How to Fix Terrible API Documentation with EchoAPI

⚠️ WARNING: This is a “How to Destroy Your API Docs and Ruin Your Team’s Sanity” guide.
If you actually want readable, maintainable API documentation, do NOT follow these steps!

Let’s face it: API documentation is often the worst part of software development. Everyone needs it, no one wants to write it, and somehow it always ends up a steaming pile of frustration. Want to know how to make that nightmare even worse? Just follow these simple steps below and watch your dev team implode.

Step 1: Reject All Standards — Stick to “Word + Excel” Like It’s 1999

Because who wants structured JSON schema or Swagger files when you can have… a chaotic collage of Excel screenshots pasted into a Word document?

Here’s the masterpiece I once encountered:

• Interface parameters dumped as endless Excel rows with no explanation
• Wrong parameter names everywhere
• Zero versioning or changelog
• Auto-generated docs? Hahaha, nope

Result? Front-end developers stare at blurry screenshots trying to decipher the magic spell that makes the API work. Spoiler alert: It doesn’t.

“What’s the type of this field?” — “Look at the screenshot, dude.”
“But it’s different from the last version!” — “That’s probably a different screenshot.”
Front-end devs: pulling out their hair
QA testers: crying softly

Step 2: GET Is The King — Use GET for Everything, Including Mutations

Forget RESTful principles. Who cares if GET means “retrieve data”? Just shove all your create, update, and delete operations into GET requests. The more you do this, the more mystified everyone will be.

Example:

GET /updateUserName
Content-Type: application/json

{
  "userId": "123",
  "newName": "Jane Doe"
}

Why is this bad? Because:

• Browsers and proxies cache GET responses assuming they’re safe and side-effect free
• GET requests normally don’t have bodies, so most clients don’t even send the payload correctly
• Your front-end now can’t tell if they’re “reading” or “writing” data

Debugging session highlights:

“Why doesn’t the data update?” — “Because the browser cached the GET response, silly!”
“Why do our logs show no POST requests?” — “Because we never used POST.”
“Can we trust the cache headers?” — “Trust? What’s that?”

Step 3: Naming Endpoints Like a Puzzle Only Indiana Jones Could Solve

Naming conventions? Consistency? Nah.

Here’s a random sample from a client project:

• /getUserList
• /userlist
• /allUsers
• /fetch_users
• /getUsreList (oh, a classic typo!)

Everyone’s left guessing which one is “correct,” if any.

A typical chat log:

Alice: “I used /getUserList but got an empty array.”
Bob: “Try /allUsers, it worked for me.”
Alice: “Docs say /userlist. Are you sure you’re looking at the right version?”
Bob: “We don’t even know what the ‘right version’ is.”

Step 4: Dump All Parameters into Request Body and Forget About Query Strings or Paths

You want to paginate through tickets? Great! Just send all pagination and filtering parameters inside the POST body, even if the request is logically a GET operation.

POST /getTickets
Content-Type: application/json

{
  "page": 1,
  "pageSize": 50,
  "status": "open"
}

Why is this a tragedy?

• You can’t test pagination via browser URL bar — gotta craft full JSON bodies every time
• Caching proxies can’t cache anything based on URL, so caching becomes useless
• Server logs are now a black box — no clear URL query parameters to debug

Step 5: Always Return HTTP 200 OK, Even for Errors — Hide Failure Inside The Body

Who needs HTTP status codes anyway? Just always return 200 and embed error info in the JSON payload.

{
  "code": 400,
  "message": "Invalid parameters"
}

Now the front-end dev has to write custom logic:

fetch(url)
  .then(res => res.json())
  .then(data => {
    if (data.code !== 200) {
      alert(`Oops: ${data.message}`);
    }
  });

Why this sucks?

• API gateways, monitoring tools, and HTTP clients expect error HTTP codes for failures, but get none
• Makes debugging and automation a nightmare
• Forces every consumer to implement custom error handling

Step 6: Response Format Roulette — JSON, CSV, XML, Oh My!

Why choose one response format when you can confuse everyone with multiple?

• Some endpoints return JSON
• Others spit out CSV files with weird formatting
• And a lucky few toss in XML just for nostalgia

Example:

GET /users.csv
HTTP/1.1 200 OK
Content-Type: text/csv

id,name,salary
1,John,$3000
2,Jane,$2800

Now the front-end must:

• Write separate parsers for each format
• Strip currency symbols to convert salaries to numbers
• Handle inconsistent field types (sometimes strings, sometimes integers)

How to Write Terrible API Docs — A Quick Recap

• Write no docs or terrible ones nobody updates
• Abuse HTTP verbs, especially GET
• Mess up naming conventions
• Put all parameters in request bodies, never in URLs
• Always return HTTP 200 with error info hidden inside
• Mix response formats across your API

Congratulations, you’ve created a toxic API experience!

Sick of This? Meet EchoAPI — The API Documentation Savior

Writing good API documentation can feel like pulling teeth. Everyone knows it’s needed, but:

• Front-end: “I can’t start without docs!”
• Back-end: “I’m slammed, docs are last priority.”
• QA: “Where are the error codes? What’s required?”

So everyone suffers.

EchoAPI changes the game by making API docs:

• Visual and interactive
• Automatically updated
• Mockable and testable
• Collaborative across teams

What Is EchoAPI?

A complete API lifecycle platform for dev teams:

Design → Document → Mock → Test → Collaborate

In other words: API docs that don’t suck, and actually help your team ship faster.

Scenario 1: Docs Outdated and Parameters a Hot Mess?

Before: Word docs and screenshots scattered in Slack channels.

With EchoAPI:

✅ Visual drag-and-drop interface for defining headers, query, path, body parameters
✅ Enforce types, required fields, example values, descriptions
✅ Auto-updating docs — no more “who updated the API without telling me?” moments

Scenario 2: Front-end Waiting Forever for Back-end APIs?

Before: Front-end developers twiddling thumbs, blocked.

With EchoAPI:

✅ One-click mock servers based on schema and examples
✅ Front-end can start integration right away, even if back-end isn’t done
✅ Parallel development

Scenario 3: Testing Nightmare Because Error Responses Are a Mess?

Before: No docs on error states, inconsistent formats.

With EchoAPI:

✅ Define multiple response scenarios (200, 400, 401, 500) with examples
✅ Visual JSON schema design with auto-generated mock data
✅ Export test cases and assertions for QA automation

Scenario 4: Confusing Auth and Complex Uploads?

Before: No clarity on auth tokens, multipart uploads, or content types.

With EchoAPI:

✅ Built-in support for OAuth, Bearer tokens, Basic Auth, AWS signing
✅ Handles JSON, form-data, binary uploads — all documented and testable
✅ No more guesswork on “how do I upload this file?”

Scenario 5: Long Parameters Lists and Complex Schemas?

Before: Manually typing docs with typos and missing fields.

With EchoAPI:

✅ Reusable parameter templates
✅ Shared fields across APIs (auth tokens, language, versions)
✅ Markdown support with images and tables for rich docs
✅ Collaboration with permissions and version control

Bonus Features

• Export to HTML, PDF, Markdown, OpenAPI (Swagger)
• Online API testing with history and logs
• Embed docs into company portals or wikis
• Integration with CI/CD pipelines for auto notifications on changes

Why EchoAPI Rocks

Stop wasting time writing bad API docs.
Start using EchoAPI to make your APIs clear, reliable, and easy to consume.

No more:
“How do I call this API?”
“Which fields are mandatory?”
“What error codes does it return?”

Because the docs already tell you everything.