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Render Whiteboard Explainer

OrganizationPopular
gooseworks-ai
render-whiteboard-explainer

Assemble a whiteboard explainer video ad from a beats file — a narrator explains one idea while a real whiteboard fills up in black marker, with a hand-lettered title, bulleted rows down the left, a drawing filling the right, and a payoff that letters the closing line and rings the claim. The board is a PHOTOGRAPH and the ink is multiplied onto it, so the surface sheen and window light come through the strokes; the drawings are generated as line art and traced to ordered strokes, then revealed in drawing order on the word they belong to. The layout is SOLVED from the beats, never hand-placed. FREE assembly (Pillow plus ffmpeg) apart from one board photo and one drawing per subject, both one-time per brand. Use for the whiteboard format.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill namerender-whiteboard-explainer
Stars
1.2K
Forks
216
Bundled files
14
LicenseMIT
Links
  • 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.

  • 14 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 Whiteboard Explainer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/gooseworks-ai/goose-skills/tree/main/skills/ads/capabilities/render-whiteboard-explainer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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-whiteboard-explainer .claude/skills/render-whiteboard-explainer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Render Whiteboard Explainer 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 Whiteboard Explainer 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 Whiteboard Explainer 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-whiteboard-explainer

The renderer for the whiteboard video ad format: a voice explains one idea while a board fills up in marker, the way a graphic recorder works a room. Every mark lands on the word it belongs to, and the board is wiped and reused between sections.

Siblings in the chat-UI family are render-imessage-chat, render-chatgpt-chat and render-apple-notes-chat, where a screen is the creative. Reach for this one when the creative is someone explaining a thing by drawing it.

The three decisions that make this format work

The board is a photograph. A drawn board reads as a drawn board, and a plain white frame reads as a sketch film. Both were built and both were rejected. One generated still of a real blank whiteboard in a real room is the plate, and the ink is multiplied onto it so the surface sheen and the window light come through the strokes rather than sitting on top as flat black. The handheld drift is generated over both layers at once, so nothing can slide against anything.

The drawings are generated as line art, then traced. Do not hand-code them, and do not trace painterly images. Art traced from a photograph carries every contour the photograph had and reads as clip-art; art generated as a marker drawing traces to a handful of confident paths. An open hand came back as a single continuous stroke. Chain each generation off the first so the line weight matches across the set.

There is no colour. Black marker throughout. Do not add an accent.

Choices

The recipe asks these before any paid step; this renderer only draws what the beats say.

  • the script — what the narrator says. Everything downstream is anchored to its word timings, so it is settled first and never changed afterwards.
  • the beats — for each moment, what is SAID and what is DRAWN. A row of text, a drawing, or both. One number can be marked as the hero, which letters it large instead of as another row.
  • the title and subtitle — lettered on the first board.
  • the payoff — the closing line, lettered on the last board, with a ring closing around the claim it refers to.
  • the boards — how many times the board is wiped and reused. Three suits a half-minute.

Brand facts come from the brand kit.

What it renders

  1. The plate. One photograph of a blank board in a room, generated once per brand, then cropped so the board fills the frame with its side edges running out of shot. The writable surface is measured off the image and pulled inside the caption safe zone before anything is mapped through it.
  2. The drawings. One black line drawing per subject the script names, generated once per brand and traced into ordered stroke paths.
  3. The layout. Solved from the beats, not authored. Rows go down a left column, drawings down a right one, with an enforced gutter between them, and the content runs the full height of the board. Boards are split at a pause near a balanced boundary, which is where a person would wipe.
  4. The video. Marks appear stroke by stroke in drawing order, each starting on its own word. Text is written letter by letter. The board wipes between sections. Captions sit inside the safe zone and never run ahead of the voice.
  5. The master. Gentle compression before a measured two-pass loudness normalisation, then a limiter. Targets minus fourteen LUFS with true peak under minus one and a half, and keeps the payoff hold intact.

Non-negotiables

  • Every mark lands on its own word. The voiceover is the clock. An anchor that resolves to the wrong word does not look wrong, it silently reorders the video: one that matched an early word instead of a late one once dragged a whole section to the front, and the ad played its ending first with nothing reporting a problem. Anchors are resolved once, shared by the solver and the renderer, and an ambiguous one is refused rather than guessed at.
  • Nothing is hand-placed. Anything that refers to something else — an arrow, a note, a ring — takes its target as an argument and works out its own position. Anything sharing space with a drawing is bounded by that drawing's box. Two things placed at coordinates chosen independently will eventually meet.
  • Copy a reference's grammar, never its content. The reference board bullets its rows with a drawn eye and fans emphasis marks beside its phrases, but those belong to that board's brand. Reproduced on another script they are decoration that means nothing. Filler has to be about something: a drawing of what the line refers to, never abstract specks.
  • Two reviews, both human. The storyboard still costs seconds and is where relevance is judged — whether a mark is about the line it sits under, whether the payoff says the closing line. No automated check decides that. Then the finished cut, watched end to end with the watch skill.

Inputs

  • the spoken audio and its word-level timings, as described below
  • a beats file — see the example beside the scripts
  • a brand kit for the facts

The voice comes with its word timings. create-vo-elevenlabs returns audio only, and this format needs a timing for every word. scripts/gen-voice.py --project <dir> reads vo and voice from beats.json and calls the proxy's /with-timestamps route, writing voice/vo.mp3 and voice/words.json, which make-episode.py requires. A dry run prints the character count and the cost; --yes spends. It routes through the GooseWorks proxy (scripts/media_proxy.py), never the speech provider directly, and refuses a payload it has already paid for.

Checks it runs itself

The build refuses to continue when any of these fail, and names what broke:

  • every anchor resolves to exactly one intended word
  • sections start in script order
  • every mark finishes being drawn before its board is wiped
  • rows stay inside the column and cannot reach a drawing
  • loudness, true peak and the payoff hold

Cost

The board photo and the drawings are one-time per brand. A second video for the same brand costs only the voiceover. Everything else — the layout, the lettering, the tracing, the render and the master — is free and local. Rendering a half-minute takes under three minutes.

Honest ceiling

Measured against the filmed reference this reaches about a fifth of its ink cover, because the reference is a time-lapse of a much longer drawing session while every mark here waits for its word. Filler narrows that and does not close it. If a brief needs a genuinely full board, the script has to be longer or the marks have to stop waiting for words.

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 Whiteboard Explainer AI skill do?

Assemble a whiteboard explainer video ad from a beats file — a narrator explains one idea while a real whiteboard fills up in black marker, with a hand-lettered title, bulleted rows down the left, a drawing filling the right, and a payoff that letters the closing line and rings the claim. The board is a PHOTOGRAPH and the ink is multiplied onto it, so the surface sheen and window light come through the strokes; the drawings are generated as line art and traced to ordered strokes, then revealed in drawing order on the word they belong to. The layout is SOLVED from the beats, never hand-place...

Why use Render Whiteboard Explainer on TypingMind?

Because you install it once and use it with any model. Render Whiteboard Explainer 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 Whiteboard Explainer 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-whiteboard-explainer. 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 Whiteboard Explainer?

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 Whiteboard Explainer?

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

Is the Render Whiteboard Explainer 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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