unity-ai-game-creator

---
name: unity-ai-game-creator
description: "Unity AI Game Creator workflow skill. Use this skill when the user needs Transform raw game ideas into complete Unity projects with AI-powered asset generation, scene blueprints, music/SFX prompts, and step-by-step development procedures using Unity 6+ and modern AI tools and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off."
version: "0.0.1"
category: ai-agents
tags: ["unity", "game-development", "ai-generation", "asset-pipeline", "scene-design", "music-generation", "game-design-document", "unity-ai-game-creator"]
complexity: advanced
risk: caution
tools: ["cursor", "antigravity", "codex-cli", "claude-code", "gemini-cli", "opencode"]
source: community
author: "Mann-Makhecha"
date_added: "2026-05-17"
date_updated: "2026-05-17"
---

# Unity AI Game Creator

## Overview

This public intake copy packages `plugins/antigravity-awesome-skills-claude/skills/unity-ai-game-creator` from `https://github.com/sickn33/antigravity-awesome-skills` into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the `external_source` block in `metadata.json` plus `ORIGIN.md` as the provenance anchor for review.

# Unity AI Game Creator

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: How It Works, Limitations, Security & Safety Notes, Common Pitfalls.

## When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

- Use when a user describes a game idea and wants a complete development plan
- Use when generating AI prompts for 3D models, textures, music, sound effects, or UI assets
- Use when setting up a new Unity project from scratch with modern architecture
- Use when creating Scene Blueprints from a concept description
- Use when building a Game Design Document (GDD) from a rough idea
- Use when leveraging Unity AI Assistant, MCP server, or external AI tools in a game workflow

## Operating Table

| Situation | Start here | Why it matters |
| --- | --- | --- |
| First-time use | `metadata.json` | Confirms repository, branch, commit, and imported path through the `external_source` block before touching the copied workflow |
| Provenance review | `ORIGIN.md` | Gives reviewers a plain-language audit trail for the imported source |
| Workflow execution | `SKILL.md` | Starts with the smallest copied file that materially changes execution |
| Supporting context | `SKILL.md` | Adds the next most relevant copied source file without loading the entire package |
| Handoff decision | `## Related Skills` | Helps the operator switch to a stronger native skill when the task drifts |

## Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

### Imported Workflow Notes

#### Imported: Overview

This skill transforms a raw game concept into a fully structured Unity development plan with AI-generated assets, scenes, music, scripts, and deployment-ready builds. It guides the agent through a 5-phase pipeline — from extracting core game dimensions to producing ready-to-use AI prompts for every asset category — using the latest Unity 6+ features and AI tooling ecosystem. Unlike generic Unity reference skills, this skill is workflow-driven: the user provides an idea, and the agent delivers a complete, actionable game development roadmap.

#### Imported: How It Works

### Master Pipeline

Execute these phases in order. Each phase produces concrete deliverables before advancing.

```
PHASE 1: IDEATION ──▶ PHASE 2: BLUEPRINT ──▶ PHASE 3: GENERATION ──▶ PHASE 4: ASSEMBLY ──▶ PHASE 5: DEPLOYMENT
  Game Brief            GDD + Scenes           AI Prompts + Assets     Project Setup          Build + Store
  Genre Analysis        Architecture           Scripts + Audio         Core Systems           QA + Submit
  Scope Assessment      Scene Blueprints       Voice + UI              Polish + Juice         Analytics
```

### Phase 1: Ideation & Deep Analysis

Extract and clarify these dimensions from the user's game idea. Ask only for what is ambiguous — infer the rest from context.

| Dimension | What to Extract | If Unclear |
|-----------|----------------|------------|
| **Genre** | Primary + secondary genre blend | Suggest 3 genre combinations |
| **Platform** | Mobile, PC, Console, WebGL, VR/AR | Recommend based on scope |
| **Perspective** | 2D, 2.5D, 3D, Top-down, Side-scroll, FPS, TPS | Infer from genre |
| **Art Style** | Realistic, Stylized, Pixel, Low-poly, Anime, Painterly | Suggest 3 options |
| **Core Loop** | The 30-second repeating gameplay action | Identify from description |
| **Target Audience** | Age range, gamer profile, platform habits | Recommend based on genre |
| **Session Length** | Average play session duration | Infer from platform + genre |
| **Monetization** | Free-to-play, Premium, Hybrid | Recommend based on platform |
| **Scope** | Solo dev, small team, studio | Ask if not obvious |
| **Timeline** | MVP in weeks, full release target | Suggest realistic milestones |

