The author doesn't need to assume molting happens exactly once a year. As the visual illustrates, the method works at any consistent rate. If, for example, rattlesnakes molt twice a year, you'd divide the section count by two to get the snake's age. If they molt three times a year, you'd divide by three. The key assumption is that molting is predictable, not that it happens at the specific frequency of 1 per year.

The overall appearance of different rattles doesn't matter. The author's method is about counting sections within a single rattle, not comparing rattles across species. Whether the rattles of different species look the same or different has no bearing on whether you can infer a particular snake's age from its own section count.

The frequency of molting doesn’t matter, as long as that frequency is predictable. Maybe rattlesnakes molt once a month throughout their entire lives. We could still infer a snake’s age by counting the number of sections in its rattle.

The author's conclusion is a hypothetical: if rattles weren't so brittle, then we could use them to infer age. Since the conclusion already removes brittleness from consideration, the author doesn't need to assume anything about how brittleness relates to age. Whatever is true about brittleness in the real world doesn't affect what would be true in the hypothetical world where rattles don't break.

If this weren’t true, it would mean that at least one other factor besides age can influence how many sections a rattle has. And that would mean we can’t infer a snake’s age solely from the number of rattle sections. We’d also have to know how food availability has affected that number. If food scarcity could speed up or slow down molting, then two snakes of the same age could have different section counts depending on how well-fed they've been. That's exactly the "unpredictable" scenario from the visual: you'd see a section count and have no way to know whether it reflects age alone or age plus dietary history.