How is the AO3 purity score calculated?

The AO3 purity score formula

Purity score = (total questions − checked questions) ÷ total questions × 100.

Every question is weighted equally, and the final percentage is rounded to the nearest whole number.

Example with 217 questions

If you check 84 of the 217 statements, 133 remain unchecked. 133 ÷ 217 × 100 rounds to 61%, so your AO3 purity score is 61.

(217 - 84) / 217 * 100 = 61.29... -> 61

Why are all questions weighted equally?

The test is designed as a lightweight, shareable snapshot. Reading a rare pair, writing a long WIP and using a custom skin each count as one checked statement. That keeps the calculation transparent, even though people arrive at the same score in different ways.

Can I calculate a score from another version?

Yes. Enter any total question count and checked count in the AO3 purity score calculator. For the complete result, use the 217-question AO3 quiz.

Calculation checklist

• Count the total statements
• Count the statements you checked
• Treat the result as a playful snapshot, not a judgment

Edge cases the calculator handles

The calculator accepts any positive total-question count, which is useful when a fandom group plays a shorter custom version. With zero checked answers, the result is 100%; with every statement checked, it is 0%. Fractions are rounded to the nearest whole percentage so that the shareable result stays readable. The same rule is used by the full AO3 purity test.

For example, a 12-question reader quiz with 3 checked statements gives (12 - 3) / 12 * 100 = 75%. That number says only that three statements matched the player's answers. It cannot tell us which habits mattered, whether the answers were recent, or how deeply someone participates in a fandom.

Because every statement has equal weight, the question mix affects the result. A version focused on tags may produce a different percentage from one focused on writing or tropes. Compare scores only when the question set is the same; use the score meaning guide for context instead of treating ranges as fixed categories.