**Also provide:**
1. **Top 3 Reference Games** — What they do well, what the user can learn
2. **Market Gap** — What opportunity exists that competitors miss
3. **Core Differentiator** — The one unique thing about this game
4. **Risk Assessment** — Technical and market risks with mitigations

**Scope Calibration:**

| Scope | Timeline | Team Size | Feature Budget |
|-------|----------|-----------|----------------|
| Prototype | 1–2 weeks | Solo | Core loop only |
| Vertical Slice | 4–6 weeks | Solo–2 | 1 complete level + polish |
| MVP | 8–12 weeks | 2–4 | 3–5 levels + save + UI |
| Full Release | 16–24+ weeks | 3–8 | Complete content + multiplayer |

### Phase 2: Blueprint & Design

#### Game Design Document (GDD)

Generate a structured GDD covering:

1. **Executive Summary** — Elevator pitch, genre, USPs
2. **Gameplay** — Core loop diagram, progression, abilities, win/loss, difficulty curve
3. **World & Narrative** — Setting, characters, level structure
4. **Art Direction** — Visual style, color palette (hex codes), reference descriptions, UI/UX style
5. **Audio Direction** — Music style per scene, SFX categories, voice needs
6. **Technical Spec** — Unity version, render pipeline, performance budgets, SDKs
7. **Monetization Strategy** — Revenue model, IAP design, ad placement
8. **Development Roadmap** — Phases, milestones, feature priority matrix, risk register

#### Scene Blueprints

For each scene, produce a hierarchy covering:

- **Environment** — Ground/terrain, skybox, lighting setup, props with positions
- **Interactive Objects** — Behavior on interaction
- **Characters / NPCs** — AI behavior, patrol paths, dialogue triggers
- **UI Overlay** — HUD elements, contextual prompts
- **Audio Layers** — Background music (mood, tempo, loop point), ambient SFX, trigger SFX
- **Camera Setup** — Type (Cinemachine/Fixed/Follow), behavior configuration
- **Systems Active** — Save checkpoints, spawners, particle effects

#### Architecture Blueprint

Provide recommended project folder structure:

```
Assets/_Project/
├── Scripts/ (Core, Gameplay, UI, Data, Audio, Utilities)
├── Prefabs/ (Characters, Environment, UI, VFX)
├── Scenes/
├── Art/ (Models, Textures, Materials, Animations, UI_Assets)
├── Audio/ (Music, SFX, Ambience)
├── ScriptableObjects/
└── Resources/
```

### Phase 3: AI-Powered Asset Generation

For every asset category, provide ready-to-use prompts for the best current AI tools.

#### 3D Model Prompts

Recommend tools dynamically (Meshy.ai, Tripo3D, Rodin, Unity AI Assistant) and generate prompts including:
- Asset name, art style, gameplay purpose
- Polygon budget, texture resolution, PBR maps needed
- Animation-ready flag, scale reference
- Unity import settings (scale factor, normals, animation type, material handling)

#### Texture & 2D Asset Prompts

Recommend tools (Leonardo.ai, Midjourney, DALL·E, Unity AI Assistant) and generate prompts including:
- Texture type (seamless tile, sprite, UI element, concept art)
- Resolution, style, tiling requirements, PBR maps
- Unity import settings (texture type, filter mode, compression, max size)

#### Music Prompts

Recommend tools (Suno, Soundraw, Sonauto) and generate prompts including:
- Track name, scene context, mood, tempo (BPM), duration
- Instruments, reference tracks, loop points, dynamic layers
- Unity import settings (format, load type, compression, loop config)

#### Sound Effects Prompts

Recommend tools (ElevenLabs, OptimizerAI/SFX Engine) and generate prompts including:
- SFX name, category, gameplay context, duration
- Variation count, characteristics
- Unity import settings (format, load type, 3D sound config, variation arrays)

#### Voice & Narration Prompts

Recommend tools (ElevenLabs, Play.ht, Coqui) and generate prompts including:
- Character name, voice profile, dialogue line, emotion, context

#### UI/UX Asset Prompts

Generate specifications for Unity UI Toolkit or AI image generation including:
- Element name, screen context, visual style
- States (normal, hover, pressed, disabled)
- Dimensions, anchor behavior, animation descriptions

### Phase 4: Assembly & Development

#### Project Initialization Checklist

- Unity version (recommend latest Unity 6 LTS)
- Render pipeline (URP for mobile/stylized, HDRP for high-fidelity, Built-in for 2D)
- Build settings, player settings (color space, scripting backend, API compatibility)
- Essential packages (Input System, Cinemachine, TextMeshPro, Addressables, Unity AI Assistant)
- Git LFS configuration for large assets

