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Be Nosy (Marathon)

Be Nosy (Marathon)

A Roblox experience owned by Tesseract Studiоs.

Clicker & idleENclickermarathonsequel

Description (written by the developer; not a statement by this register)

You wasted your time clicking all those buttons, finally getting your salvation after finding both of the correct ones. Yet you still return, greedy for more. Inspired by Be Saga (https://www.roblox.com/games/17798700673) by @SlashedWasTaken Every first couple victors of the badges is cube and jorm, every actual first victor is listed in the descriptions of the badges.

Last updated by the developer 25 May 2026, 12:57 UTC.

0
playing (measured 14 Aug 2026, 23:20 UTC)
696
lifetime visits
71%
liked (5 👍 / 2 👎)
12
favourites (17.2 per 1k visits)
16 March 2022
created (per Roblox)

Play on Roblox →

Live players over time

Growth

Growth history is still building. We hold one measurement for this entry. A trend needs at least two, taken days apart — so this will fill in on its own rather than being estimated. We do not publish numbers we have not measured.

Measurement log — every players count we have recorded
Measured (UTC)PlayersChange
14 Aug 2026, 23:200first reading

Concurrent players at each of our measurements (insert-on-change).

Monetization — game passes

beat the game
999,999,999 R$

Game passes for sale and their prices, measured from the Roblox passes API. Developer products bought inside the game aren’t publicly listable.

Badge funnel

Be Here (Marathon) · welcome27 · 0.00% win
Begin. · welcome19 · 0.00% win
Be Nosier (Marathon) · other4 · 0.00% win
Be Nosy (Marathon) · other3 · 0.00% win
The Third Find · collection3 · 0.00% win
The First Find · collection3 · 0.00% win
The Second Find · collection3 · 0.00% win
The Fourth Find · collection3 · 0.00% win
Be Truest Completionist1 · 0.00% win
The Final Find.1 · 0.00% win

How many players have ever earned each badge — a proxy for how far players get before they stop. Steep drop-offs mark where a game loses people. Win rate is the past-day share of players who earned it; categories are assigned by a language model from each badge’s own name and description.