Turn Word Table API Docs into Ready‑to‑Use Postman Test Cases in Minutes

Core strategy: table extraction → structured fill → AI generation

The article presents a three‑step workflow for turning Word‑based API documentation into Postman test cases.

Step 1 – Quickly extract the Word table (≈5 minutes)

Copy the entire table from Word and paste it into Excel or a plain‑text editor. Adjust the format so each row corresponds to a single API. An example table includes columns for interface name, method, URL, request parameters, and response examples such as:

接口名称   方法   URL               请求参数                响应示例
用户登录   POST   /api/login        username(字符串,必填)   {"code":0,"data":{"token":"xxx"}}
查询订单   GET    /api/orders       orderId(整数,必填)      {"code":0,"data":{订单信息}}

Step 2 – Use a fill‑in template to structure the data (≈2 minutes)

Create a plain‑text template and paste the cleaned table rows into it. The template defines sections for basic information, API list, method, path, request body parameters, and success/error responses.

# 接口测试需求 - 直接复制使用
## 基础信息
- 基础URL: http://api.example.com
- 认证方式: JWT Token

## 接口列表
### 接口1: 用户登录
- **方法**: POST
- **路径**: /api/login
- **请求体参数**:
  - username: 字符串, 必填
  - password: 字符串, 必填
- **成功响应**: {"code":0,"data":{"token":"xxx"}}
- **错误响应**: {"code":1001,"msg":"密码错误"}

Step 3 – Generate Postman test cases with a dedicated AI prompt (≈3 minutes)

Copy the following prompt, replace the placeholder with the structured content from step 2, and run it in an AI model. The prompt asks the model to produce a Postman Collection v2.1 JSON with three test cases per API (normal flow, parameter error, boundary test), automatic token handling, Authorization header insertion, status‑code and response‑time assertions, and no explanatory text.

你是一个Postman测试专家。请将以下接口信息转换为完整的Postman Collection v2.1格式的JSON。
要求：
1. 为每个接口创建3个测试用例：正常流程、参数错误、边界测试
2. 登录接口成功后自动保存token为环境变量
3. 需要认证的接口自动添加Authorization头
4. 每个请求都要有状态码断言和响应时间检查
5. 输出纯净JSON，不要解释
接口信息：【将第二步中整理好的内容完全粘贴在这里】

The AI returns a JSON snippet similar to the following (truncated for brevity):

{
  "info": {"name": "API测试集合"},
  "item": [
    {
      "name": "用户注册-正常流程",
      "request": {
        "method": "POST",
        "header": [{"key": "Content-Type", "value": "application/json"}],
        "body": {"mode": "raw", "raw": "{
\"mobile\": \"13800138000\",
\"password\": \"123456\"}
"},
        "url": {"raw": "http://api.myshop.com/api/register"}
      },
      "event": [{
        "listen": "test",
        "script": {"exec": [
          "pm.test(\"状态码为200\", function() { pm.response.to.have.status(200); });",
          "pm.test(\"包含userId\", function() { var json = pm.response.json(); pm.expect(json.code).to.equal(0); pm.expect(json.data).to.have.property('userId'); });"
        ]}}
      ]
    }
    // … other test cases …
  ]
}

Advanced tip – Handling messy tables

If the original Word table is poorly formatted, ask the AI to clean it first using a prompt like:

请帮我整理以下混乱的接口文档表格，提取出清晰的接口信息：
[粘贴您的Word表格内容]
请按这个格式输出：
接口名称: [名称]
方法: [GET/POST等]
URL: [路径]
参数: [每个参数一行，格式：名称(类型,是否必填)]
响应: 成功-[示例];失败-[示例]

Practical checklist

✅ Copy Word table to a text editor

✅ Adjust formatting for readability

✅ Use the fill‑in template to structure data

✅ Copy the AI prompt and generate Postman JSON

✅ Import the JSON into Postman and fine‑tune parameters

Possible fine‑tuning after generation

Replace example data with real test data

Adjust timeout and other request settings

Correct assertions to match actual API behavior

The key is to prioritize speed over perfect parsing; a usable test suite covering main scenarios can be produced in about ten minutes, then refined within Postman.