#### Development Order (Week-by-Week)

1. **Foundation** — Project setup, GameManager, event system, scene management, input config
2. **Core Gameplay** — Player controller, camera, core loop, basic enemies
3. **Content & Systems** — Level building, UI system, audio manager, save/load
4. **Polish & Feedback** — VFX/juice, progression, tutorial, settings
5. **Platform & Release** — Profiling, monetization, analytics, platform polish, submission

#### Script Architecture Patterns

- GameManager → Singleton or Service Locator
- Events → Observer Pattern (C# events + ScriptableObject Events)
- Save System → JSON serialization + encryption
- Object Pooling → Generic pool for bullets, enemies, VFX
- State Machine → Player states, game states, enemy AI
- Audio → Singleton with Audio Mixer Groups
- UI → UI Toolkit with MVVM or event binding
- Scene Loading → Addressables + async with progress
- Input → New Input System with Action Maps

#### Unity AI Assistant & MCP Integration

- Setup steps for Unity AI Assistant (Unity 6.3+)
- MCP server configuration for external IDE/agent control
- Example in-editor prompts for scene manipulation, scripting, profiling

### Phase 5: Quality & Deployment

#### Performance Budgets

|                    | Mobile    | PC        | Console   |
|--------------------|-----------|-----------|-----------|
| Target FPS         | 30/60     | 60/120    | 60        |
| Draw Calls         | < 100     | < 500     | < 300     |
| Triangles/frame    | < 100K    | < 2M      | < 1M      |
| Texture Memory     | < 150MB   | < 1GB     | < 512MB   |
| Build Size         | < 150MB   | < 2GB     | < 4GB     |

#### Testing Checklist

Core loop stability, UI responsiveness, save/load persistence, audio balance, memory leak checks, frame rate stability, input device coverage, edge cases (low battery, interruptions), accessibility, localization.

#### Store Submission Guide

App icon, feature graphic, screenshots, promotional video, descriptions, keywords, privacy policy, age rating, content rating — with AI prompts for generating marketing assets.

## Examples

### Example 1: Ask for the upstream workflow directly

```text
Use @unity-ai-game-creator to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
```

**Explanation:** This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

### Example 2: Ask for a provenance-grounded review

```text
Review @unity-ai-game-creator against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
```

**Explanation:** Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

### Example 3: Narrow the copied support files before execution

```text
Use @unity-ai-game-creator for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
```

**Explanation:** This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

### Example 4: Build a reviewer packet

```text
Review @unity-ai-game-creator using the copied upstream files plus provenance, then summarize any gaps before merge.
```

**Explanation:** This is useful when the PR is waiting for human review and you want a repeatable audit packet.

### Imported Usage Notes

#### Imported: Examples

### Example 1: Cozy Farming Game

**User:** "I want to make a cozy farming game with magic elements for mobile"

**Agent delivers:**
1. **Game Brief** — Cozy farm sim × magical creatures, mobile portrait, stylized low-poly, 5-min sessions, F2P with cosmetic IAP
2. **3 Reference Games** — Stardew Valley (loop), Merge Magic (mobile UX), Moonstone Island (magic farm blend)
3. **Core Loop** — Plant → Tend → Harvest → Sell → Upgrade → Discover magical seeds
4. **Scene Blueprints** — Farm (main), Village Market, Enchanted Forest, Player Home
5. **AI Asset Kit** — 15 crop models, 8 building models, 5 character models, seasonal music tracks, ambient farm SFX, UI kit
6. **Technical Plan** — Unity 6 LTS + URP, mobile-first 30fps, addressable assets for seasonal updates
7. **6-Week Roadmap** — Foundation → Core Gameplay → Content → Monetization → Polish → Soft Launch

### Example 2: Multiplayer Shooter

**User:** "Make a fast-paced arena shooter for PC with neon visuals"

**Agent delivers:**
1. **Game Brief** — Arena FPS, PC/Steam, stylized neon cyberpunk, 10-min matches, Premium $9.99
2. **Core Loop** — Spawn → Loot → Fight → Eliminate → Score → Respawn
3. **Technical Plan** — Unity 6 + HDRP, Netcode for GameObjects, dedicated servers, 120fps target
4. **AI Asset Kit** — Arena models, weapon models, neon material/shader prompts, electronic music tracks, weapon SFX

