Asset Audit logo

Asset Audit

CommunityPopular
Donchitos
asset-audit

Audit assets against naming conventions, file size budgets, format standards. Finds orphaned assets, missing references.

Overview

PublisherDonchitos
RepositoryClaude-Code-Game-Studios
Skill nameasset-audit
Stars
25.8K
Forks
3.7K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Donchitos on GitHub. Read the source before you install it.

Installation

Install the Asset Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Donchitos/Claude-Code-Game-Studios/tree/main/.claude/skills/asset-audit
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Donchitos/Claude-Code-Game-Studios.git /tmp/Claude-Code-Game-Studios
mkdir -p .claude/skills
cp -r /tmp/Claude-Code-Game-Studios/.claude/skills/asset-audit .claude/skills/asset-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Asset Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Asset Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Asset Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Measuring file sizes and formats requires Bash

This skill's report asks for file sizes against budgets, texture dimensions (power-of-two), audio sample rates, and last-modified times for orphan detection. None of those are obtainable from Read/Glob/Grep — they need stat or a binary header read, so the read-only measuring commands (stat, file, od, wc, du) are pre-approved above; list files with Glob. Anything else asks first.

If you cannot take a measurement, the cell is NOT ASSESSED, never an estimate. A size budget table filled from guesses is worse than an empty one: it looks like evidence. This is a live fabrication vector even on a project full of real assets: if the template demands tables of numbers the tool allowlist cannot produce, the only way to complete it is to invent them.


Insufficient input — check this before producing any report

If the inputs this skill needs do not exist, the answer is "could not run" — not a filled-in report. Check first, and stop if the check fails.

  1. List the inputs this skill reads (data files, prior reports, profiler output, test results, registries, source code).
  2. For each, record FOUND or ABSENT — not "assumed present".
  3. If any input required for a section is ABSENT, that section is NOT ASSESSED — NO DATA. Do not estimate it, do not infer it from an adjacent artifact, and do not leave a mandated cell to be filled by whoever reads the template next.
  4. If every required input is ABSENT, stop and report NOT ASSESSED — NO DATA as the whole verdict, naming what was missing and which skill produces it.

A verdict of NOT ASSESSED is a success. It is the correct, useful answer to "what does the data say?" when there is no data. The failure mode this prevents is specific and has been observed in practice: report templates whose verdict enum had no "could not run" state produced false clean passes — an asset audit returning COMPLIANT on a project with no assets and no standards, and a performance profile reporting ">99% headroom against a 16.67ms budget" with zero profiler data and no budget ever set.

Absence of evidence is never evidence of absence. A scan that finds no matches because there are no files to scan has not verified anything. Say which of the two happened — a reader cannot tell from a green result.


Phase 1: Read Standards

Read the art bible's Asset Standards section (design/art/art-bible.md) and any asset standards in the relevant design docs — size budgets and format rules come from there. The naming patterns are the ones in Phase 3 below, unless the art bible states its own.

If neither states a size budget — or there is no art bible — the Size section is NOT ASSESSED — no size budget set, and the report names /art-bible, whose Asset Standards section sets budgets, formats and the naming convention.


Phase 2: Scan Asset Directories

Assets live under the engine's asset root: assets/ on Godot, Assets/ on Unity, Content/ on Unreal. Resolve the engine and its code root per .claude/docs/code-root-resolution.md; that code root is the one Phase 3's orphan and missing-asset searches read. If it is unresolved, stop: NOT ASSESSED — engine unresolved, naming /setup-engine.

Scan the asset root using Glob:

  • Godot — assets/art/**/*, assets/audio/**/*, assets/vfx/**/*, assets/shaders/**/*, assets/data/**/*
  • Unity — Assets/**/*, leaving out scripts (*.cs, *.asmdef) and *.meta files
  • Unreal — Content/**/*.uasset and Content/**/*.umap

The files matched are Total assets scanned. If there are none, the checks on scanned files — Naming, Size, Format, Orphaned — are NOT ASSESSED — no assets under <asset root>; the missing-asset search still runs.


