Demo Studio logo

Demo Studio

Organization
tryproduck
demo-studio

Build a premium, fully-animated PRODUCT-DEMO / launch motion-graphics video from a written brief about your product — the "one seamless film" style: scene-by-scene motion graphics with camera moves, real UI mockups, and full sound design, rendered from HTML+CSS+GSAP to MP4 via HyperFrames. Use whenever someone wants to "make a product demo video", "launch video", "animated walkthrough", "hype/demo reel for <product>", an animated feature or flywheel story, or to add any of these set-pieces: a notification/feedback FLOOD of bubbles, real photos of people as circular avatars, a GitHub/changelog/release mock, a "context accumulates" web of connecting cards, a UI element that MOVES + recolors with the camera following it, a contributors wall, an explosion-into-logo endcard, count-up numbers, 3D panel fly-ins, or camera zoom/dolly transitions. ALSO covers full SOUND DESIGN — picking the right SFX for each animation and placing them (see docs/SOUND.md + the bundled sfx/ kit + templates/). The techniques come from a real launch film (https://youtu.be/spaS08Udkyk), but this is a GENERAL-PURPOSE kit: do not copy that film's story. Ask the user what THEIR product does, pick a story arc that fits it, and re-skin the brand tokens. The bundled example uses deliberately generic placeholder copy. For single-concept explainer reels or talking-head edits this is the wrong tool.

Overview

Publishertryproduck
Repositoryproduck-skills
Skill namedemo-studio
Stars
511
Forks
10
Bundled files
38
LicenseApache-2.0
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.

  • 38 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by tryproduck on GitHub. Read the source before you install it.

Installation

Install the Demo Studio 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/tryproduck/produck-skills/tree/main/skills/demo-studio
  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/tryproduck/produck-skills.git /tmp/produck-skills
mkdir -p .claude/skills
cp -r /tmp/produck-skills/skills/demo-studio .claude/skills/demo-studio
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Demo Studio 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 Demo Studio 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 Demo Studio 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.

DemoStudio — the playbook

You are building a premium product-demo motion-graphics film: one seamless timeline of full-screen scenes telling the USER'S story (pick an arc that fits their product, e.g. problem → product → payoff, before → after, or many inputs → one output; do not default to a feedback-capture loop), with camera moves between beats. The whole video is ONE self-contained HyperFrames composition (index.html = HTML + CSS + GSAP) that renders to MP4, then a single SFX track is muxed on.

Start from the example: example/index.html is a compact, commented, working scaffold that shows the whole architecture (paused timeline, 3 scenes, a camera push, a flood, an endcard). Read it first, then grow it into the real thing scene by scene.


0. When to use / not use

  • Use for animated product demos, launch/hype videos, feature stories, flywheel/loop narratives. Any "show the product doing something, beautifully, scene by scene" film.
  • Not for: single-concept explainer reels (one scene per spoken beat), talking-head/CapCut edits, or avatar/TTS videos. Different tools entirely.

1. Architecture (always the same)

  • One paused timeline: const tl = gsap.timeline({paused:true}); register it on window.__timelines["main"] = tl. HyperFrames seeks it per frame.
  • Scenes = absolutely-positioned full-frame <div>s inside #stage, overlapping in the DOM; faded in/out by the timeline. Only the active one is visible at a given time.
  • Schedule by ABSOLUTE time — the last arg of every tl.* call is the start time in seconds. Anchor scene offsets with named consts (e.g. S1, S2, END) so changing one shifts the rest. A DUR const + the data-duration attrs (root, bg, stage) must all match the total length.
  • Deterministic only: no Math.random() / Date.now() / argless new Date() — they break the frame-seeked render. Use a seeded PRNG (see the mul()/rnd() helpers in the example).
  • Build loop:
    npx hyperframes lint                       # 0 errors required
    npx hyperframes render --output out/raw.mp4 -q high
    ffmpeg -i out/raw.mp4 -c:v libx264 -pix_fmt yuv420p -g 30 -keyint_min 30 \
      -sc_threshold 0 -r 30 -crf 17 -movflags +faststart out/vNN.mp4     # ALWAYS re-encode
    ffmpeg -ss <t> -i out/vNN.mp4 -frames:v 1 /tmp/f.png                  # verify by viewing frames
  • gsap defaults: gsap.defaults({ease:"power3.out", duration:0.6}). Register MotionPathPlugin if used.

