Muat turun RanaRangam: Where Chess Pieces Bleed Demo

Tentang Permainan Ini

RanaRangam turns classic chess into a tactical battlefield where every command continues beyond a single turn.

Pieces do not instantly jump to their destination. They move step by step toward the command you give them, allowing multiple pieces to carry out their orders at the same time. Your army keeps advancing, clashing, healing, and threatening the board as every decision unfolds over time.

COMMANDS KEEP MOVING

Plan ahead, control key tiles, and create pressure with pieces that continue following their assigned commands. A single move can become a future attack, a block, or a setup for something bigger.

POSITIONING CREATES SUPPORT

Pieces are not only useful for attacking. With the right positioning, they can support friendly units on valid tiles to restore health, making formation and defense just as important as offense.

CHECKS NOW BLEED THE KING

There is no instant checkmate. The King must be defeated. Checks still matter, but now they deal damage to the King, creating constant pressure and forcing you to respect dangerous positions.

ULTIMATES CAN TURN THE BATTLE

Ultimate abilities are tied to each piece’s valid tiles. If enemies are standing in those tiles, the ultimate can punish them, making positioning and timing just as important as the ability itself.

Built on familiar chess foundations, RanaRangam turns every match into a living tactical fight where movement, combat, healing, pressure, and timing decide who survives.

Pendedahan Kandungan Dihasilkan AI

Pembangun menerangkan cara permainan mereka menggunakan Kandungan Dihasilkan AI seperti berikut:

As a solo indie developer working with a limited art budget, I have used generative AI tools for some visual assets, primarily UI artwork.

The gameplay systems, mechanics, programming, balancing, and overall game design are created and implemented by me.

My long-term goal is to continue improving the game’s artwork and, as the game grows, work with professional artists to replace and further refine AI-assisted visual assets.