Agent skill

Scenario Skyboxes

by scenario-labs in scenario-labs/skills

Install Scenario Skyboxes

skills CLI

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

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

GitHub CLI

$ gh skill install scenario-labs/skills scenario-skyboxes --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-skyboxes .claude/skills/scenario-skyboxes && 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-skyboxes" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-skyboxes into .claude/skills/scenario-skyboxes/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-skyboxes", 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-skyboxes

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-skyboxes -a codex

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

GitHub CLI

$ gh skill install scenario-labs/skills scenario-skyboxes --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-skyboxes .agents/skills/scenario-skyboxes && 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-skyboxes" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-skyboxes into .agents/skills/scenario-skyboxes/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-skyboxes", 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-skyboxes -a cursor

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

GitHub CLI

$ gh skill install scenario-labs/skills scenario-skyboxes --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-skyboxes .cursor/skills/scenario-skyboxes && 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-skyboxes" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-skyboxes into .cursor/skills/scenario-skyboxes/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-skyboxes", 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-skyboxes

--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-skyboxes -a gemini-cli

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

GitHub CLI

$ gh skill install scenario-labs/skills scenario-skyboxes --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-skyboxes .gemini/skills/scenario-skyboxes && 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-skyboxes" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-skyboxes into .gemini/skills/scenario-skyboxes/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-skyboxes", 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-skyboxes

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-skyboxes -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-skyboxes .github/skills/scenario-skyboxes && 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-skyboxes" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-skyboxes into .github/skills/scenario-skyboxes/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-skyboxes", 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-skyboxes -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-skyboxes --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-skyboxes .opencode/skills/scenario-skyboxes && 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-skyboxes" agent skill from https://github.com/scenario-labs/skills/tree/main/skills/scenario-skyboxes into .opencode/skills/scenario-skyboxes/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "scenario-skyboxes", 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-skyboxes
GitHub stars: 931
Token cost: ~1.6k tokens
SKILL.md length: 736 words
Files: 1
Skills in repo: 143
Repo updated: Oct 8, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Works in 7 steps: search with target="models",… → model_schema_get for that model. Expect… → model_run with parameters={"prompt":… → …
A task involves generating
SKILL.md covers Overview, Quick reference, Worked example: generate,… and Common mistakes
Calls npx

What it does

Scenario Skyboxes is an agent skill from scenario-labs/skills. Use when a task involves generating or iterating on skyboxes, 360 panoramas, equirectangular images, environment maps, HDRI-style backdrops, or VR backdrops through the Scenario MCP. Triggers include text-to-skybox, turning a photo into a 360 environment, restyling a panorama's mood, upscaling a skybox without breaking the seam wrap, or exporting equirectangular or cubemap layouts for game engines such as Unity, Unreal, or Godot.

Its SKILL.md is about 1.6k 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 development. It works with Model Context Protocol and Godot. 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

A task involves generating
Iterating on skyboxes
Equirectangular images
Environment maps

Example prompts

“/scenario-skyboxes”

Requirements

Node.js

Workflow steps

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

search with target="models", query="skybox", public=true. Pick a text-to-skybox model, for example model_scenario-skybox-flux.
model_schema_get for that model. Expect fields like prompt, style, negativePrompt, image, strength, numOutputs, geometryEnforcement, seed…
model_run with parameters={"prompt": "ancient pine forest at dawn, mist between trunks, god rays", "style": "cinematic", "numOutputs": 2}…
jobs_wait with job_ids=[the returned job_id]. Its ~180s timeout is not an error: re-call with the returned pending_job_ids as job_ids…
Iterate on mood: copy the seed from the best result and change only style (cinematic, oil-painting, cyberpunk, and more). To keep…
Export: run model_sc-upscale-flux-skybox with image=asset_id and the smallest upscaleFactor that reaches target (the upscale can cost…
Verify the seam at no cost: compare the saved PNG's leftmost and rightmost pixel columns; on a seamless panorama they differ by near zero…

What it can do on your machine

Read from SKILL.md and the folder at commit 91caa01. 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 Skyboxes loads about 1.6k tokens when it runs. Until then it costs about 113 tokens; SKILL.md has 736 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~113
When it runs · the whole SKILL.md, loaded when a task matches: ~1.6k

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 91caa01, republished under its MIT licence (© scenario-labs). 736 words, ~1,552 tokens.

