Godisnje is a turn-based strategy card game where players match Month cards with trait-based sets across multiple boards, manipulate seasonal effects, and outscore AI opponents through in-depth tactical play.

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此遊戲尚未在 Steam 上發售

預計發行日期: 2026 年 3 月

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關於此遊戲

Godisnje is a structured turn-based strategy card game built around multi-board play and the logic of the seasons.

Turn requires players to match Month cards with their corresponding descriptive card. Players plan ahead to manipulate seasonal effects, and construct scoring opportunities across multiple active boards. As additional boards unlock, positional decisions compound and sequencing becomes critical.

There are no reflex mechanics. No speed advantage. Success depends on planning, pattern recognition, and calculated trade-offs.

What begins as a straightforward matching system evolves into layered decision-making across interconnected boards. Seasonal shifts alter optimal play paths, trade mechanics introduce calculated risk, and every scoring opportunity must be evaluated within the broader board state.

Godisnje rewards players who enjoy learning systems, refining strategy, and mastering structured competitive play.

Key Features

  • Multi-Board Strategy — Manage and evaluate multiple active boards where decisions in one space affect opportunities in another.

  • Seasonal Logic System — Month cards and shifting seasonal effects alter optimal play paths each match.

  • Layered Tactical Depth — Matching, sequencing, and trade interactions create compounding strategic decisions.

  • Structured Turn Flow — No timers or reflex mechanics. Every turn rewards deliberate analysis.

  • Tournament Progression — Compete through bracketed play and refine strategy over extended sessions.

AI 生成內容聲明

開發者針對他們的遊戲使用 AI 生成內容方式的說明如下:

I was the archaic and fragmented DNA in the amber bound insect. AI was the frog DNA.

Original Card Game: All card art is original, hand painted on canvas and physically printed on real cards (5,000 in total). The face images are scans of those pained canvas prints/ cards. AI was used to generate the card's backs and some of the playing surfaces/backgrounds.

Coding: While I on and off experience in JavaScript since 2002, AI was used to help generate and debug portions of the code. I especially used AI when predicting potential conflicts and integration problems (especially Steam integration) before implementing new code. I found it very helpful when changing long sets of repetitive blocks of code. The volume of human error that was cut down was tremendous.

Localization: Localization will be finalized in Beta. Initial translations were done with AI. Corrections and finalization will be done after input from the community (new game, some new terms).

Music: We are Streamer first. Streamer need background music that won't affect their monetization. From the beginning, music that was all original, was critical to me. I wanted Streamers to have no worries when letting our background music play for hours. Musicians want astronomical payments and deals that will leave me perpetually paying them. I generated all of our music in Suno and own it all. I plan on releasing more, in two hour blocks, that will be available as free DLC's.

All AI I used was after human talent quoted cost ineffective numbers or outright turned me down. This is a simple card game. A vehicle for a game and art I have made. I set out to make an affordable, sturdy, reliable, user focused game. AI helped me make the best product I could.

系統需求

    最低配備:
    • 需要 64 位元的處理器及作業系統
    • 作業系統: Windows 10 (64-bit)
    • 處理器: Intel Core i3 / AMD equivalent
    • 記憶體: 4 GB 記憶體
    • 顯示卡: DirectX 11 compatible GPU / integrated graphics
    • DirectX: 版本:11
    • 儲存空間: 1 GB 可用空間
    • 音效卡: Any
    • VR 支援: N/A
    • 備註: Mouse Required
    建議配備:
    • 需要 64 位元的處理器及作業系統
    • 作業系統: Windows 10/11 (64-bit)
    • 處理器: Intel Core i5 / AMD equivalent
    • 記憶體: 8 GB 記憶體
    • 顯示卡: DirectX 11 compatible GPU
    • DirectX: 版本:11
    • 儲存空間: 2 GB 可用空間
    • 音效卡: Any
    • VR 支援: N/A
    • 備註: SSD Recommended
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