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I meant in a general sense that it's better when reporting measurements/estimates of real numbers to report the uncertainty of the estimate alongside the estimate, instead of using some kind of janky rounding procedure to try and communicate that information.

You're absolutely right that if you have a binary random variable like "IMO gold by 2026", then the only thing you can report about its distribution is the probability of each outcome. This only makes it even more unreasonable to try and communicate some kind of "uncertainty" with sig-figs, as the person I was replying to suggested doing!

(To be fair, in many cases you could introduce a latent variable that takes on continuous values and is closely linked to the outcome of the binary variable. Eg: "Chance of solving a random IMO problem for the very best model in 2025". Then that distribution would have both a mean and a variance (and skew, etc), and it could map to a "distribution over probabilities".)