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

name: scenario-skyboxes
description: Use when a task involves generating or iterating on skyboxes, 360 panoramas, equirectangular images, environment maps, HDRI-style backdrops, or VR backdrops through the Scenario MCP. Triggers include text-to-skybox, turning a photo into a 360 environment, restyling a panorama's mood, upscaling a skybox without breaking the seam wrap, or exporting equirectangular or cubemap layouts for game engines such as Unity, Unreal, or Godot.
license: MIT

Scenario Skyboxes and 360 Panoramas

Overview

Scenario hosts dedicated skybox models that produce seamless equirectangular 360 panoramas, plus a seam-preserving skybox upscaler. Always generate with a skybox-specific model rather than a generic image model: these enforce the seam continuity and pole geometry that ordinary text-to-image output lacks.

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	Purpose
1	`search` (target="models", query="skybox", public=true)	Discover current skybox models
2	`model_schema_get`	Exact parameter contract for the chosen model
3	`model_run`	`dry_run=true` to price; `wait=false` to batch
4	`jobs_wait`	On timeout re-call with `pending_job_ids`
5	`asset_display` / `asset_download`	Review inline, then save the file

Model IDs and the parameter facts below were live search hits at authoring time. Re-discover them each time: availability differs per team and evolves.

model_scenario-skybox-flux: text to 360 panorama, a style preset enum (count drifts; read it from the schema), automatic seam and pole correction, optional reference image with a strength slider.
model_scenario-skybox-gpt: text to 360 panorama guided by up to 10 reference images, quality presets, width and height up to 3840 px.
model_hunyuan-world-image-to-skybox: one photo of a place to a seamless 360 skybox.
model_sc-upscale-flux-skybox: 2x to 8x skybox upscale that preserves the seamless wrap.

Worked example: generate, iterate, export

Example: a stylized forest skybox for a game scene.

search with target="models", query="skybox", public=true. Pick a text-to-skybox model, for example model_scenario-skybox-flux.
model_schema_get for that model. Expect fields like prompt, style, negativePrompt, image, strength, numOutputs, geometryEnforcement, seed. negativePrompt is inert unless negativePromptStrength is above 0.
model_run with parameters={"prompt": "ancient pine forest at dawn, mist between trunks, god rays", "style": "cinematic", "numOutputs": 2}. Take style preset names from the schema response. dry_run=true first prices the run; launch with wait=false.
jobs_wait with job_ids=[the returned job_id]. Its ~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 each output.
Iterate on mood: copy the seed from the best result and change only style (cinematic, oil-painting, cyberpunk, and more). To keep composition while shifting look, pass the favorite as image with low strength (0.2 to 0.4). To steer mood from concept art instead, switch to model_scenario-skybox-gpt and pass referenceImages.
Export: run model_sc-upscale-flux-skybox with image=asset_id and the smallest upscaleFactor that reaches target (the upscale can cost several times the generation, and its dry_run can only run once the input asset exists, so the chain cannot be priced up front). baseModel defaults to FLUX.1-dev (stylized); a Krea-based realism option exists, and strength defaults to 0.6, which invents detail: lower it when the goal is the same panorama at higher resolution. Read the exact allowed values from model_schema_get before switching. Then asset_download the final asset.
Verify the seam at no cost: compare the saved PNG's leftmost and rightmost pixel columns; on a seamless panorama they differ by near zero while columns a quarter-turn apart differ by an order of magnitude more.

Show full SKILL.md (217 more words)Show less

Engine format notes: Skybox Flux outputs equirectangular panoramas; keep the default sizing (1536x768 at authoring time) and read the real dimensions off the returned asset rather than assuming them. Skybox GPT's catalog lists equirectangular 2:1 plus cubemap strip 6:1 and cubemap cross 4:3 layouts, but its schema exposes only width and height, so confirm the layout contract with model_schema_get before relying on a cubemap layout. Beyond flat backdrops, the same search surfaces model_hunyuan-world-skybox-to-splat, and a separate search (query="world") finds the Marble world models; both turn a finished panorama into a navigable 3D Gaussian splat scene, the pipeline the scenario-3d-worlds skill teaches end to end.

