Agent skill

Render Multiworld

by gooseworks-ai in gooseworks-ai/goose-skills

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 (approved headline +…

MITAuto-check passedMedia & Creative

Install Render Multiworld

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill render-multiworld -a claude-code

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

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills render-multiworld --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/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ads/capabilities/render-multiworld .claude/skills/render-multiworld && 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/

Facts

Skill name
render-multiworld
GitHub stars
1.2k
Token cost
~1.5k tokens
SKILL.md length
740 words
Files
6 (incl. scripts)
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

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 (approved headline +…

  • Works in 4 steps: Trim clips (FFmpeg, FREE) — trim each… → End card (Playwright/HTML, FREE) —… → Hard-cut concat (FFmpeg, FREE) — concat… → …
  • The multiworld-product-tour format
  • SKILL.md covers Choices, Run, Contract and Gaps / routing notes
  • Tasks that involve Video production

What it does

Render Multiworld is an agent skill from gooseworks-ai/goose-skills. 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 (approved headline + handwritten product 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.

Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts (for example `scripts/PIPELINE.md`, `scripts/README.md` and `scripts/config.example.json`).

It sits in Media & Creative, covering Video production and Browser testing. It works with Playwright and FFmpeg. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.

When your agent uses it

  • The multiworld-product-tour format
  • Tasks that involve Video production
  • Tasks that involve Browser testing

Example prompts

  • “/render-multiworld”

Workflow steps

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

  1. Trim clips (FFmpeg, FREE) — trim each per-world clip to its scene_grid[].duration_sec
  2. End card (Playwright/HTML, FREE) — screenshot end_card.html over the AI flat-lay
  3. Hard-cut concat (FFmpeg, FREE) — concat the six trimmed clips in scene order
  4. Music mux + web encode (FFmpeg, FREE) — mux the single instrumental bed onto the

What it can do on your machine

Read from SKILL.md and the folder at commit c650c6d. 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

    Ships 3 files in scripts/, which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    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

Render Multiworld loads about 1.5k tokens when it runs. Until then it costs about 130 tokens; SKILL.md has 740 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~130
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 740 words, ~1,511 tokens.

Download SKILL.mdSave it as .claude/skills/render-multiworld/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
render-multiworld
description
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 (approved headline + handwritten product 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.
status
active

render-multiworld

Assemble a silent, music-led "multi-world product tour" ad (≈27s, 9:16) — a tour of three distinct "third-place" worlds (chosen per video), one per product/variant, 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 product stays small) hard-cutting to a ~3.5s top-down MACRO product MOMENT (the sealed product nested with its companion prop). Variant identity is carried by the world + companion prop, not by product 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.

Choices

The calling recipe asks the user these before any paid step; this capability only assembles what they produced. The worked example (Primally Pure) values are examples, never defaults.

  • worlds — the three places toured → config.worlds, config.scene_grid (demo: pilates studio / spa anteroom / farmers market).
  • visual_style — the worlds' look → config.visual_style, worlds[*].palette, end_card.nb2_prompt (demo: sunlit-natural / handmade).
  • music — the bed's genre/mood → config.music.prompt (demo: warm acoustic-pop).

Nothing in the assembly keys on world slugs or names: clips are ordered by scene_grid[].scene, and the end-card copy is whatever end_card.overlay holds.

Run

  1. 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.
  2. 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 (overlay.headline, approved brand copy — the demo's was "FIND YOUR DAILY."; Inter 900), one handwritten Caveat product label + hand-drawn SVG arrow per product, Playfair wordmark + URL. End-card text is HTML, NEVER AI-rendered — the AI step produces the background only.
  3. 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.
  4. 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.
Show full SKILL.md (343 more words)Show less

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-video config (worlds, palettes, companion props and music mood from the user's choices; prompts; end-card copy from the brand kit); this capability is the generic assembler.

Gaps / routing notes

  • Update: the current recipe makes the six clips with create-image-fal (nano_banana_2 keyframe edit grounded on the real product_image) → create-video-fal (Kling 3.0 i2v), so the gap below only applies to reproducing the demo's Higgsfield build exactly.
  • The demo's clips used 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.

© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts) in skills/ads/capabilities/render-multiworld of gooseworks-ai/goose-skills.

  • SKILL.md
  • scripts/PIPELINE.md
  • scripts/README.md
  • scripts/config.example.json
  • skill.meta.json
  • tests/smoke-test.md

Open the folder on GitHubat commit c650c6d

Compare with similar skills

Render Multiworld 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.

Render Multiworld compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Render Multiworld this skillgooseworks-ai/goose-skills1.2k—~1.5kAutomated safety check: PassMIT
Cs Code VideoChenShuo2004/cs-skills194—~2.1kAutomated safety check: PassMIT
Character Animation QAcalesthio/OpenMontage66k—~389Automated safety check: PassMIT
Browser Video Recordingnirholas/three.ws2281 repos~1.5kAutomated safety check: PassApache-2.0
Demo Videoalinaqi/maggy707—~1.4kAutomated safety check: PassMIT
Sprint Summaryshopsys/shopsys350—~6.4kAutomated safety check: PassCustom licence

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Questions about Render Multiworld

What does Render Multiworld do?

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 (approved headline +…. Render Multiworld is an agent skill from gooseworks-ai/goose-skills. 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 (approved headline + handwritten product labels + arrows) over an AI flat-lay background, and mux one music bed into a 720x1280 web master.

When should I use Render Multiworld?

Render Multiworld fits situations like: the multiworld-product-tour format; tasks that involve Video production; tasks that involve Browser testing.

How do I install Render Multiworld in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill render-multiworld -a claude-code`. Or copy the skill folder (skills/ads/capabilities/render-multiworld in gooseworks-ai/goose-skills) into .claude/skills/render-multiworld in your project. Claude Code loads it when a task matches its description.

How do I install Render Multiworld in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill render-multiworld -a codex`. Or copy the skill folder (skills/ads/capabilities/render-multiworld in gooseworks-ai/goose-skills) into .agents/skills/render-multiworld in your project. Codex loads it when a task matches its description.

Can I use Render Multiworld 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 gooseworks-ai/goose-skills --skill render-multiworld -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/render-multiworld, .gemini/skills/render-multiworld, .github/skills/render-multiworld and .opencode/skills/render-multiworld in your project.

What does Render Multiworld need to run?

SKILL.md names no scripts, command-line tools or credentials: Render Multiworld is instructions for the agent only.

Does Render Multiworld access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Render Multiworld 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Render Multiworld use?

Render Multiworld is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Render Multiworld use?

About 1.5k tokens (SKILL.md is roughly 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 Render Multiworld?

Skills that share tags, products or a category with Render Multiworld: Cs Code Video (ChenShuo2004/cs-skills, 194 stars), Character Animation QA (calesthio/OpenMontage, 66k stars), Browser Video Recording (nirholas/three.ws, 228 stars) and Demo Video (alinaqi/maggy, 707 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Render Multiworld?

gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,239 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.

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