### Example 3: 2D Puzzle Mobile

**User:** "Simple puzzle game like Wordle but with colors"

**Agent delivers:**
1. **Game Brief** — Casual puzzle, mobile portrait, flat minimalist, 2-min sessions, F2P with rewarded ads
2. **Scope** — Prototype in 1 week, MVP in 3 weeks
3. **Scene Blueprints** — Main Menu, Game Board, Results Screen, Daily Challenge
4. **AI Asset Kit** — UI sprites, celebration particles, calm ambient music, tap/swipe SFX

## Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

- ✅ Start with the core loop — Nail the 30-second cycle before anything else
- ✅ Profile before optimizing — Use Unity Profiler to find real bottlenecks
- ✅ Use ScriptableObjects for data — Decouple data from logic for flexibility
- ✅ Generate multiple AI asset variations — Pick the best from 3–5 generations
- ✅ Test on real devices early — Emulators miss platform-specific issues
- ✅ Version control from day one — Git + LFS, commit often
- ❌ Don't hardcode tool choices — Always present alternatives to the user

### Imported Operating Notes

#### Imported: Best Practices

- ✅ **Start with the core loop** — Nail the 30-second cycle before anything else
- ✅ **Profile before optimizing** — Use Unity Profiler to find real bottlenecks
- ✅ **Use ScriptableObjects for data** — Decouple data from logic for flexibility
- ✅ **Generate multiple AI asset variations** — Pick the best from 3–5 generations
- ✅ **Test on real devices early** — Emulators miss platform-specific issues
- ✅ **Version control from day one** — Git + LFS, commit often
- ❌ **Don't hardcode tool choices** — Always present alternatives to the user
- ❌ **Don't skip the GDD** — Even solo projects benefit from written design
- ❌ **Don't optimize prematurely** — Make it work, make it right, make it fast
- ❌ **Don't ship AI assets without review** — Check licensing terms for each tool

## Troubleshooting

### Problem: The operator skipped the imported context and answered too generically

**Symptoms:** The result ignores the upstream workflow in `plugins/antigravity-awesome-skills-claude/skills/unity-ai-game-creator`, fails to mention provenance, or does not use any copied source files at all.
**Solution:** Re-open `metadata.json`, `ORIGIN.md`, and the most relevant copied upstream files. Check the `external_source` block first, then restate the provenance before continuing.

### Problem: The imported workflow feels incomplete during review

**Symptoms:** Reviewers can see the generated `SKILL.md`, but they cannot quickly tell which references, examples, or scripts matter for the current task.
**Solution:** Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

### Problem: The task drifted into a different specialization

**Symptoms:** The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
**Solution:** Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.



## Related Skills

- `@20-andruia-niche-intelligence-v2` - Use when the work is better handled by that native specialization after this imported skill establishes context.
- `@advogado-criminal-v2` - Use when the work is better handled by that native specialization after this imported skill establishes context.
- `@advogado-especialista-v2` - Use when the work is better handled by that native specialization after this imported skill establishes context.
- `@agent-memory-systems-v2` - Use when the work is better handled by that native specialization after this imported skill establishes context.

## Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

| Resource family | What it gives the reviewer | Example path |
| --- | --- | --- |
| `references` | copied reference notes, guides, or background material from upstream | `references/n/a` |
| `examples` | worked examples or reusable prompts copied from upstream | `examples/n/a` |
| `scripts` | upstream helper scripts that change execution or validation | `scripts/n/a` |
| `agents` | routing or delegation notes that are genuinely part of the imported package | `agents/n/a` |
| `assets` | supporting assets or schemas copied from the source package | `assets/n/a` |



### Imported Reference Notes

#### Imported: Limitations

- This skill does not replace environment-specific validation, testing, or expert review.
- AI-generated assets require legal review for commercial usage rights per each tool's Terms of Service.
- Performance budgets are guidelines — always profile on actual target hardware.
- AI tools and their capabilities evolve rapidly — verify current availability and pricing before recommending.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

#### Imported: Security & Safety Notes

- This skill does not include shell commands, network fetches, or credential handling.
- All AI tool recommendations are external services; the skill does not execute API calls or store tokens.
- Asset generation prompts are text-only guidance — no automated downloads or file mutations occur.

#### Imported: Common Pitfalls

- **Problem:** User provides a vague idea like "make a game"
  **Solution:** Ask 2–3 targeted questions (genre, platform, scope) before generating the first draft

- **Problem:** Scope creep — trying to build everything at once
  **Solution:** Use the scope calibration table and feature priority matrix (Must/Should/Could/Won't)

- **Problem:** AI-generated assets don't match the art style
  **Solution:** Always include the GDD's art direction keywords in every asset prompt for consistency

- **Problem:** Performance issues on target platform
  **Solution:** Set platform-specific budgets early and profile against them weekly