EcoGnomix (v1.0)

A cheerful gnome settlement sits above a dangerous, ever-changing maze of magical caverns, and its survival depends on what its miners can bring back from below. EcoGnomix blends the long-term planning of a compact city builder with the pressure and unpredictability of a roguelite expedition. Its colorful presentation and oddball plants make the underground inviting at first glance, but every descent becomes a calculated risk as hostile creatures, dwindling supplies, and cave instability close in. The result is a relaxed-looking strategy game with a surprisingly tense decision-making core.

Each run begins by choosing a crew of specialized gnomes, then placing them across a cave map to harvest materials, battle threats, and secure useful terrain. Turns revolve around positioning: workers perform their tasks, the team is reorganized, and players decide whether to push deeper or leave with what they have collected. Remaining underground increases the potential reward, but bats consume supplies and the cave grows less stable, so greed can quickly turn a profitable trip into a desperate retreat. Resources still return to the village even after an unsuccessful run, creating a forgiving progression loop that lets players improve rather than lose everything. Back above ground, gathered materials unlock structures, production chains, new recruits, permanent improvements, and abilities that make future expeditions more flexible.

What makes EcoGnomix work is the way its two halves feed directly into one another: village expansion opens new tactical options, while tactical runs provide the economy needed to keep building. Gnome classes, swappable team compositions, hidden character talents, and run-specific upgrades encourage experimentation instead of relying on one perfect strategy. Its small-scale settlement management recalls the satisfying resource flow of games like Against the Storm, while the expedition layer has the positional, turn-based tension associated with roguelite tactics games. Players who enjoy optimizing production, adapting to random maps, and making hard calls about when to quit will find plenty to dig into, while newcomers benefit from its low-punishment approach to failed runs.