scenario-meshy

scenario-meshy is a skill for Claude Code from scenario-labs/skills. It costs 131 tokens per session (1,660 once invoked), scanned A, original, MIT.

An add-on for creating and refining 3D assets with Meshy models through Scenario, an AI media service. A 3D asset is a digital object that can be viewed, imported into games, or used in other 3D software.

In plain words
What is it for?
Use it to turn one or several images or text into a 3D model, retexture a GLB file, reduce its polygon count, unwrap its UVs, rig a humanoid character, and apply an animation.
Why use it?
It organizes separate steps such as generating a model, improving its mesh, preparing its surface, and adding movement. Each step can use the 3D asset produced by the previous step.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the 14.-3d-model-families plugin — 4 skills shipped together

Good fit Use it to turn one or several images or text into a 3D model, retexture a GLB file, reduce its polygon count, unwrap its UVs, rig a humanoid character, and apply an animation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/scenario-labs/skills/scenario-meshy
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 scenario-labs/skills --skill scenario-meshy
Clone the repo
git clone --depth 1 https://github.com/scenario-labs/skills

Made for: Claude Code.

Or install 14.-3d-model-families, the plugin that ships this one along with the rest of its 4 skills.

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 scenario-meshy

README.md
[![agentmods](https://agentmods.dev/badge/skills/scenario-labs/skills/scenario-meshy/github.svg)](https://agentmods.dev/skills/scenario-labs/skills/scenario-meshy)
Your own site
<a href="https://agentmods.dev/skills/scenario-labs/skills/scenario-meshy"><img src="https://agentmods.dev/badge/skills/scenario-labs/skills/scenario-meshy/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 scenario-meshy

Your own site · 80×15
<a href="https://agentmods.dev/skills/scenario-labs/skills/scenario-meshy"><img src="https://agentmods.dev/badge/skills/scenario-labs/skills/scenario-meshy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 131 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,660 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 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 5.1 $0.00131 $0.01660
Opus 5 $0.00066 $0.00830
Sonnet 5 $0.00026 $0.00332
Haiku 4.5 $0.00013 $0.00166

Measured 11d ago against content hash 3a0301b84b01, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

scenario-meshy 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 11d ago.

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/scenario-meshy/SKILL.md · 59 lines

How it starts

The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Scenario Meshy 3D

Overview

Meshy on Scenario is a toolchain rather than one model: image-to-3D generators (Meshy 7 Image to 3D, Meshy 7 Multi Image to 3D, Meshy T2 Smart Topology), Meshy 6 Text-to-3D, and GLB-in, GLB-out utilities (Retexture, Remesh, UV Unwrap, Rigging, Animation). Work runs as a pipeline: generate a mesh, refine it, then rig or animate, each stage its own model_run whose model parameter takes the 3D asset id the previous stage returned. Discover members with search and treat model_schema_get as the contract: members disagree on defaults as basic as enablePbr (true on Image to 3D, false on Multi Image and Retexture at authoring time).

Connection and the core loop: see the scenario skill in this repo; model-agnostic 3D work (viewer, capture, engine import): 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

Members and their traps (names from the live schema, caps at authoring time):

Member Core input Watch for
7 Image to 3D image (1-4) ultraMode takes a single image only; raw mesh by default
7 Multi Image to 3D image (1-4, first = front view) remeshes in-run; savePreRemeshedModel keeps the raw GLB
T2 Smart Topology image (1-4) animation-ready topology; targetPolycount caps at 15,000
6 Text-to-3D prompt (600 chars) shouldRemesh off by default
Retexture model + one style input geometry untouched; keep inputs near 30K polys; enableOriginalUv
Remesh model targetPolycount 100 to 300,000, resizeHeight, originAt
UV Unwrap model rejects meshes above 44,000 faces; Remesh down first
Rigging model, heightMeters humanoid skeleton and skin weights
Animation model, actionId auto-rigs, then applies the clip

Read the full file on GitHub · 59 lines

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. 11d ago First seen · 59 lines · 131 tokens per session scan A 3a0301b84b01

Subscribe to this mod's changes

scenario-meshy is a skill published in the GitHub repository scenario-labs/skills (11 stars, last pushed today), licensed MIT. It adds 131 tokens to every session and 1,660 once invoked, about $0.0007 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 2026-08-31.