Phase 3: Run Compliance Checks

Naming conventions:

  • Art: [category]_[name]_[variant]_[size].[ext]
  • Audio: [category]_[context]_[name]_[variant].[ext]
  • All files must be lowercase with underscores

These are Godot's conventions. Unity and Unreal name assets in PascalCase, so on those engines check names only against a naming rule the art bible states; with none, Naming is NOT ASSESSED — no naming rule for <engine> (name /art-bible).

File standards:

  • Textures: Power-of-two dimensions, correct format (PNG for UI, compressed for 3D), within size budget
  • Audio: Correct sample rate, format (OGG for SFX, OGG/MP3 for music), within duration limits. file reports an audio file's format and sample rate but not its length, and no pre-approved tool here does; a duration budget is therefore NOT ASSESSED — duration not measurable here, naming the files it covers.
  • Data: Valid JSON/YAML, schema-compliant

On Unreal an asset file (.uasset, .umap) does not keep its source file's format or dimensions, so Format is NOT ASSESSED there; its size is still measured.

Orphaned assets: Search the code root for references to each asset file. Flag any with no references.

Missing assets: Search the code root for asset references and verify the files exist.

Both searches need code: if the code root holds no source files, Orphaned and Missing are NOT ASSESSED — no code to search. On Unity and Unreal most asset references live in scenes, prefabs and other assets rather than code, so an asset no code names may still be in use: Orphaned is NOT ASSESSED there.


Phase 4: Output Audit Report

markdown
# Asset Audit Report -- [Category] -- [Date]

## Summary
- **Total assets scanned**: [N]
- **Naming violations**: [N]
- **Size violations**: [N]
- **Format violations**: [N]
- **Orphaned assets**: [N]
- **Missing assets**: [N]
- **Sections not assessed**: [none | each section and why]

## Naming Violations
| File | Expected Pattern | Issue |
|------|-----------------|-------|

## Size Violations
| File | Budget | Actual | Overage |
|------|--------|--------|---------|

## Format Violations
| File | Expected Format | Actual Format |
|------|----------------|---------------|

## Orphaned Assets (no code references found)
| File | Last Modified | Size | Recommendation |
|------|-------------|------|---------------|

## Missing Assets (referenced but not found)
| Reference Location | Expected Path |
|-------------------|---------------|

## Recommendations
[Prioritized list of fixes, one per violation, each naming the change — the
target resolution or compression for a size violation, the corrected name for a
naming violation, the target format for a format violation]

## Verdict: [NOT ASSESSED / COMPLIANT / WARNINGS / NON-COMPLIANT]

Choose the verdict by the findings, first match wins:

  • NON-COMPLIANT — any size violation, or any asset that code references but that does not exist
  • WARNINGS — only naming, format or orphaned-asset findings
  • NOT ASSESSED — the audit did not cover its scope: no data at all (the path above), zero assets scanned, or any section NOT ASSESSED — name which. It ranks below the two finding verdicts, because a measured violation is more actionable than a gap, and above COMPLIANT
  • COMPLIANT — at least one asset scanned, every section assessed, no findings

This skill is read-only — it produces a report but does not write files.


Phase 5: Next Steps

  • Fix naming violations using the Phase 3 patterns (or the art bible's, where it states its own).
  • If standards were missing, run /art-bible to write its Asset Standards section.
  • Delete confirmed orphaned assets after manual review.
  • Run /content-audit to cross-check asset counts against GDD-specified requirements.

Frequently asked questions

What does the Asset Audit AI skill do?

Audit assets against naming conventions, file size budgets, format standards. Finds orphaned assets, missing references.

Why use Asset Audit on TypingMind?

Because you install it once and use it with any model. Asset Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Asset Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Donchitos/Claude-Code-Game-Studios/tree/main/.claude/skills/asset-audit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Asset Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Asset Audit?

As many as you like. As long as a model supports skills, you can use Asset Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Asset Audit AI skill free?

Yes. It is published on GitHub by Donchitos under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