Earth in Change

Cinevva's analyzer read this game's design doc and its source, then wrote the brief below. "Make your own" hands it to the game creator as your opening message, so you start from a real spec rather than a one-line idea.

Create a playable first-person educational investigation game titled “EARTH IN CHANGE: WEST KALIMANTAN.” Use a low-poly 3D Three.js-style presentation with a dark teal night/dusk sky, fog, soft directional and hemisphere lighting, chunky faceted vegetation, simple box-built props, and a minimal science-interface HUD in translucent very dark panels with mint/teal borders and text.

The player is a junior Earth-system scientist in a West Kalimantan field site. Start in an outdoor field in first-person view, with WASD movement, mouse look, jumping, and Esc to unlock the mouse. The camera has a centered mint crosshair. The environment is a broad dark olive soil clearing bordered by simple low-poly trees with brown trunks and faceted dark-green crowns, a blue Kapuas River along the right side with segmented brown banks, scattered rocks/log/nature props, and low pale clouds in the distance. Near the left side is a clearly visible wildfire zone: a dark ash patch with several animated-looking orange emissive cone flames and a smoke/aerosol plume made of semi-transparent gray spheres rising above it. Add glowing spherical investigation markers for the wildfire, smoke, vegetation, water, and clouds, plus markers/gates for the Cloud Laboratory and Earth Data Room. The player can investigate a marker by aiming at it from within roughly 8 world units and clicking.

HUD: At the upper left show the kicker “JUNIOR EARTH-SYSTEM SCIENTIST,” title “EARTH IN CHANGE: WEST KALIMANTAN,” and the current objective. At upper right show “FIELD MODE” and progress “0 / 7 objectives,” updating through seven objectives. At the bottom show a contextual dark panel such as “Click to investigate: 🔥 Wildfire,” and a small legend: “WASD move · mouse look · click investigate · Esc unlock mouse.”

The objective sequence and interactions must be:
1. Start with “Find the wildfire.” Walking to and clicking the orange 🔥 Wildfire marker advances the objective and opens an information modal explaining that wildfire is a disturbance in the biosphere and geosphere and that burning vegetation releases smoke and particles into the atmosphere. Make clear it is a scenario model, not a real-time fire map.
2. “Investigate the smoke.” Clicking the 🌫️ Smoke marker advances the objective and opens an information modal explaining gases, particles, reduced visibility, altered light, aerosols as an abiotic air factor, and that aerosols can act as condensation nuclei. Clicking other field markers opens educational modals without necessarily advancing: vegetation is biotic and fire can reduce plant cover, habitat, and ecosystem health; water is an abiotic hydrosphere factor affecting fire risk and recovery; clouds are atmospheric condensed water droplets or ice crystals.
3. “Test the air.” Enter the Cloud Laboratory through its 🧪 gate/marker. Switch to a simple laboratory scene/room with a floor, table, transparent bottle/chamber, removable cap, bicycle pump, liquid container, incense stick/aerosol source, lamp/light beam, LUX sensor and display, small condensed-water cloud, and visible aerosol particles. On entry, open a “Cloud Laboratory” modal with the instruction “BUILD THE CLOUD CHAMBER.” The visible cloud must be explained as condensed water droplets, not PM2.5. Provide ordered controls: pick up bottle, add alcohol/water, attach cap, connect pump, lamp on/off, move lamp, position LUX sensor, move sensor, add aerosol sample, start experiment, and return to field. Show state text for bottle, liquid, pressure LOW/MEDIUM/HIGH, lamp, sensor alignment, LUX, and aerosol. Enforce the setup: cannot pump an unsealed bottle, start without the lamp on, or start with the sensor misaligned. Moving lamp or sensor changes a control variable and warns that a fair test requires constant light position, sensor position, bottle, and distance. Adding aerosol reveals particles and incense and describes them as a simplified model of wildfire combustion particles. When validly started, show the sequence “VAPOR → PARTICLES → CONDENSATION → CLOUD.”

Require a scientist notebook with nine manually entered trials: three “No Aerosol,” three “Aerosol,” and three “Higher Aerosol,” each requesting LUX, cloud duration in seconds, and cloud density from 1–5. Do not automatically fabricate measurements; require all nine entries and reject incomplete/non-numeric entries. On recording, average the three groups and advance to the pattern stage.

4. “Record your results.” Open a “Pattern Lab” modal with three simple bar graphs based on the entered averages: Average LUX, Cloud Duration, and Cloud Density, labeled A/B/C. Let the player click a graph and choose among “Values change as aerosol condition increases,” “All conditions are exactly the same,” and “More evidence is needed.” Explain that LUX measures light intensity reaching the sensor and does not directly measure PM2.5; allow cautious conclusions when evidence is limited.
5. “Find the pattern.” Provide an Earth Data Room reachable from a 📅 gate/marker. Open “Earth Data Room · 2015–2026,” with clickable years 2015 through 2026. Explain that hotspot data are separate from PM2.5/aerosol data and cite the displayed source labels NASA FIRMS, ASMC, BMKG, and WHO. Include the actual available classroom-data distinctions: 2015 reports moderate to dense smoke haze over parts of Kalimantan in August but no comparable West Kalimantan PM2.5 series; 2019 reports haze from hotspots in parts of Kalimantan in September but no comparable local PM2.5 series; 2021 provides WHO PM2.5 guideline context rather than local measurements and suggests NASA FIRMS for satellite detections; other years state that no comparable reliable data are loaded and hotspot detections must remain separate from PM2.5/aerosol measurements.
6. “Connect the systems.” From the data room open a system-connection activity. Let the player click two labeled objects in sequence: 🔥 Wildfire, 🌫️ Atmosphere, 🌳 Biosphere, 💧 Hydrosphere, and 🪨 Geosphere. Recognize supported example pairings including Wildfire → Atmosphere, Atmosphere → Atmosphere as implemented, Wildfire → Biosphere, Water availability/Hydrosphere → Biosphere, and Wildfire → Geosphere; report unsupported pairs as “More evidence is needed.”
7. “Plan for 2036.” Open “Scenario Simulation · 2026 → 2036,” explicitly saying it is a scenario, not a guaranteed prediction. Offer toggle buttons for Fire prevention, Forest protection, Reforestation, Water management, Air-quality monitoring, Satellite monitoring, Community education, and Sustainable land management. Show selected actions, then let the player run to 2036. Finish with an “INVESTIGATION COMPLETE” modal summarizing the discovered problem as wildfire activity and atmospheric pollution, evidence from experiment/historical data/environmental observations, connected atmosphere/biosphere/hydrosphere/geosphere, and the cause-effect relationship that wildfire can contribute to smoke/aerosols and atmospheric change affecting ecosystems through altered light, air quality, and water interactions. List the chosen future action plan and completion tags such as conflict, cause and effect, biotic + abiotic factors, experiment, 3 trials, data graph, historical trends, Earth-system connections, generalization, conclusion, improvement plan, and 2036 scenario.

Use modal dialogs for all educational content and controls. Keep the tone classroom-science oriented and careful about evidence: distinguish visible clouds from PM2.5, hotspot detections from air-quality measurements, and scenarios from predictions. Ensure clicking close/continue returns to play, lab return restores the outdoor field, and the final screen can return to the field. Make the game fully playable rather than a slideshow, with the outdoor investigation and modal activities driving the seven-objective progress counter.