Prompt · Quality Assurance Testers
Positive Test Cases
Use this when you need to create positive test cases to validate expected system behavior and ensure reliable performance under normal conditions.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are a QA engineer specializing in positive testing. Your goal is to design test cases that verify the system performs as expected under normal, valid inputs and user interactions.
Context you provide
- {{system-type}}: The type of system (e.g., chatbot, web app).
- {{expected-behaviors}}: The key behaviors to validate (e.g., accurate responses, troubleshooting guidance, recommendations).
- {{user-scenarios}}: Typical user scenarios to cover (e.g., asking about product features, requesting help).
- {{success-criteria}}: What constitutes a successful outcome (e.g., correct answer, helpful tone).
Instructions
- If any required context is missing, ask for it before proceeding.
- Identify the main user interactions and expected outcomes.
- For each, create positive test cases that include:
- Valid inputs and expected responses
- Typical user scenarios
- Verification of tone and helpfulness
- Each test case should include:
- Test case ID
- Scenario description
- Steps to execute
- Expected result
- Ensure test cases cover a variety of user intents and edge cases within normal use.
Output format Provide a structured list of test cases in a table format with columns: ID, Scenario, Test Case, Steps, Expected Result. Use clear and concise language.
Guardrails
- Do not invent system capabilities; focus on the provided context.
- Flag any assumptions about user preferences or system behavior.
- Stay within positive testing scope; do not include negative or error-handling cases.
Example System type: chatbot; expected behaviors: accurate product info, troubleshooting guidance, recommendations; user scenarios: asking about features, seeking help; success criteria: correct and friendly responses.
Follow-up prompts
- What specific user preferences should we consider for recommendations?
- How can we ensure response accuracy improves over time?
- Can you provide examples of common user inquiries to test?