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Documentation Index

Fetch the complete documentation index at: https://docs.requestly.com/llms.txt

Use this file to discover all available pages before exploring further.

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Introduction

“What if I could test all my APIs at once, like a chain reaction, without switching tabs or hitting Send repeatedly?” If you’ve ever tested APIs manually, you know the pain:
  1. Send a login request
  2. Copy the token
  3. Paste it into the next request
  4. Then test one endpoint after another
It’s repetitive and time-consuming, especially when you’re testing a whole workflow like Login → Create User → Fetch User → Delete User. That’s where Requestly Interceptor’s Collection Runner shines. In this guide, I’ll walk you through how I explored the Collection Runner feature, how it simplifies API automation, and how you can start using it right away, even if you’re completely new to automated API testing.

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Prerequisites

Before you begin, make sure you have:
  • Requestly Interceptor app installed (desktop or browser extension)
  • Basic understanding of APIs and HTTP methods
  • Access to an API for testing (we’ll use JSONPlaceholder in this tutorial)
  • Familiarity with JavaScript (helpful but not required)

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What Is the Collection Runner?

The Collection Runner in Requestly Interceptor lets you execute multiple saved API requests sequentially, in a single automated flow. Imagine chaining requests together: Login → Create User → Fetch User → Delete User You can run them one after another, apply test scripts, reuse variables, and even debug results visually, all without writing a single line of backend automation code.

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Step-by-Step Guide

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Step 1: Setting Up Your First Collection

I started by opening the Requestly Interceptor app → going to APIs → New → and clicking Collection. You can also import a pre-existing API collection by clicking the Import button. I named mine User Management APIs, because I wanted to simulate a typical CRUD workflow using JSONPlaceholder’s /users endpoint. Inside my collection, I added the following 4 requests:
  1. GET /users, Fetch all users
  2. GET /users/1, Get a specific user
  3. POST /users, Create a new user
  4. DELETE /users/1, Delete a user (mock)
Setting Up Each request can include pre-request scripts, test scripts, and variables.

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Step 2: Using Pre-Request & Post-Response Scripts

You can use JavaScript to make your requests dynamic. Let’s test a real example using JSONPlaceholder (a free mock API).

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Pre-Request Script

const randomName = "User_" + (+new Date()).toString(36).slice(-5);
const randomEmail = randomName + "@example.com";
const randomPhone = Math.floor(Math.random() * 9000000000) + 1000000000;

rq.environment.set("name", randomName);
rq.environment.set("email", randomEmail);
rq.environment.set("phone_number", randomPhone);

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Post-Request Script

rq.test("Status code is 201", () => {
  rq.response.to.have.status(201);
});

rq.test("Request method is POST", () => {
  rq.expect(rq.request.method).to.equal("POST");
});

rq.test("Response has valid JSON body", () => {
  rq.response.to.have.jsonBody();
});

rq.test("Response body is JSON object", () => {
  const parsed = JSON.parse(rq.response.body);
  rq.expect(parsed).to.be.an("object").and.not.to.be.an("array");
});
Scripts These tests automatically validate the response when your collection runs. So now, after every run, I could instantly see if a request passed or failed, without manually checking the response body.

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Step 3: Running All Your Requests at Once

Once my collection was ready, I clicked the little ▶ Run icon beside it (honestly, the most satisfying button). This opened the Collection Runner, where I could configure: Collection Runner
  • Iterations: How many times to repeat the run
  • Delay: How long to wait between requests (useful if your server needs a breather)
  • Select data file: Optional, useful if you want to pass different input sets for multiple runs

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Step 4: Reordering or Skipping Requests

Here’s something I really liked, before running, I could reorder the requests or uncheck the ones I didn’t want to include. I dragged my “Delete User” request to the end (because, obviously, who deletes before testing?). That small UX detail made the workflow feel super flexible. Reordering After setting everything up, I hit Run Collection, and boom! Requestly Interceptor started running all my requests in order, one after another, while I just watched it go. Collection-Running

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Step 5: Making It Dynamic with Variables & Environments

Hardcoding URLs and values works for one-time tests, but it quickly becomes a hassle when switching between environments like dev, staging, or prod. That’s where variables come in. Instead of writing full URLs, you can use placeholders like: 
{{base_url}}/users
Then, in your Variables tab, define your base URL: Variables This way, you can easily switch between different environments without modifying each request individually.

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Step 6: The Results Dashboard

After running my JSONPlaceholder collection, Requestly Interceptor displayed a Run Summary that instantly made everything click. It didn’t just show “pass” or “fail”, it broke everything down clearly:
  • ✅ Number of passed tests
  • ❌ Number of failed tests
  • ⏱ Total execution time
  • 💬 Average response time per request
Each request had its own section showing:
  • HTTP method and endpoint (like GET /users, POST /users, DELETE /users)
  • Response status (e.g., 200 OK, 201 Created)
  • Test outcomes for each assertion you wrote
  • Response body preview
Final Tests Another really neat feature is the History tab in the top right corner. It automatically saves each run, so you can:
  • Revisit old runs anytime
  • Compare results between test iterations
  • Track when something started failing
That means you can build up a timeline of test runs, perfect for debugging or regression tracking later on.

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What’s Actually Happening Behind the Scenes

Here’s a simple breakdown of what goes on under the hood when you click Run:
  1. Variables like {{base_url}} get replaced
  2. Pre-request scripts (if any) execute
  3. The actual HTTP request is made
  4. Post-response tests run automatically
  5. Everything is logged in the Test results for you to analyze
It’s basically like having a mini continuous testing pipeline, right inside Requestly Interceptor, but without the complexity of CI/CD setup.

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Examples

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Real-World Use Cases

After just one run, I could already see how useful this tool is for developers and testers alike: Regression Testing: Run your full suite of APIs before every deployment. Chained Workflow Testing: Simulate real user journeys (e.g., Create → Fetch → Update → Delete). Environment Switching: Use variables to test across dev, staging, and prod instantly. QA Validation: Automate repeated test cases with zero manual effort.

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Conclusion

The Collection Runner in Requestly Interceptor turns API testing from a manual chore into an effortless, automated workflow. Instead of juggling multiple tabs and copying data around, you can just run one collection and validate everything at once. Key Takeaways:
  • Collections let you organize and run multiple API requests in sequence
  • Pre and post-request scripts enable dynamic testing and validation
  • Variables make it easy to switch between environments
  • The results dashboard provides instant visibility into test outcomes
  • History tracking helps with debugging and regression analysis
It’s like giving your APIs an autopilot mode. Try it once, and you’ll never want to test manually again.

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Additional Resources