Render Multiworld

OrganizationPopular

gooseworks-ai

render-multiworld

Assemble a silent, music-led 3-world product-tour ad — trim and hard-cut-concat the per-world WIDE-arrival + top-down-macro clips, composite the HTML/Playwright brand end card ("FIND YOUR DAILY." + handwritten scent labels + arrows) over an AI flat-lay background, and mux one music bed into a 720x1280 web master. FREE, deterministic assembly (Playwright + PIL/HTML + FFmpeg); the recipe supplies the config and gates the paid clip/background/music calls. Use for the multiworld-product-tour format.

Overview

Publisher	gooseworks-ai
Repository	`goose-skills`
Skill name	`render-multiworld`
Stars	1.2K
Forks	208
Bundled files	4
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by gooseworks-ai on GitHub. Read the source before you install it.

Installation

Install the Render Multiworld AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-multiworld

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git /tmp/goose-skills
mkdir -p .claude/skills
cp -r /tmp/goose-skills/skills/ads/capabilities/render-multiworld .claude/skills/render-multiworld

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Render Multiworld in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Render Multiworld on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Render Multiworld is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

render-multiworld

Assemble a silent, music-led "multi-world product tour" ad (≈27s, 9:16) — a tour of three distinct "third-place" worlds, one per product/scent, that lands on a Pinterest-style brand end card. Each world is a two-shot pair: a ~4.5s WIDE kinetic-calm ARRIVAL (the environment dominates, the bottle stays small) hard-cutting to a ~3.5s top-down MACRO product MOMENT (the sealed bottle nested with its botanical companion). Scent identity is carried by the world + botanical companion, not by bottle color. No VO, no captions in the scenes — one music bed carries the whole thing.

This capability is the FREE, deterministic assembler. The paid steps — the six per-world clips, the AI flat-lay end-card background, the ElevenLabs music bed — are separate capabilities (see the gap below for the clips); the recipe orchestrates and gates them.

Run

Trim clips (FFmpeg, FREE) — trim each per-world clip to its scene_grid[].duration_sec (arrival 4.5 / macro 3.5), re-encode to the master spec (720×1280, 24fps, yuv420p, scale+pad, audio stripped). Trimming the macro so the top-down portion dominates also hides any label misrender at the clip's upright tilt extreme.
End card (Playwright/HTML, FREE) — screenshot end_card.html over the AI flat-lay BACKGROUND, then FFmpeg-encode to a dwell_sec (3.0s) static clip. Headline ("FIND YOUR DAILY.", Inter 900), one handwritten Caveat scent label + hand-drawn SVG arrow per bottle, Playfair wordmark + URL. End-card text is HTML, NEVER AI-rendered — the AI step produces the background only.
Hard-cut concat (FFmpeg, FREE) — concat the six trimmed clips in scene order (S01 arrival → S02 macro → … → S06 macro) + the end-card clip. Hard cuts (no dissolves), normalized to one fps/codec first so concat-copy is safe.
Music mux + web encode (FFmpeg, FREE) — mux the single instrumental bed onto the silent concat with afade in/out + loudnorm I=-16:TP=-1.5:LRA=11, AAC 192k, clamped to 27.0s, explicit single-audio map so no silent scene-track leaks in → the H.264 (+ AAC) 720×1280 master.

Contract

Deterministic + FREE (Playwright + PIL/HTML + FFmpeg); no paid calls, no AI-rendered end-card text. Iterate the cut for free by re-running the assembly.
Silent, music-led — no VO, no captions during the scenes; on-screen text appears ONLY on the end card, HTML-composited.
Per world = WIDE arrival (bottle small, environment dominant) → top-down macro (product + botanical, no hands). Hard cuts between scenes; end card is a static hold with legible HTML text; music starts at t=0 and fades the tail.
Sealed-bottle rule is enforced at QC — trim/concat can't fix an open-cap or spraying clip; that's a re-roll (paid), not an assembly fix. Identity via world + botanical, never bottle color.
The template recipe (DB) supplies the per-brand config (worlds, palettes, botanicals, prompts, end-card copy, music mood); this capability is the generic assembler.

Gaps / routing notes

The six per-world clips need a Higgsfield-proxy capability that does not exist. The source molecule fires them through Higgsfield Marketing Studio (marketing_studio_video/product_showcase) grounded on imported product UUIDs, with the sealed-bottle safety block front-loaded on every prompt. create-video-fal is a FAL i2v proxy — a different provider and job shape — so it cannot serve this step. Wiring the clip step to templates-as-data requires a create-video-higgsfield proxy (Marketing Studio product_showcase, imported-product grounding, per-prompt safety block) that does not exist yet. Until it lands, the clips are generated via the Higgsfield Marketing Studio path directly (CLI/MCP) and that step is not a fetchable capability.
The end-card background is an AI flat-lay render (text-free, all three sealed bottles + botanicals) that in prod routes through create-image-fal (NB2); only the HTML text overlay + encode run locally as FREE assembly.
The music is a paid ElevenLabs call that in prod routes through create-music-elevenlabs; only the loudnorm + fade + mux run locally as FREE assembly.

See scripts/PIPELINE.md for the full config-field → source-step map and scripts/README.md for the FREE-assembly detail.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Render Multiworld AI skill do?

Why use Render Multiworld on TypingMind?

Because you install it once and use it with any model. Render Multiworld is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Render Multiworld in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-multiworld. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Render Multiworld?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Render Multiworld?

As many as you like. As long as a model supports skills, you can use Render Multiworld with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Render Multiworld AI skill free?

Yes. It is published on GitHub by gooseworks-ai under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

render-multiworld

Run

Contract

Gaps / routing notes

Bundled files

Frequently asked questions

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