Project 16: Steam Store Page Builder

A complete store page package with capsule images, trailer plan, copy variants, and tag strategy.

Quick Reference

Attribute Value
Difficulty Level 2
Time Estimate 1 week
Main Programming Language C# (.NET 8) + MonoGame
Alternative Programming Languages F#, C++ (raylib), Godot C#
Coolness Level Level 3
Business Potential Level 3
Prerequisites Deterministic loop basics, debugging discipline, content pipeline fundamentals
Key Topics Positioning clarity, Visual hierarchy, Wishlist conversion loops

1. Learning Objectives

  1. Translate one concrete production question into a testable implementation plan.
  2. Implement and validate the feature in a MonoGame runtime context.
  3. Instrument success and failure paths with actionable diagnostics.
  4. Produce a repeatable demo artifact for portfolio or interview use.

2. All Theory Needed (Per-Concept Breakdown)

Positioning clarity

Fundamentals Positioning clarity is central to this project because it defines the non-negotiable behavioral contract for the feature. You should be able to describe valid inputs, legal state transitions, and expected outputs under normal and failure conditions.

Deep Dive into the concept Treat Positioning clarity as a boundary-setting mechanism. Start by defining the smallest deterministic scenario that proves the feature works. Stress that scenario under altered timing, altered content inputs, and altered user actions. If behavior changes unexpectedly, document hidden coupling and sequence assumptions. Keep transitions explicit and observable via logs or debug panels. Connect each transition to an event record so regression analysis is possible after refactors.

Visual hierarchy

Fundamentals Visual hierarchy ensures the project scales from local prototype behavior to repeatable system behavior.

Deep Dive into the concept Use Visual hierarchy to reason about data flow ownership and mutation timing. Document where writes occur, when validation runs, and how rollback behaves if a write fails.

Wishlist conversion loops

Fundamentals Wishlist conversion loops connects this project to shipping reality by forcing you to think about operational constraints early.

Deep Dive into the concept Define one production-like failure mode related to Wishlist conversion loops and build a mitigation checklist. The solution is complete when you can demonstrate both a golden path and a controlled failure path.

3. Project Specification

3.1 What You Will Build

A store-page production workspace that prepares capsule assets, copy variants, and conversion checklist reports for Steam partner submission.

Visible game deliverable:

  • Capsule preview board for all required Steam sizes
  • Copy panel with short and long description variants
  • Checklist meter for clarity/CTA/tag alignment

3.2 Functional Requirements

  1. Generate all required capsule image variants with naming conventions.
  2. Author and compare short/long copy variants.
  3. Map tags to positioning hypothesis and audience intent.
  4. Produce a readiness report with explicit pass/fail criteria.

3.3 Non-Functional Requirements

  • Performance: Must remain inside project-appropriate frame budget.
  • Reliability: Must recover from at least one injected failure mode.
  • Usability: Outcome must be observable by a reviewer in under two minutes.

3.4 Example Usage / Output

[STORE] capsules_exported=3 required_sizes=PASS
[STORE] copy_variant=B readability=0.82
[STORE] readiness_score=96%

3.5 Data Formats / Schemas / Protocols

  • Event record: {timestamp, module, action, result}
  • Feature state snapshot: {version, state, counters, flags}

3.6 Edge Cases

  • Text truncation at common viewport widths.
  • Capsule focal point unreadable at smallest size.
  • Tag set misaligned with actual gameplay loop.

3.7 Real World Outcome

This is a game-facing outcome you can see and play immediately.

What you will see in the game window:

  • Capsule preview board for all required Steam sizes
  • Copy panel with short and long description variants
  • Checklist meter for clarity/CTA/tag alignment

Project 16 Steam Store Page Builder Window Mockup

How you interact:

  • A/B toggles copy variants
  • E exports capsule set
  • R runs readiness checklist

3.7.1 How to Run (Copy/Paste)

$ dotnet restore
$ dotnet build
$ dotnet run --project src/Game -- --scene store-page-lab

3.7.2 Golden Path Demo (Deterministic)

  1. Start the scene and confirm all HUD panels load.
  2. Perform the three core interactions listed above.
  3. Verify the success signal appears without warnings.