Common mistakes

Prompting a generic image model for a "360 panorama": edges will not wrap and poles smear. Use a dedicated skybox model.
Upscaling with a generic upscaler: it breaks continuity at the wrap seam. Use the skybox upscaler.
Hardcoding model IDs in scripts or docs: re-discover with search; the catalog changes.
Fighting seam or pole distortion through prompt wording on Skybox Flux: raise geometryEnforcement above 0 instead, and only when distortion is actually visible.
Requesting a non 2:1 width to height ratio on Skybox GPT while expecting equirectangular output: keep 2:1 (for example 2048x1024) for correct 360 viewing.
Skipping model_schema_get: skybox models carry model-specific fields (style, geometryEnforcement, quality) that generic assumptions miss.

Files

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

Open the folder on GitHubat commit 91caa01

Compare with similar skills

Scenario Skyboxes 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 Skyboxes compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Scenario Skyboxes this skillscenario-labs/skills	931	—	~1.6k	Automated safety check: Pass	MIT	yesterday
MCP DriverRandallLiuXin/GodotMaker	550	1 repos	~1.1k	Automated safety check: Pass	Custom licence	22 days ago
Godotvalkor-ai/loom	1.2k	—	~765	Automated safety check: Pass	Apache-2.0	3 days ago
Game Assetsglifxyz/glif-mcp-server	212	—	~831	Automated safety check: Pass	MIT	yesterday
Studiowith-pebbly/aseprite-ai-artist	206	—	~4k	Automated safety check: Pass	MIT	2 days ago
Godot Gdscript Patterns925236118/AlphaAgent	103	10 repos	~5k	Automated safety check: Pass	MIT	yesterday

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Works with

Questions about Scenario Skyboxes

What does Scenario Skyboxes do?

A skill your agent uses when a task involves generating or iterating on skyboxes, 360 panoramas, equirectangular images, environment maps, HDRI-style backdrops, or VR backdrops through the Scenario…. Scenario Skyboxes is an agent skill from scenario-labs/skills. Use when a task involves generating or iterating on skyboxes, 360 panoramas, equirectangular images, environment maps, HDRI-style backdrops, or VR backdrops through the Scenario MCP.

When should I use Scenario Skyboxes?

Scenario Skyboxes fits situations like: A task involves generating; iterating on skyboxes; equirectangular images; environment maps.

How do I install Scenario Skyboxes in Claude Code?

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

How do I install Scenario Skyboxes in Codex?

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

Can I use Scenario Skyboxes 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-skyboxes -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-skyboxes, .gemini/skills/scenario-skyboxes, .github/skills/scenario-skyboxes and .opencode/skills/scenario-skyboxes in your project.

What does Scenario Skyboxes need to run?

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

Does Scenario Skyboxes 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 Skyboxes 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 Skyboxes use?

Scenario Skyboxes 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 Skyboxes use?

About 1.6k tokens (SKILL.md is roughly 6.2k 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 Skyboxes?

Skills that share tags, products or a category with Scenario Skyboxes: MCP Driver (RandallLiuXin/GodotMaker, 550 stars), Godot (valkor-ai/loom, 1.2k stars), Game Assets (glifxyz/glif-mcp-server, 212 stars) and Studio (with-pebbly/aseprite-ai-artist, 206 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Scenario Skyboxes?

scenario-labs (a GitHub organization) maintains it in scenario-labs/skills, which has 931 GitHub stars. The repository holds 143 skills in this directory. The repository was last updated on October 8, 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 Skyboxes

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 Skyboxes and 360 Panoramas

Overview

Quick reference

Worked example: generate, iterate, export

Common mistakes

Files

Compare with similar skills

Similar skills

More from scenario-labs/skills

Related

Questions about Scenario Skyboxes