Ai Asset Generation

AI Asset Generation

Purpose

Generate production-candidate game assets from text prompts through the generative provider registry (manifests/asset-providers.json) so projects can move from procedural placeholders to real content without leaving the scaffold — while keeping generation engine-neutral, reproducible, provenance-tracked, and subject to the same acceptance gates as authored content.

Optional Capability — Gate Before Use

AI generation is an optional layer, not a dependency. It is available only when the active provider's API key is set in the environment (FAL_KEY for the default fal.ai provider). The scaffold's asset workflow does not require it:

• Key present → this skill is available; the project may upgrade placeholders to

generated content.

• Key absent → this skill is inert. Fall back to the default scaffold tooling

exactly as before the capability existed — placeholder-asset-pipeline and the engine placeholder commands (/unity-placeholders, /godot-placeholders, /web-placeholders) for sprites, 3D primitives, and procedural audio. A project built entirely on placeholders is a fully valid, shippable-to-prototype outcome; generation is an enhancement, never a gate.

Detecting the gate is cheap: the generator (scripts/generate-assets.js) reads the key from the environment and reports clearly when it is missing, pointing back to the placeholder path. Never fabricate or hand-place assets to "stand in" for the API.

Resolution Order and Cost

• Prefer free before paid. For image/skybox (the registry's

nativeFirstCapabilities), if the running harness has a native image generator (e.g. Codex $imagegen), use it instead of the paid API — keep the same names, paths, and acceptance gates. Fall to the API only when no native generator exists and a key is set; fall to placeholders otherwise. model3d/sfx/music/speech/ video have no native path — API or placeholders only.

• Confirm before spending. Every run prints an estimated cost; the generator

refuses runs at or above confirmOverUsd without --yes. For a single asset the user explicitly asked for, dry-run, show the estimate, and proceed if cheap. For autonomous or batch flows, get a clear yes on the total before running. Iterate on the cheap default model; reserve the expensive alternative and video for finals.

• Quality vs price tier. Ask the user once, before a batch, which tier to use —

budget, balanced, or premium — and pass --quality (default balanced). The registry's byQuality map picks the model per capability (e.g. image: flux-schnell / nano-banana-2 / nano-banana-pro; video: Wan / Seedance / Veo). Budget can keep a whole video run under the cost gate; premium crosses it and needs --yes. Tier sets the spend; the gate prevents surprises.

Use When

• placeholder assets exist and the project is ready to upgrade them to real content
• a game needs images, textures, skyboxes, 3D models, sound effects, music, voice

lines, or intro/cinematic video that no artist is available to produce

• concept art needs to be lifted into 3D (image-to-3D) or into motion (image-to-video)
• the team wants reproducible asset generation runs (prompt + seed + model recorded)

instead of one-off results pasted from a chat tool

Inputs

• the provider registry (manifests/asset-providers.json) and a valid API key in the

provider's apiKeyEnv environment variable (never committed)

• art bible or visual direction document, and the audio direction where relevant
• asset inventory: which entities need which asset type, at which target size or length
• the placeholder manifest of the project, so generated files can adopt the same

names and paths (drop-in replacement contract)

• a staging directory outside the engine's import folders

Process

1. classify each requested asset by capability: image, skybox, model3d,

sfx, music, speech, or video

1. define the acceptance contract before generating (for raster assets this is the

generated-raster-asset-pipeline contract: background policy, display size, collision envelope; for audio: length, loopability, loudness target; for 3D: poly budget, scale, pivot; for video: duration, aspect ratio, codec)

1. resolve the model from the registry — do not hardcode model ids in project code;

pass --model only to deviate intentionally

1. dry-run first to review the resolved payload:

node scripts/generate-assets.js --type --prompt "..." --out --dry-run

1. generate with a fixed --seed where the model supports it, iterating on the

cheap/fast default model and switching to the higher-fidelity alternative for finals

1. review candidates against the acceptance contract before any engine import
2. move accepted files into the project under the placeholder names and paths, keep

the .provenance.json sidecar next to each accepted asset, and record raster assets in the project's generated-assets.json manifest

1. import through the active engine layer only (Unity/Unreal/Godot/web import rules

stay in their engine packs), then run the matching review command (/art-2d-pass, /art-3d-pass, /audio-pass)

Outputs

• generated asset files in neutral formats (PNG, GLB, MP3/WAV, MP4) staged and then

integrated under the project's existing names and paths

• a .provenance.json sidecar per generation run: provider, model, prompt, seed,

request id, timestamp, source URLs, license note

• updated generated-assets.json entries for accepted raster assets
• a short generation log in the project docs: what was generated, with which model,

what was rejected and why

Quality Bar

• every generated file has a provenance sidecar; an asset without provenance is

treated as unlicensed third-party content

• generation is reproducible: prompt, seed, and model id recorded, so a lost file

can be regenerated or deliberately re-rolled

• generated assets pass the same acceptance gates as authored content — no

"the AI made it" exemption from naming, budget, or review rules

• engine isolation holds: the generation step never writes into engine-specific

import folders directly

• cost is managed deliberately: iterate cheap, finalize expensive, and dry-run

video (the costliest capability) before batch runs

Common Failure Modes

• hardcoding a model id in project code or docs and having it rot when the provider

catalog rotates — the registry is the only source of truth

• accepting a "transparent" sprite with a baked checkerboard background (run the

raster acceptance contract; validate:generated-assets catches PNGs)

• treating a generated skybox as valid without checking the equirectangular 2:1

projection and horizon continuity

• importing a generated GLB at the wrong scale because the poly/scale/pivot contract

was never defined before generation

• generating voice lines outside the localization pipeline and discovering the

text was never source-controlled

• burning budget on video generation iterations that an image-to-video workflow

with an accepted still would have art-directed for a fraction of the cost

Related Agents

• technical-artist
• 2d-artist
• audio-designer

Related Commands

• generate-assets
• art-2d-pass
• art-3d-pass
• audio-pass

Related Skills

• generated-raster-asset-pipeline
• placeholder-asset-pipeline
• 3d-asset-pipeline
• cinematic-pipeline
• audio-implementation

Notes

• The registry's default provider is fal.ai because a single pay-per-use key covers

every capability; the design is provider-agnostic and a second provider is a manifest entry away.

• Rigging and animation of generated 3D models are out of scope for the current

registry — generated meshes are static; route rigging through the rigging-skinning-pipeline skill and a dedicated tool or provider.

• An optional fal-media MCP server (see mcp-configs/mcp-servers.json) exposes the

same catalog interactively for exploration; reproducible production runs should go through scripts/generate-assets.js so provenance is written.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: MRCalderon3D
• Source: MRCalderon3D/everything-game-dev-code
• License: MIT

Install and usage instructions live in the source repository linked above.