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scenario-textures — Claude Code skill: what it does, how to install

Orchestrates tileable texture generation, repeat-safe upscaling, and PBR material extraction via the Scenario MCP. Useful when preparing 2D surfaces and 3D mesh materials for game engines.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add scenario-labs/skills --skill scenario-textures -a claude-code
Open on GitHub

What scenario-textures does

This skill directs tileable texture and material workflows through the Scenario MCP. Because model availability evolves across teams, the agent avoids hardcoded model IDs. It discovers models at runtime using recommend with the user's prompt or search by name, then inspects inputs via model_schema_get. You can price any batch beforehand by running model_run with dry_run=true.

Generations support repeat tiling with seam inpainting via eraseSeam, along with up to 10 style reference images. For PBR map extraction from flat surfaces, the workflow routes to models like model_patina to produce normal, metallic, height, and roughness maps. The roughness map returns tagged as smoothness. Check your shader conventions before wiring the channel into your material graph.

Texture upscaling uses dedicated models that preserve tiling from 2x to 8x. Standard image upscalers break the tile repeat. If a task requires retexturing an entire 3D mesh, the workflow hands off execution to sibling skills scenario-3d and scenario-meshy.

What it helps with

  • generate tileable textures from text prompts or reference images
  • extract PBR texture maps from flat surface images
  • upscale textures from 2x to 8x without breaking repeat boundaries
  • remove seam artifacts across texture edges using eraseSeam
  • price batch texture runs in advance using dry_run

Example prompts for the agent

  • Generate a tileable weathered red brick texture at 1024x1024 with eraseSeam enabled
  • Extract PBR maps from this stone wall image using the Patina model
  • Upscale this floor texture by 2x without breaking the tile repeat

How to install scenario-textures

1Skills CLI (Vercel)

npx skills add scenario-labs/skills --skill scenario-textures -a claude-code

2Manually: put the files in place

~/.claude/skills/scenario-textures/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/scenario-textures/

Step by step, with commands for each platform: How to install skills in Claude Code: five ways

Questions about scenario-textures

How to install scenario-textures in Claude Code?

Run npx skills add scenario-labs/skills --skill scenario-textures -a claude-code. The skill file will be placed in ~/.claude/skills/scenario-textures/SKILL.md.

What does scenario-textures do?

It orchestrates calls to Scenario MCP for generating tileable textures, inpainting seams, extracting PBR maps, and upscaling. The skill finds compatible models dynamically and validates input schemas before execution.

What dependencies are required for scenario-textures?

It requires access to Scenario MCP and the core scenario skill for connection handling. Retexturing full 3D meshes requires sibling skills scenario-3d or scenario-meshy.

Source text

SKILL.md · MIT
---
name: scenario-textures
description: "Use when a task involves game textures or materials through the Scenario MCP: seamless or tileable textures, themed texture packs (brick, wood, stone, floors, hand-painted), PBR materials (albedo, metallic, roughness, normal) on 3D assets, retexturing a mesh, material iteration from reference images, texture upscaling that must preserve tiling, or sizing textures for game engines. Keywords: seamless texture, tileable, PBR, material, retexture, texture upscale, surface."
license: MIT
---

# Scenario texture and material workflows

## Overview

Scenario generates seamless, tileable textures from text or reference images, upscales them without
breaking the tile, and applies PBR materials when texturing 3D meshes. Model availability differs
per team and evolves, so always discover models at run time instead of hardcoding IDs: `recommend`
with the need in the user's own words for a capability, `search` for a member known by name.

Connection and the core generation loop: see the `scenario` skill in this repo. 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

| Step                | Tool                                              | Notes                                                                                                                                                           |
| ------------------- | ------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Find texture models | `recommend` with the need in the user's own words | `capability` is `txt2img` or `img2img` with the texture in `prompt` (the catalog tags texture models `txt2img_texture`, `img2img_texture`); `search` for a name |
| Inspect inputs      | `model_schema_get`                                | Always call before `model_run`                                                                                                                                  |
| Generate            | `model_run`                                       | `dry_run=true` prices a batch first                                                                                                                             |
| Wait                | `jobs_wait`                                       | Re-call with `pending_job_ids`                                                                                                                                  |
| View and save       | `asset_display`, then `asset_download`            | Download for engine import                                                                                                                                      |
| Upscale             | `model_run` on a texture upscaler                 | 2x to 8x, tiling preserved                                                                                                                                      |

