--- title: Writing API Reference Docs That Developers Actually Read description: "Consistent structure, examples for every endpoint, thorough error documentation, and fast search. The principles behind API reference docs that get read, not skimmed and abandoned." canonical: https://nowah.xyz/blog/writing-api-reference-docs-developers-read lastModified: "2026-08-07T08:12:53.772Z" --- # Writing API Reference Docs That Developers Actually Read Consistent structure, examples for every endpoint, thorough error documentation, and fast search. The principles behind API reference docs that get read, not skimmed and abandoned. I have seen API references with 200 endpoints and zero examples. Every endpoint documented with parameter types and descriptions, technically complete, and completely useless for a developer trying to figure out how to actually call the thing. The [problem with](/blog/problem-with-travel-loyalty-programs) most API reference documentation is not that it is wrong. It is that it is written for the API, not for the developer using the API. There is a difference. Documenting what the API accepts and returns is necessary. Showing a developer how to use it effectively is what makes reference docs useful. ## The template that works ![Illustration for this section](https://pics.nowah.xyz/website-media/developer-experience-048-img-1-template.webp) Every endpoint in our reference follows the same structure. Consistency is the first kindness you can extend to a developer reading your docs, because it means they do not have to re-learn the layout on every page. **Description.** Two to three sentences explaining what this endpoint does and when you would use it. Not a technical specification. A human-readable explanation. "Search for available flights between two airports on specific dates. Returns ranked results based on price, duration, and your preference settings." **Authentication.** Which authentication method this endpoint requires and any special scoping requirements. "Requires an API key with search permissions." **Parameters.** A table with the parameter name, type, required/optional flag, and a description that includes constraints and examples. Not just "departureDate: string" but "departureDate: string (ISO 8601 date, e.g., 2026-06-15). Must be today or later." **Request example.** A complete, working request with realistic data\. Not \`foo\` and \`bar\`\. Real airport codes\. Real dates\. Real passenger counts\. This example is tested in CI and confirmed working\. **Response example.** A complete response showing the full structure, including nested objects. Truncated where necessary for very large responses, but with a clear indication of what was cut and a link to the full schema. **Errors.** A table listing every error code this endpoint can return, with the error code, HTTP status, and a one-line description. Each error code links to its dedicated documentation page. This template means a developer landing on any endpoint page can find what they need in the same position every time. Parameters are always in the same spot. Examples are always in the same spot. Errors are always in the same spot. ## Example quality The examples in your reference docs are the most-read parts of those docs. Developers scan past descriptions and parameter tables. They stop at examples because examples show them what to actually type. Our examples follow strict quality rules. Realistic data only. No placeholder strings. The example flight search uses JFK to CDG, not "ABC" to "XYZ." The example hotel search uses a real city with a real date range. When a developer sees the example, it should look like something they would actually send. Every example is runnable. Copy it, paste it into a configured SDK client or cURL, and it works. We enforce this through CI testing. If an example stops working because the API changed, the build fails, and the example gets updated before the API change ships. Both success and error cases get examples. A developer does not just need to see what a successful response looks like. They need to see what a 400 validation error looks like, what an expired offer error looks like, and what a rate limit response looks like. Error examples in the reference docs prevent a category of support tickets entirely. ## Error coverage ![Supporting diagram](https://pics.nowah.xyz/website-media/developer-experience-048-img-2-feedback.webp) Every endpoint lists every possible error code it can return. Not just the common ones. All of them. This is tedious to maintain and invaluable to developers\. When a developer gets an \`OFFER\_EXPIRED\` error and searches the reference docs, they should find it listed on the booking endpoint page with a description and a link to the full [error documentation](/blog/error-documentation-not-writing) page that explains common causes and fixes. Error documentation is the third most-visited section of our docs, after the quickstart and the API reference itself. Developers hit errors constantly during integration, and the quality of error documentation directly determines whether they solve the problem themselves or file a [support ticket](/blog/every-support-ticket-dx-bug). ## Search that actually finds answers Developer docs need fast, fuzzy search. A developer looking for "flight search pagination" should find the right page whether they type "pagination flights," "cursor next page," or "search results paging." We structure our headings and content for searchability. Parameter names appear in headings when they are commonly searched: "departureDate parameter" rather than just the generic heading "Parameters." Code-searchable text means a developer who copies an error code from their terminal and pastes it into the docs search bar finds the relevant page immediately. Search results show context snippets so the developer can evaluate which result is most relevant without clicking through each one. For API reference pages, the snippet includes the endpoint method and path alongside the content match. ## Feedback collection Every reference page has a "Was this helpful?" widget. Two buttons: thumbs up and thumbs down. If thumbs down, an optional text field lets the developer explain what was missing or confusing. This feedback feeds directly into our [developer experience](/blog/developer-experience-customer-experience) improvement backlog. We review it monthly, and the most-reported issues become documentation tasks. We also track page view analytics. High traffic on a specific endpoint's reference page might indicate that the endpoint is popular. Or it might indicate that the endpoint is confusing and developers keep returning to re-read the docs. Cross-referencing page views with feedback data distinguishes between the two. Most-viewed doc pages deserve the most attention. If hundreds of developers visit the flight search reference page every week, that page needs to be impeccable. If the webhook configuration page gets five views a month, it matters less. ## Generating from specification while keeping it human Our reference docs are auto\-generated from our OpenAPI specification\. This ensures that parameter types, response schemas, and endpoint paths are always accurate\. You cannot have a doc page that says the endpoint accepts \`passengers\` when the spec says \`travellers\` because the generation catches the mismatch\. But auto-generation alone produces dry, mechanical documentation. The descriptions read like schema definitions, not explanations. The examples are minimal or absent. We solve this by overlaying hand-written content on top of the generated skeleton. The endpoint structure, parameter types, and response schemas come from the spec. The descriptions, examples, usage notes, and error explanations are written by humans. The overlay is maintained separately and merged during build. When the spec changes, the generated skeleton updates automatically. The human-written overlay stays in place unless the change requires updating it, in which case our CI doc tests flag it. This hybrid approach gives us accuracy from automation and readability from human writing. Neither alone would be enough. Together, they produce reference docs that developers actually read and use. --- Nowah is an AI travel agent that searches and books real flights and hotels through conversation — no filters, no thirty open tabs. [Plan your next trip](https://app.nowah.xyz).