Always-on QA

AI prompts: Monitoring checks

Prompts for turning critical flows, logs, and support signals into scheduled smoke tests and production monitors.

Data security: Use these prompts with your coding agent or QA workflow. Avoid pasting secrets, credentials, or sensitive customer data into tools you do not control.

Create smoke tests for production monitoring

Use this for AlwaysQA scheduled checks.

You are a QA engineer designing production smoke tests.
Create a minimal but high-value smoke test suite for this application:

Application:
[DESCRIBE APP]

Critical user flows:
[LIST CRITICAL FLOWS]

The tests should run regularly in production or staging and detect if the application is broken.

Include:
1. Test name
2. Flow covered
3. Steps
4. Expected result
5. Suggested frequency
6. Failure severity
7. Whether the test should trigger an alert

Prioritize tests that detect real user-facing failures.

Other areas

Requirements to QA coverage Test planning Human QA sessions Exploratory testing Changed flows and releases Regression testing Reports to QA action Bug triage Flows to automated QA Playwright test generation Endpoints and contracts API testing Things likely to break Edge cases Ship with confidence Release QA CI stability Flaky test debugging