

KHURDA LALBE3
Khurda lalbe3 (خردة للبيع) is a negotiation and economy-management game built solo in Unity 6, following a repeating day cycle of buying junk cheap from roadside sellers, haggling hard, and reselling the haul for profit before your cash or reputation run out.
The game is built around a custom slider-based negotiation system, a hidden acceptance threshold, three tries per deal, and four escalating reaction tiers, that recalculates a fresh haggling range for every item and every seller, layered on top of a full day/night economy loop, a difficulty curve that tightens over time, and complete English/Arabic localization with proper right-to-left text rendering.
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Details:
Tools used
Github, pixabay, audiomas, asprite, itch.io, C#, Photopea, canva.
Project type: 2D PC / WebGL game
Game genre: Negotiation & economy management
Game engine: Unity 6.3
Time frame: 3 weeks
Core Mechanics — World & Progression
Randomized daily seller roster drawn from a larger pool, spawning and scrolling along the route
Persistent day counter driving a difficulty curve, with a "Day X Reached" milestone transition each day
Full Arabic localization pipeline: RTLTMPro integration, a custom text-shaping and digit-conversion helper, and a batch tool to convert existing localization components
Lose condition on running out of cash or reputation, with a full main menu, pause menu, and settings loop
Metrics
3 tries per negotiation, 4 reaction tiers
2 negotiable deal types
Complete English + Arabic localization with real RTL text support
Full day/night cycle with a dynamic sun arc and shifting ambient light
Core Mechanics — Negotiation & Economy
Slider-based negotiation with a hidden acceptance threshold, 3 tries per deal, and 4 escalating reaction tiers (Insulted, Skeptical, Warm, Accepted)
Offer-history tick marks recorded on the slider track for every rejected offer, color-coded by reaction tier
Per-encounter randomized worth and asking price for every item, so no two visits play the same
Cash and reputation economy, with daily expenses drawn from a random pool plus a fixed repeating weekly schedule

Trailer:
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