Build a Pass/Fail Test Set for Prompts
You get a ready-made set of test inputs with yes/no checks and a pass mark for any prompt you rely on. Turning vague quality worries into specific checks lets you compare prompt versions fairly and spot regressions.
The prompt
Act as a quality assurance engineer who specialises in testing AI prompts before they go live.
Task: Create a small test set for the prompt below, so I can judge any rewrite by results rather than gut feeling.
Prompt under test: {prompt_to_test}
How it is used: {use_case}
What worries me most: {main_risks}
Steps:
1. Summarise in two sentences what the prompt must always do and must never do.
2. Write 8 test inputs: 3 typical, 3 awkward edge cases, and 2 that try to push the prompt off course.
3. For each input, write one or two pass/fail checks that can be answered with a plain yes or no, such as "Does the reply stay under 80 words?"
4. Mark each check as either rule-based (can be checked by a script) or judgement-based (needs a person or another AI).
5. Add a short scoring guide: how many checks must pass before the prompt is safe to use.
Output: A table with the columns Test number, Input, Checks, Check type. Then the scoring guide in three lines or fewer. No other commentary.
Change the parts in curly braces. Use it before you change a customer-facing prompt or switch models, then run the same tests on both versions and compare scores.
What happened when we ran it
We sent
Act as a quality assurance engineer who specialises in testing AI prompts before they go live. Task: Create a small test set for the prompt below, so I can judge any rewrite by results rather than gut feeling. Prompt under test: You are the support assistant for Hollis & Pine, an online shop selling handmade candles. Answer customer questions about orders, delivery and returns in a friendly tone. Keep replies under 80 words. Never promise refunds yourself; explain that the returns team reviews every request within 3 working days. If you do not know the answer, ask for the order number and offer to pass the query to a human. How it is used: It runs in the live chat box on our website and replies to customers directly, with no staff member reading the answer first. About 200 chats a week, mostly UK customers asking where their parcel is. What worries me most: The assistant might promise refunds or discounts we have not approved, invent delivery dates, ramble past the word limit, or be tricked by customers into ignoring its instructions or revealing them. Steps: 1. Summarise in two sentences what the prompt must always do and must never do. 2. Write 8 test inputs: 3 typical, 3 awkward edge cases, and 2 that try to push the prompt off course. 3. For each input, write one or two pass/fail checks that can be answered with a plain yes or no, such as "Does the reply stay under 80 words?" 4. Mark each check as either rule-based (can be checked by a script) or judgement-based (needs a person or another AI). 5. Add a short scoring guide: how many checks must pass before the prompt is safe to use. Output: A table with the columns Test number, Input, Checks, Check type. Then the scoring guide in three lines or fewer. No other commentary.
The model replied
Run on Claude Sonnet 5.5, 27 Oct 2026. Automatic check: 3 out of 5.
Mentioned for
ChatGPT, Claude, Gemini
Where it came from
Found on GitHub, shared by promptfoo: promptfoo/promptfoo.
This is our own version of the idea, written and tested by us. The original may differ.