Writing a good prompt makes a big difference when you are using AI to generate test cases. If your prompt is clear, the AI gives you test cases that are accurate and useful. If your prompt is vague, you will likely end up fixing or rewriting most of them.
This article is a guide to writing better prompts. Not perfect ones, just practical and effective ones. You can try them out using the Generator Agent in Test Management by Testsigma, which creates test cases from plain English, Jira tickets, designs, and even videos or screenshots. Let’s look at what makes a prompt actually work.
Table Of Contents
Why Prompt Quality Matters in AI-Generated Testing
When testers write or talk through test cases with teammates, we usually add extra details without even realizing it. We explain the goal, mention what should happen if something fails, and point out unusual cases to consider. All of this adds context, and that context helps others understand what needs to be tested.
AI does not have that kind of intuition. It does not assume or interpret unless you clearly tell it what to look for. If your prompt is too short, vague, or missing key information, the AI will generate test cases that are either too generic or miss important scenarios entirely. This is where human intelligence plays a critical role. AI can automate tasks, but it needs clear guidance. It depends on you to define the boundaries, priorities, and intent behind each feature or scenario. The better your prompt, the better the AI can support you.
For example, if you just say “test the login page,” the AI will not know:
- What inputs are required
- What a successful login looks like
- What should happen when credentials are incorrect
- Whether multi-factor authentication is involved
- Which edge cases should be included
On the other hand, if you describe the feature clearly, state the user’s goal, and include both expected flows and failure conditions, the AI can create test cases that are much more complete and relevant. This is why a well-written prompt saves time. It reduces the need to regenerate or manually fix test cases. The better your input, the more accurate and useful your output will be.
What to Include in a Good Prompt
The best prompts are short, but not shallow. They balance clarity with coverage. Here are five elements that make a prompt effective.
1. Purpose of the Feature
Describe what the feature does and why it exists. This sets the foundation.
Example: “This is a sign-up form for new users to create an account using their email and password.”
2. User Goal OR Outcome
Tell the AI what the user is trying to achieve. This helps shift the focus from system behavior to real scenarios.
Example: “The goal is for the user to register and land on the welcome page once the account is created successfully.”
3. Main Interactions
List the core steps or inputs involved. These are what the test cases will revolve around.
Example: “User enters email, sets password, accepts terms, and clicks submit.”
4. Conditions and Edge Cases
Call out scenarios that should be tested. This includes invalid inputs, optional fields, or alternate flows.
Example: “If the email format is invalid, show an error. Password must be at least 8 characters.”
5. Reference to Source Material
If your feature is tied to a Jira ticket or design, include the link or ticket ID.
Example: “Refer to JIRA-123 for UI specs and validations.”
What Weak Prompts Look like
Just to be clear, a short prompt is not always a bad one. The problem is when it leaves out essential information.
- “Login feature”
This does not tell the AI what success looks like, what inputs are required, or how the system should respond. - “Generate test cases for the cart”
Too broad. Are we talking about adding items, removing items, applying coupons, or checking out?
The more precise you are, the more aligned the test cases will be to the actual business logic.
Prompt Examples: Before and after
Let’s look at two versions of the same idea.
Vague Prompt:
“Generate test cases for login page.”
Improved Prompt:
“Generate test cases for the login screen where users enter email and password. If credentials are valid, they land on the dashboard. If not, show an error message. Refer to JIRA-456 for more details.”
The second one gives the AI context, flow, expected outcome, and a reference. You are not leaving anything to interpretation.
How to Test Your Prompt Quality
You might understand what a good prompt looks like in theory. But the best way to improve is to test it in practice. A prompt that seems clear to you may not give the kind of test cases you expect until you see the output. This is where the Generator Agent in Test Management by Testsigma comes in, which is an AI-powered test management tool that helps you generate test cases from plain English prompts, Jira requirements, Figma designs, UI screenshots, or walkthrough videos. You can test your prompt-writing skills directly in the platform and fine-tune them with real feedback.
Here’s how to try it:
- Go to the Test Cases tab in the Test Management by Testsigma dashboard.
- Create a new folder to keep your generated test cases organized.
- Select the Generator Agent and enter a prompt. For example, if you are testing a search feature, your prompt can look like:
- “Generate test cases for the search functionality of an online bookstore where users can search by title, author, or genre, and apply filters like price and language.”
- “Create test cases for a travel booking platform’s search bar, where users enter destination and dates, apply filters for flight duration and price, and view results in list or grid view.”
- Instead of typing a prompt, you can also upload or link:
- A Jira ticket that describes the feature or requirement
- A Figma design file showing the UI and components
- A screenshot of the screen or search area
- A walkthrough video of the user performing the task
The Generator Agent will process your input and generate relevant test cases. For a search feature, the output might include:
- Verify the default placeholder text in the search bar
- Validate search results on keyword input
- Check the response time for various queries
- Ensure filters are applied correctly after the search
- Confirm “no results” message for irrelevant terms
Review what the agent generates. If the test cases are too generic or missing critical details, go back and look at your prompt. Did you include the user goal? Did you describe expected behavior and edge cases? Adjust your input and run it again.
The process is quick and flexible. You do not need to get it perfect the first time. Prompt writing improves the more you try, and the Generator Agent gives you a hands-on way to sharpen that skill with real, usable output.
Test your prompts, refine your language, and use the results to build better, faster test coverage, powered by your own guidance.
Closing Thoughts
Writing effective prompts is not about following a fixed format. It is about communicating clearly, with just enough context for the AI to do its job well. As test automation becomes more AI-driven, prompt writing is becoming a core testing skill. Treat it with the same care you give your test cases. Start practicing, test them with the Generator Agent, and see the difference for yourself. The quality of your testing can only rise to the quality of your input. Make your prompts count.
