build-rigged-game-assets

build-rigged-game-assets is a skill for Codex from devinilabs/pro-skill. It costs 134 tokens per session (1,587 once invoked), scanned A, a copy of build-rigged-game-assets, MIT.

A workflow for creating or checking complete rigged 3D game characters and monsters, including a model, skeleton, animations, equipment, collisions, runtime files, and catalogue information. Rigging connects a 3D model to a skeleton so it can move in a game.

In plain words
What is it for?
Use it to import or create a playable character or monster, prepare optimized game files, connect equipment and collision behavior, and validate the accompanying asset manifest and review media.
Why use it?
It prevents an asset from being treated as finished when only the model exists or when it has not been tested in the game. It also checks that the required files and asset details are present.

Skill for Codex

Written for Codex: agents/openai.yaml present.

Good fit Use it to import or create a playable character or monster, prepare optimized game files, connect equipment and collision behavior, and validate the accompanying asset manifest and review media.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/devinilabs/pro-skill/build-rigged-game-assets
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.

Any agent
npx skills add devinilabs/pro-skill --skill build-rigged-game-assets
Clone the repo
git clone --depth 1 https://github.com/devinilabs/pro-skill

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for build-rigged-game-assets

README.md
[![agentmods](https://agentmods.dev/badge/skills/devinilabs/pro-skill/build-rigged-game-assets/github.svg)](https://agentmods.dev/skills/devinilabs/pro-skill/build-rigged-game-assets)
Your own site
<a href="https://agentmods.dev/skills/devinilabs/pro-skill/build-rigged-game-assets"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/build-rigged-game-assets/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for build-rigged-game-assets

Your own site · 80×15
<a href="https://agentmods.dev/skills/devinilabs/pro-skill/build-rigged-game-assets"><img src="https://agentmods.dev/badge/skills/devinilabs/pro-skill/build-rigged-game-assets.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 134 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,587 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod 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 5.1 $0.00134 $0.01587
Opus 5 $0.00067 $0.00794
Sonnet 5 $0.00027 $0.00317
Haiku 4.5 $0.00013 $0.00159

Measured 10d ago against content hash 093ab5940d12, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

build-rigged-game-assets 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 10d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/validate_asset_manifest.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.

Origin

This is a copy

100% identical to build-rigged-game-assets — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

agent-skills/game-development/build-rigged-game-assets/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Build Rigged Game Assets

Build one truthful actor package from source reference through gameplay and catalog proof.

Establish the contract first

Inspect repository truth before generating or editing files:

  • Locate the source image/model, runtime loader, skeleton conventions, action API, equipment system, collision system, catalog schema, review routes, budgets, and tests.
  • Classify the actor as character or monster.
  • Classify delivery as catalog-only, review-only, or runtime. Do not call an asset implemented until gameplay loads it.
  • Preserve immutable source artifacts separately from optimized runtime files.
  • Decide target formats before using a credit-bearing generator.

Copy the matching template from assets/, fill it in, and keep it beside the implementation or in the project’s asset metadata location:

  • character-asset-manifest.template.json
  • monster-asset-manifest.template.json

Run scripts/validate_asset_manifest.py <manifest> before building. Re-run with --root <repo> for shipped-file checks and --require-verified only after every acceptance check has actually passed.

Read references/requirements.md before creating the model, rig, actions, equipment, sockets, or collision data. Read references/catalog-and-testing.md when adding the catalog card, inspector, moveset route, telemetry, or release tests.

Build the common actor package

  1. Preserve the source.
    • Record reference images, source tasks, imported files, licenses, generator/model, and material provenance.
    • Never overwrite the high-detail source with the runtime optimization.
  2. Produce the main model.
    • Normalize scale, Y-up, forward axis, pivot, ground contact, materials, textures, and triangle budget.
    • Ground from feet or authored contact sockets, never a weapon tip, cloth tail, shadow, or VFX.
    • Remove isolated triangles, non-manifold fragments, duplicate surfaces, hidden generator debris, and unused nodes.
  3. Build one stable rig.
    • Name root, hips/center mass, head, limbs, feet, and attachment sockets explicitly.
    • Keep at most four normalized skin influences per vertex unless the engine contract says otherwise.
    • Preserve a deterministic bind pose, finite transforms, positive usable scale, and compatible skeleton identity across every clip.
  4. Build the action library.
    • Give every clip a stable id, semantic role, loop policy, root-motion policy, duration, contact events, and source.
    • Prefer animation-only GLBs for separate clips. They must not smuggle duplicate meshes, materials, or textures.
    • Make non-looping actions restartable and return to the intended locomotion/idle state.
  5. Build runtime integration.
    • Use one asset-specific loader/factory with disposal for geometry, materials, textures, mixers, events, observers, renderers, and animation frames.
    • Publish source, model, rig, socket, action, equipment, collider, triangle, material, and status metadata.
    • Keep a truthful rollback path when replacing a shipped runtime asset.

Read the full file on GitHub · 111 lines

Files

What ships with it

6 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. 10d ago First seen · 111 lines · 134 tokens per session scan A 093ab5940d12

Subscribe to this mod's changes

build-rigged-game-assets is a skill published in the GitHub repository devinilabs/pro-skill (24 stars, last pushed 28d ago), licensed MIT. It adds 134 tokens to every session and 1,587 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to build-rigged-game-assets, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories