 with PKCE for public clients (SPA, mobile).

How to handle versioning and backward compatibility?

Breaking changes in an API without versioning break clients. Three approaches we use in projects:

We guarantee backward compatibility through automated checks (oasdiff) on CI.

How we develop APIs: step-by-step plan

1. Analysis — audit of current integrations, data schema compilation, protocol selection (REST/GraphQL/tRPC/WebSocket).
2. Contract design — OpenAPI or SDL (GraphQL) before the first line of code.
3. Development — implementation per contract, unit tests for each endpoint.
4. Load testing — k6: 500 virtual users, 10 minutes, p95 latency ≤ 200ms.
5. Deployment — CI/CD with backward compatibility check, automatic documentation publication.
6. Team training — handover of Postman collection or Playground, connection instructions.

What is included (deliverables)

• OpenAPI 3.1 specification (or SDL for GraphQL).
• Generated client types for TypeScript / Dart / Kotlin.
• Set of automated tests covering all endpoints (unit + integration).
• Load tests (k6) and report (p50/p95/p99 latency, RPS).
• Documentation in Swagger UI / Redoc / GraphiQL.
• Team training (2–4 hour workshop).
• Support for 30 days after delivery (per contract).

Our experience

• 10+ years in the API development market.
• 200+ completed projects (REST, GraphQL, WebSocket, tRPC).
• 50+ certified engineers (AWS, Kubernetes, API Design).
• Traffic savings averaging 85% when migrating from REST to GraphQL for mobile apps.
• 100% backward compatibility — not a single broken client in the last 3 years.

Timeline

API development for a typical SaaS project with 30–50 endpoints: from 3 to 8 weeks depending on business logic complexity and number of external integrations. Migration of an existing REST API to GraphQL: from 2 to 6 weeks. Adding a WebSocket layer to an existing backend: from 1 to 3 weeks. Cost is calculated individually after an audit. Get a consultation — contact us to discuss your project.