Agent skill

Scenario Rodin

by scenario-labs in scenario-labs/skills

Install Scenario Rodin

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-rodin -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-rodin --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/scenario-rodin .claude/skills/scenario-rodin && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "scenario-rodin" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-rodin into .claude/skills/scenario-rodin/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-rodin", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/scenario-labs/skills/tree/main/skills/scenario-rodin

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-rodin -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-rodin --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/scenario-rodin .agents/skills/scenario-rodin && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "scenario-rodin" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-rodin into .agents/skills/scenario-rodin/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-rodin", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-rodin -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-rodin --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/scenario-rodin .cursor/skills/scenario-rodin && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "scenario-rodin" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-rodin into .cursor/skills/scenario-rodin/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-rodin", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/scenario-labs/skills.git --path skills/scenario-rodin

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-rodin -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-rodin --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/scenario-rodin .gemini/skills/scenario-rodin && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "scenario-rodin" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-rodin into .gemini/skills/scenario-rodin/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-rodin", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-rodin

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-rodin -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/scenario-rodin .github/skills/scenario-rodin && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "scenario-rodin" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-rodin into .github/skills/scenario-rodin/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-rodin", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add scenario-labs/skills --skill scenario-rodin -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install scenario-labs/skills scenario-rodin --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/scenario-labs/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/scenario-rodin .opencode/skills/scenario-rodin && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "scenario-rodin" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-rodin into .opencode/skills/scenario-rodin/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-rodin", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: scenario-rodin
GitHub stars: 946
Token cost: ~1.4k tokens
SKILL.md length: 699 words
Files: 1
Skills in repo: 146
Repo updated: Oct 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Works in 6 steps: search with target="models",… → model_schema_get with that id: enums,… → upload_asset the turnaround stills (see… → …
Generating 3D assets with Rodin Hyper3D models on Scenario via MCP: image-to-3D from up to five multiview stills
SKILL.md covers Overview, Quick reference, The lane decides the dialect and Bang! wants a finished mesh, plus 2 more sections
Calls npx

What it does

Scenario Rodin is an agent skill from scenario-labs/skills. Use when generating 3D assets with Rodin Hyper3D models on Scenario via MCP: image-to-3D from up to five multiview stills, text-to-3D from a prompt, fast prototyping versus full quality tiers, quad or triangle topology, PBR materials, HighPack 4K textures, T-pose or A-pose characters for rigging, or splitting a finished mesh into parts and retexturing it with Bang!. Keywords: Rodin Gen-2.5, Hyper3D, Deemos, image to 3D, text to 3D, part segmentation, texture delight.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Game Development, covering Game assets and audio and Prototyping. It works with Model Context Protocol. The repository describes itself as: Get production-ready images, video, audio, and 3D from any AI agent: skills that pick the right model, price before spending, and keep characters and brands consistent through… The licence is MIT.

When your agent uses it

Generating 3D assets with Rodin Hyper3D models on Scenario via MCP: image-to-3D from up to five multiview stills
Text-to-3D from a prompt
Fast prototyping versus full quality tiers
Triangle topology

Example prompts

“/scenario-rodin”

Requirements

Node.js

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

search with target="models", query="rodin", public=true. Match capability to task (img23d here, txt23d for prompt-only, Fast for cheap…
model_schema_get with that id: enums, defaults, and caps before anything else.
upload_asset the turnaround stills (see the scenario skill) to get asset ids.
model_run with that model_id, dry_run=true, and parameters={"images": ["asset_front", "asset_side", "asset_back"], "prompt": "stylized…
Re-run with wait=false, then jobs_wait with the returned job id, re-called with pending_job_ids on timeout. Full-lane jobs take minutes; a…
asset_display the mesh, then asset_download for engine import (details in the scenario-3d skill).

What it can do on your machine

Read from SKILL.md and the folder at commit f6f8ab7. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- npx
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Scenario Rodin loads about 1.4k tokens when it runs. Until then it costs about 122 tokens; SKILL.md has 699 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~122
When it runs · the whole SKILL.md, loaded when a task matches: ~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from scenario-labs/skills at commit f6f8ab7, republished under its MIT licence (© scenario-labs). 699 words, ~1,395 tokens.