3.7.3 If CLI: exact transcript

$ dotnet run --project src/Game -- --scene store-page-lab
[STORE] capsules_exported=3 required_sizes=PASS
[STORE] copy_variant=B readability=0.82
[STORE] readiness_score=96%

3.7.7 If GUI / Desktop

+------------------------------------------------------+
| store-page-lab                                   [F1 HUD] |
|------------------------------------------------------|
| PLAYFIELD: gameplay objects and interactions         |
| HUD: key metrics + status badges                    |
| STATUS: success/failure cues and prompts            |
+------------------------------------------------------+

4. Solution Architecture

4.1 High-Level Design

Positioning Brief -> Asset Builder -> Copy Variant Engine -> Checklist Validator -> Export Package

Positioning Brief -> Asset Builder -> Copy Variant Engine -> Checklist Validator -> Export Package

4.2 Key Components

Component Responsibility Key Decisions
CapsulePackager Produces size-specific marketing images One source layout with controlled crops
CopyVariantLab Compares store copy alternatives Track readability and clarity metrics
StoreReadinessChecker Scores package completeness and quality Hard fail on missing mandatory assets

4.4 Algorithm Overview

  1. Validate preconditions.
  2. Apply deterministic transition.
  3. Emit feedback and telemetry.
  4. Persist if required.

5. Implementation Guide

5.3 The Core Question You’re Answering

“How do you convert impressions to wishlists before launch day?”

5.4 Concepts You Must Understand First

  1. Positioning clarity
  2. Visual hierarchy
  3. Wishlist conversion loops

5.5 Questions to Guide Your Design

  1. How will you validate capsule readability at smallest size?
  2. What criteria pick between copy variant A and B?
  3. Which checklist items are hard blockers for launch?

5.6 Thinking Exercise

Trace one full success path and one failure path on paper before implementation.

5.7 The Interview Questions They’ll Ask

  1. Why did you pick this architecture boundary?
  2. Which failure mode did you prioritize first and why?
  3. How does your instrumentation accelerate debugging?
  4. How would you scale this feature to a larger game?

5.8 Hints in Layers

  • Hint 1: Stabilize one invariant before feature expansion.
  • Hint 2: Add diagnostics before optimization.
  • Hint 3: Keep platform calls at system boundaries.
  • Hint 4: Re-run deterministic scenario after each refactor.

5.9 Books That Will Help

Topic Book Chapter
Core concept “Traction by Gabriel Weinberg and Justin Mares” Relevant concept chapter
Reliability “Release It!” Failure handling chapters
Architecture “Clean Architecture” Boundary and dependency chapters

6. Testing Strategy

  1. Golden path completes and emits success signal.
  2. Injected failure path recovers without crash.
  3. Re-run scenario after restart and confirm consistency.

7. Common Pitfalls & Debugging

  • Hidden initialization order coupling
  • Time-coupled behavior tied to render rate
  • Missing fallback behavior on platform call failure

8. Extensions & Challenges

  • Beginner: add one extra diagnostics panel metric.
  • Intermediate: add replay capture for event flow.
  • Advanced: add automated stress test harness.

9. Real-World Connections

This project mirrors shipping feature-module work in real indie and mid-size game teams.

10. Resources

  • Steamworks official docs
  • MonoGame docs
  • Gemini image generation docs (for asset-related projects)

11. Self-Assessment Checklist

  • I can explain the feature invariant and prove it in a demo.
  • I can trigger and handle one deterministic failure scenario.
  • I can describe tradeoffs and future scaling choices.

12. Submission / Completion Criteria

Minimum Viable Completion:

  • Feature works in deterministic golden path.
  • One controlled failure path is handled gracefully.
  • Core diagnostics are visible and documented.

Full Completion:

  • All minimum criteria plus edge-case coverage and regression checks.

Excellence:

  • Includes polished instrumentation and clear productionization notes.