## What live search confirmed at authoring time (examples to re-discover, not constants)

- Seamless generation: `model_scenario-texture` (Scenario Texture) takes a prompt (a tileable hint
  is appended automatically), `width`/`height` from 16 to 3840 in multiples of 16, `quality`,
  `seed`, up to 10 `referenceImages` for style, and `eraseSeam` (off by default) with
  `overlap`/`featherRadius` to inpaint away both seam axes.
- Themed texture LoRAs (Flux.1 LoRA, tag `sc:texture`): floors, marble, concrete, stone walls, wood
  boards, brick, terracotta, hand-painted, cybernetic, realistic textures. They expose dedicated
  texture capabilities (`txt2img_texture`, `img2img_texture`, `controlnet_texture`).
- Tiling-safe upscaling: `model_sc-upscale-flux-texture` (Scenario Texture Upscale), `upscaleFactor`
  2 (the minimum) to 8, presets `precise`/`balanced`/`creative` riding the same `strength` and
  controlnet sliders the schema exposes. It re-renders, so expect small tonal drift: `precise` with
  low strength minimizes it, and the result is compared against the source before shipping.
- Material-look conversion: `model_sc-texture-converter` (Texture Converter) turns a flat image into
  a surface material using `raised`, `shiny`, `polished`, `angular` sliders and an `invert` relief
  toggle.
- PBR maps come from two different routes. For a flat texture, 2D map extractors (`recommend`,
  `capability="img2img"`, with the user's words about extracting maps from a flat texture; `search`
  only for one already known by name) return a full set in one img2img call: `model_patina` (PATINA
  Image to Maps) outputs base color, normal, roughness, metalness, and height, each as its own image
  asset whose `metadata.type` names it (`texture-albedo`, `texture-normal`, `texture-smoothness`,
  `texture-metallic`, `texture-height`) in the order requested; the roughness request comes back
  labeled smoothness, so confirm the convention before wiring it. `model_patina-material` tiles a
  PBR material straight from a prompt. For a mesh, 3D texturing and image-to-3D models emit the maps
  instead (Tripo 3.0 Texturing, Tencent Texture Edit, Meshy 7 Retexture); enable the PBR toggle
  found via `model_schema_get`. Retexturing a full mesh is a 3D-to-3D pipeline: see `scenario-3d`,
  and `scenario-meshy` for the Meshy retexture contract.

## Worked example: seamless brick, iterated then upscaled

1. `recommend` with the user's own words as `prompt` ("seamless tileable weathered brick"), pick the
   seamless generator (e.g. `model_scenario-texture`).
2. `model_schema_get` `model_id="model_scenario-texture"`.
3. `model_run` with
   `parameters={"prompt": "weathered red brick wall, moss in the mortar joints", "width": 1024, "height": 1024, "eraseSeam": true, "seed": 42}`.
   For a themed pack, price the batch with `dry_run=true` first, then launch the runs with
   `wait=false`.
4. `jobs_wait` with `job_ids=["job_..."]` (the ids returned by `model_run`). A ~180s timeout is not
   an error: re-call with the returned `pending_job_ids` as `job_ids`, never a second `model_run`.
   Then `asset_display` the output asset.
5. Iterate: rerun with the same `seed` and an edited prompt, or add `referenceImages=["asset_..."]`
   to lock a style.
6. Upscale: `recommend` with `capability="img2img"` and the user's own words as `prompt` ("upscale
   this texture without breaking the tile"), hold the pick to tiling preservation (a generic
   upscaler breaks the repeat), `model_schema_get` it, then `model_run` with the image and the
   factor and preset fields the schema names (at authoring time the texture upscaler took
   `upscaleFactor: 2` and `preset: "precise"`), raising the factor only deliberately: cost follows
   output pixels, and this leg can only be `dry_run`-priced once its input asset exists, so a
   two-step chain is never priced up front.
7. Verify tiling at no cost: the saved PNG's left column against its right and top row against
   bottom should differ no more than neighboring interior columns do, and a 2x2 self-tile proof
   sheet shows any seam instantly.
8. `asset_download` the final asset for engine import.

## Common mistakes

- Skipping `model_schema_get`: parameter names differ per model and most models reject an empty
  payload.
- Using a generic upscaler on a tileable texture: it breaks the repeat at the seams. Use the
  texture-specific upscaler, which preserves tiling.
- Generating huge sizes directly: generate near 1024, then upscale 2x to 8x. Generation dimensions
  cap at 3840.
- Routing a flat texture through a 3D texturing model just to get PBR maps: the 2D map extractors do
  that in one img2img call, and the 3D models are for meshes.
- Ignoring engine sizing: engines expect square power-of-two textures (the seamless generator
  defaults to 1024x1024, 1:1). The generator accepts any multiple of 16, so choose 1024 or 2048
  deliberately.
- Hardcoding model IDs: availability differs per team. Re-discover each session.

© scenario-labs · MIT · scenario-labs/skills

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