Wild City (v2026.04.29)

An urban election becomes a living strategy puzzle where wildlife, greenery, and political muscle all compete for space. Wild City combines roguelike deckbuilding with hex-based tile placement, asking you to assemble a functioning ecosystem while pushing a long-shot mayoral campaign through a rough, energetic metropolis. The mood is colorful but scrappy: every new supporter, animal, plant, and civic element can become part of a thriving machine or a badly timed complication. Rather than simply dealing damage through cards, you build an interconnected board whose layout matters as much as the deck in your hand.

Runs revolve around drafting cards, placing them across an expanding hexagonal grid, and exploiting their shared keywords to create valuable chains of effects. A species may contribute resources, strengthen adjacent tiles, trigger another card type, or fill a political role, so smart positioning continually changes the value of your options. Campaign encounters include protests, rivals, and boss-style challenges that alter the rules and force you to rethink a strategy that worked in earlier fights. Victory leads to additional cards and tougher modes, giving repeated attempts a sense of long-term growth instead of resetting everything to square one.

Its most interesting idea is the overlap between ecological design and electoral competition. With more than 400 cards in the pool, Wild City gives players plenty of room to test strange combinations, whether they favor carefully planned board engines or opportunistic decks built around whatever a run provides. The keyword-focused design helps cards stay flexible, reducing the feeling that a draw is completely useless while still demanding careful sequencing and spatial planning. Fans of Slay the Spire’s run-based drafting and the escalating chaos associated with Vampire Survivors should find familiar appeal here, though the hex grid makes it more deliberate than either. It suits deckbuilding veterans who enjoy optimizing synergies, while newcomers with patience for layered rules can learn through experimentation.