game-dev-agent

An AI assistant for Unity, a tool for building games, covering game code, visual assets, audio, balance settings, and events that happen during play.

In plain words
What is it for?
It is for creating sprites and icons, scaffolding Unity scripts, tuning game parameters, preparing audio files, and generating in-game events.
Why use it?
It brings several game-development jobs into one workflow, including Unity-specific C# code and changes to game settings.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/melons/melons-agents/game-dev-agent
Any agent
npx skills add MelonS/MelonS-Agents --skill game-dev-agent
Clone the repo
git clone --depth 1 https://github.com/MelonS/MelonS-Agents

Made for: Claude Code, Codex.

Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,024 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00046 $0.01024
Opus 5 $0.00023 $0.00512
Sonnet 5 $0.00009 $0.00205
Haiku 4.5 $0.00005 $0.00102

Measured 2d ago against content hash bc632dd402f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

game-dev-agent scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

The scan reads SKILL.md. This mod also ships 17 executable files (scripts/agent.py, scripts/latest_build.py, scripts/modules/__init__.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/game-dev-agent/SKILL.md · 117 lines

How it starts

The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.

game-dev-agent

AI agent that orchestrates Unity game development tasks via CLI. Companion to pawnsim (the actual game built using this agent).

What it does

Modules (each = subagent):

  • asset_gen — Generate sprites / tiles / UI icons via ComfyUI + SDXL, auto-save to Unity Assets folder with proper import settings
  • code_assist — Unity-aware C# scaffolding: MonoBehaviour / ScriptableObject / Editor scripts. Knows Unity 2022.3 API.
  • balance_tune — Read ScriptableObject configs + JSON balance files, propose parameter tuning. Game-dev specific (beyond what general AI code assistants do).
  • audio_gen — BGM via Suno (operator-provided files), SFX via local AudioCraft / freesound API. Auto-conform to Unity AudioClip import.
  • runtime_director (in-game AI) — LLM-driven event generation for the game itself, demonstrating dev-time + runtime AI agent patterns.

Why this skill matters

Career positioning: combines deep game-dev domain (operator's existing strength) with AI agent engineering (rare, emerging hire-niche). Portfolio = (this agent) + (game built with it) = T-shape proof.

Operator-specific:

  • Operator has 10+ year game dev background
  • AI agent engineer roles emerging in game industry + general tech
  • Game industry downturn — pure game-dev roles competitive
  • AI agent angle = downturn-resilient niche

Usage (planned, Day 1)

# Generate a sprite
python skills/game-dev-agent/scripts/agent.py gen-sprite \
    "evil knight enemy, 2D pixel art, top-down view, simple silhouette" \
    --output Assets/Sprites/enemy_knight.png

# Scaffold Unity MonoBehaviour script
python skills/game-dev-agent/scripts/agent.py code \
    "PlayerMovement: top-down 2D, WASD input, 5 m/s speed" \
    --output Assets/Scripts/PlayerMovement.cs

# Analyze + propose balance changes
python skills/game-dev-agent/scripts/agent.py balance \
    --config Assets/Configs/enemies.json \
    --goal "make wave 5 challenging but beatable"

# Generate BGM via Suno (operator provides Suno prompt template)
python skills/game-dev-agent/scripts/agent.py audio \
    --style "lofi dungeon synth, slow, atmospheric" \
    --output Assets/Audio/BGM_dungeon.mp3

Read the full file on GitHub · 117 lines

Files

What ships with it

38 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 117 lines · 46 tokens per session scan A bc632dd402f0

Subscribe to this mod's changes

game-dev-agent is a skill published in the GitHub repository MelonS/MelonS-Agents (16 stars, last pushed 11d ago), licensed MIT. It adds 46 tokens to every session and 1,024 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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