CASTLE OF TRAPS

Castle of Traps is a small UE5 demo I built independently during a game jam to showcase my Level Design, Blueprint Programming, and Prototyping skills. The game is a linear, trap-based challenge where players navigate hazards, collect medieval helmets, and reach the final open area of the castle.

QUICK BREAKDOWN

Designed and built in under 14 hours during a game jam.
  • Fully solo project: all gameplay logic, traps, layout, lighting, and flow by me.
  • Created to demonstrate:
    • Strong Blueprint scripting abilities
    • Understanding of level pacing and difficulty ramping
    • Ability to design readable but challenging environments
  • Uses darker lighting intentionally to increase tension and force players to read environmental cues.
  • Helmet collectibles encourage exploration and teach players risk-reward decision making.

FEATURES AND DOCUMENTATION

CLICK TO DOWNLOAD PROJECT

Blueprint Programming
  • Modular trap systems: collapsing floors, closing spikes, rotating blades, moving saws, spike pillars.
  • Timeline-based motion, collision volumes, damage application, respawn logic.
  • Interaction systems (doors), health manager, collectible logic, and exit triggers.
Level Design
  • Linear level structured around learn → test → combine progression.
  • Difficulty escalates by stacking previously learned mechanics.
  • Clear player flow with intentional lighting and silhouettes to guide attention.
  • Reward space at the end with optional high-skill parkour challenges.
Trap Sequence Highlights
  • Crumbling Floor Bridge: teaches timing + risk-reward through center collectible.
  • Closing Wall Spikes: introduces pressure + vertical movement.
  • Revolving Blade Corridor: tests prediction and hazard reading.
  • Rotating Log Over Spikes: requires precision and momentum control.
  • Ground Saws: multi-directional avoidance.
  • Spike Pillar Chamber: layered hazards + limited visibility = skill test.

What I Learned

  • Improved my ability to scope and execute a full gameplay loop within strict time constraints.

  • Strengthened my skills in rapid prototyping, including fast iteration of block-outs, movement metrics, and encounter spacing.

  • Gained hands-on experience building modular and scalable Blueprint systems suitable for reuse across different trap types.

  • Enhanced my understanding of encounter pacing, including anticipation cues, failure punishment, reward placement, and player flow metrics.

  • Learned how lighting, contrast, and silhouette readability affect player decision-making and trap recognition in real time.

  • Developed better intuition for safe zone placement, linearity control, and critical path clarity.

  • Realized the value of cross-disciplinary collaboration for more complex mechanics (e.g., AI systems, multi-layered interactions, narrative integration), helping me better understand scope boundaries for solo LD work.