Download SKILL.mdSave it as .claude/skills/scenario-rodin/SKILL.md (or your agent's skills folder).

name: scenario-rodin
description: Use when generating 3D assets with Rodin Hyper3D models on Scenario via MCP: image-to-3D from up to five multiview stills, text-to-3D from a prompt, fast prototyping versus full quality tiers, quad or triangle topology, PBR materials, HighPack 4K textures, T-pose or A-pose characters for rigging, or splitting a finished mesh into parts and retexturing it with Bang!. Keywords: Rodin Gen-2.5, Hyper3D, Deemos, image to 3D, text to 3D, part segmentation, texture delight.
license: MIT

Scenario Rodin 3D

Overview

Rodin Hyper3D, Deemos Technology's 3D family on Scenario, picks its mode by member: image-to-3D and text-to-3D each ship as a full model and a Fast variant, and Bang! splits finished meshes into parts. Discover them with search and treat model_schema_get as the contract: the lanes agree on ideas and disagree on parameter names.

Connection and the core loop: see the scenario skill in this repo; model-agnostic 3D work: the scenario-3d skill. If a sibling skill named here is missing from your available skills, ask the user to install it (npx skills add scenario-labs/skills --skill <name>); unattended, proceed from tool schemas and flag the gap.

Quick reference

Pick the member by task:

Task	Member	Required inputs
Image to 3D (`img23d`)	Gen-2.5, or Fast	`images`
Text to 3D (`txt23d`)	Gen-2.5 Text to 3D, or Fast	`prompt`
Split and retexture (`3d23d`)	Bang!	`model` + `image`

images is an array even for one still (up to 5 at authoring time), every entry a view of one subject, never an alternative concept. Prompt is optional on the image members: left empty, Rodin writes one from the images. Shared generator knobs: qualityMeshOption (topology and poly budget in one enum string, "18K Quad"), material (PBR, Shaded, All, None), textureDelight (strips baked lighting), TAPose (true poses the character in T or A pose for rigging; the schema does not pick between them), seed (0 to 65535).

The lane decides the dialect

Full and Fast express the same ideas through different parameters, so a payload never moves between lanes unchanged. At authoring time the full lane's tier ran Gen-2.5-Extreme-Low through Gen-2.5-Extreme-High (Extreme High bills double the base rate), HighPack rode in addons as a string (on a Quad mesh it multiplies faces about 16 times), geometryInstructMode: "creative" loosened interpretation, isSymmetric steered symmetry, and isMicro took effect only on Extreme High. The Fast lane's tier stopped at Gen-2.5-Minimum, Gen-2.5-Extreme-Low, and Gen-2.5-Low for one fixed price, highPack was a boolean, enableCreativeMode added generative robustness without losing consistency, and meshes capped at 20K behind an Auto default. In both lanes HighPack means 4K textures plus high-poly geometry at extra cost: dry_run the exact payload before any batch. Text members drop the image-only switches (useOriginalAlpha, previewRender).

Bang! wants a finished mesh

Bang! is 3D-to-3D: it takes an existing 3D asset as model plus a reference image (both required at authoring time, prompt is optional guidance), splits the mesh into semantically meaningful parts, and regenerates each part's materials in the same pass. strength (2 to 12, default 5) sets how fine the split gets, higher splitting into more parts; material defaults to PBR here, not All; resolution "Basic" is 2K, "High" is 4K. At authoring time it ran several minutes and cost more per asset than a default generator run: dry_run it like any other member.

Show full SKILL.md (234 more words)Show less

Worked example: a rig-ready character from turnaround stills

search with target="models", query="rodin", public=true. Match capability to task (img23d here, txt23d for prompt-only, Fast for cheap drafts), e.g. model_rodin-hyper3d-v2-5 (a live hit at authoring time: re-discover each session).
model_schema_get with that id: enums, defaults, and caps before anything else.
upload_asset the turnaround stills (see the scenario skill) to get asset ids.
model_run with that model_id, dry_run=true, and parameters={"images": ["asset_front", "asset_side", "asset_back"], "prompt": "stylized adventurer, clean silhouette", "tier": "Gen-2.5-Medium", "qualityMeshOption": "18K Quad", "material": "PBR", "textureDelight": true, "TAPose": true}; re-estimate after any tier or HighPack change.
Re-run with wait=false, then jobs_wait with the returned job id, re-called with pending_job_ids on timeout. Full-lane jobs take minutes; a timeout is not a failure and never justifies a second model_run.
asset_display the mesh, then asset_download for engine import (details in the scenario-3d skill).

