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Get a job at 5 AM 1.4.5

Get a job at 5 AM 1.4.5

A Roblox experience owned by Kubalibree studios.

AdventureENhorrorexplorationendings

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

This is an amazing game inspired by "find the markers" and "eat a snack at 4 am," in which you have to find all the endings to complete the game.

Last updated by the developer 4 Aug 2026, 17:51 UTC.

0
playing (measured 16 Aug 2026, 14:36 UTC)
1,058
lifetime visits
85%
liked (11 👍 / 2 👎)
5
favourites (4.7 per 1k visits)
14 May 2025
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 We do not publish numbers we have not measured.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
16 Aug 2026, 14:360first reading

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

Monetization — game passes

Ultimate speed
399 R$
Sprint
79 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

Took a shower · other57 · 0.00% win
Made dad angry · secret55 · 0.00% win
Smile ending · progression52 · 0.00% win
Made mom mad · other40 · 0.00% win
Time stone · collection36 · 0.00% win
Happy green john · other35 · 0.00% win
Mind stone · collection33 · 0.00% win
Luisgamercool23 ending · secret31 · 0.00% win
Made green john mad · other30 · 0.00% win
Shoplifted · other30 · 0.00% win
Power stone · collection30 · 0.00% win
Leek 1 · collection27 · 0.00% win
Got a job · other25 · 0.00% win
Soul stone · collection25 · 0.00% win
Space stone · collection22 · 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.