Creative fatigue is one of those problems teams usually notice too late. The ad is still live. Spend is still flowing. Nobody wants to admit the creative has gone stale because the dashboard does not scream about it yet. Then performance gets weird, the team starts talking about "market conditions," and suddenly everyone agrees the ad has probably been tired for weeks. The frustrating part is that you often can see fatigue clues earlier, even from public data. Not perfect proof. Not ROAS. Not internal frequency. But enough signal to make better decisions. That is what this post is about: how to use public ad library snapshots to detect creative fatigue, how I score it, what the signal can and cannot tell you, and how to build the workflow in both JavaScript and Python. What Creative Fatigue Looks Like in Public Data If you do not have access to the ad account, you cannot see the internal performance metrics that paid teams obsess over.…