Common mistakes

A bare string in images: one still goes as ["asset_x"].
Carrying a payload across lanes: addons: "HighPack" versus boolean highPack, geometryInstructMode versus enableCreativeMode, disjoint tier enums.
Asking the Fast lane for Medium or High tiers or a 500K mesh: its enums stop at Low and 20K.
Setting isMicro below Extreme High on the full lane: it changes nothing.
Handing Bang! an image as model: model is a 3D asset; the image guides the regenerated textures.
Freeform enum strings: values are exact, "Gen-2.5-Medium", "18K Quad", not "medium" or "18k quad".

Files

Just SKILL.md in skills/scenario-rodin of scenario-labs/skills.

Open the folder on GitHubat commit f6f8ab7

Compare with similar skills

Scenario Rodin next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Scenario Rodin compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Scenario Rodin this skillscenario-labs/skills	946	—	~1.4k	Automated safety check: Pass	MIT	yesterday
Unreal Material and VFX Workflowflopperam/unreal-engine-mcp	1.1k	—	~927	Automated safety check: Pass	None	3 mo ago
Kiln Refine Assetinstruktlabs/kiln	255	—	~3.6k	Automated safety check: Pass	MIT	today
Fmodel Unpackpa001024/dna-builder	137	—	~2.6k	Automated safety check: Pass	MIT	yesterday
Kiln Author Assetinstruktlabs/kiln	255	—	~4k	Automated safety check: Pass	MIT	today
Kiln QA Assetinstruktlabs/kiln	255	—	~2.7k	Automated safety check: Pass	MIT	today

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Works with

Model Context Protocol

Questions about Scenario Rodin

What does Scenario Rodin do?

A skill your agent uses when generating 3D assets with Rodin Hyper3D models on Scenario via MCP: image-to-3D from up to five multiview stills, text-to-3D from a prompt, fast prototyping versus full…. Scenario Rodin is an agent skill from scenario-labs/skills. Use when generating 3D assets with Rodin Hyper3D models on Scenario via MCP: image-to-3D from up to five multiview stills, text-to-3D from a prompt, fast prototyping versus full quality tiers, quad or triangle topology, PBR materials, HighPack 4K textures, T-pose or A-pose characters for rigging, or splitting a finished mesh into parts and retexturing it with Bang!.

When should I use Scenario Rodin?

Scenario Rodin fits situations like: generating 3D assets with Rodin Hyper3D models on Scenario via MCP: image-to-3D from up to five multiview stills; text-to-3D from a prompt; fast prototyping versus full quality tiers; triangle topology.

How do I install Scenario Rodin in Claude Code?

Run `npx skills add scenario-labs/skills --skill scenario-rodin -a claude-code`. Or copy the skill folder (skills/scenario-rodin in scenario-labs/skills) into .claude/skills/scenario-rodin in your project. Claude Code loads it when a task matches its description.

How do I install Scenario Rodin in Codex?

Run `npx skills add scenario-labs/skills --skill scenario-rodin -a codex`. Or copy the skill folder (skills/scenario-rodin in scenario-labs/skills) into .agents/skills/scenario-rodin in your project. Codex loads it when a task matches its description.

Can I use Scenario Rodin in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add scenario-labs/skills --skill scenario-rodin -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/scenario-rodin, .gemini/skills/scenario-rodin, .github/skills/scenario-rodin and .opencode/skills/scenario-rodin in your project.

What does Scenario Rodin need to run?

Going by SKILL.md and its folder, Scenario Rodin needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Scenario Rodin access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Scenario Rodin safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Scenario Rodin use?

Scenario Rodin is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Scenario Rodin use?

About 1.4k tokens (SKILL.md is roughly 5.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Scenario Rodin?

Skills that share tags, products or a category with Scenario Rodin: Unreal Material and VFX Workflow (flopperam/unreal-engine-mcp, 1.1k stars), Kiln Refine Asset (instruktlabs/kiln, 255 stars), Fmodel Unpack (pa001024/dna-builder, 137 stars) and Kiln Author Asset (instruktlabs/kiln, 255 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scenario Rodin?

scenario-labs (a GitHub organization) maintains it in scenario-labs/skills, which has 946 GitHub stars. The repository holds 146 skills in this directory. The repository was last updated on October 10, 2026.

Source: scenario-labs/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Scenario Rodin

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Scenario Rodin 3D

Overview

Quick reference

The lane decides the dialect

Bang! wants a finished mesh

Worked example: a rig-ready character from turnaround stills

Common mistakes

Files

Compare with similar skills

Similar skills

More from scenario-labs/skills

Related

Questions about Scenario Rodin