2. Brand tokens (re-skin per product) — see docs/BRANDING.md

Everything visual is driven by :root CSS vars. To make it your product's film, swap the tokens and keep the system: one canvas colour, near-black ink, exactly ONE restrained accent, status green/red/blue, a shadow style, and three fonts (display / body / mono). Keep one focal accent per scene. Dark scenes use a deep navy + a warm radial glow, never flat black.

3. The technique library — copy these patterns

The full, code-level version is in docs/ARCHITECTURE.md. The set-pieces:

  • Text: typewriter caption (per-char spans + stagger, flip the last word to the accent), kinetic fly-in lines (opacity/y/blur + stagger), count-up numbers (tl.call sets text + a scale punch).
  • People as circular avatars: any square photo → border-radius:50%; overflow:hidden + a name + a role/credibility pill. Mix real faces with code-drawn identicons (deterministic 5×5 symmetric pixel grid) for the natural "not everyone has a face" look.
  • Floods & particles: scatter with jittered-y + brick-offset-x (don't read as rows), clamp on screen; pop in back.out; implode → click → burst on a ring.
  • Transitions: 3D fly-in (rotationY/rotationX/z + blur → flat), blur-out handoff, edge-on flip to swap content unseen, HUD-pill flip to change a label cleanly.
  • Camera (the signature): it's just scale + x/y on the scene element. Push/pull, measured dolly across a tall element, and a camera that follows a moving element.
  • Element moves home: measure the translate to a target slot, leave a dashed ghost, recolor mid-flight, pop a code-diff chip beside it so it references what changed.
  • "Context accumulates" web: SVG lines drawn on (strokeDashoffset→0), a hub that grows a notch per connection, +N badges riding the lines in, a counter ticking up.
  • Explosion endcard: flash + orange disc + shock ring + ~22 shards + screen shake, revealing a value card underneath. Keep it tight (~3s).
  • Realistic SaaS/GitHub UI in pure HTML/CSS: app windows, nav/subnav, PR rows, a release page with per-user credit avatars, diffs that tick green one-by-one. All divs + SVG.

4. Gotchas

  • translate(-50%,…) + GSAP fight over transform — center with xPercent/yPercent or flex.
  • Hidden-then-draw lines/dots: set them hidden at t=0 or they flash early.
  • Scope per-scene CSS under the scene id (#capture .btn) to avoid cross-scene collisions.
  • Always re-encode after render (sparse keyframes → frozen still otherwise).
  • overwrite:"auto" on tweens retargeting the same property (successive camera scales).
  • SVG transform-origin is unreliable — prefer strokeDashoffset draw-ons / explicit origins.

5. Sound design — see docs/SOUND.md + sfx/ + templates/

The film renders silent; sound is a separate muxed layer you can re-roll independently.

  • The repo ships a complete all-original SFX kit in sfx/ (25 sounds, every one synthesized — see templates/make_kit.py). Regenerate any time with python3 templates/make_kit.py.
  • Place cues with templates/build_audio_kit.py (edit the CUES list of (time, token, dB, semitones)) → master.wav → mux: ffmpeg -i video.mp4 -i master.wav -c:v copy -c:a aac -shortest out-sound.mp4.
  • Motion → SFX: pop=appear, click=click, whoosh=motion, wash=converge, coin cascade=counter, confirm(warm muffled)=saved/live, boom=explosion. Full mapping table + mixing rules in docs/SOUND.md.

6. Starting a NEW video

  1. Copy example/index.html into your project (or npx hyperframes init and paste the pattern in).
  2. Re-skin the :root brand tokens to your product (docs/BRANDING.md). Keep the system.
  3. Plan the scene beats as a story and lay anchor consts. One accent per scene, no em dashes.
  4. Build scene-by-scene, copying patterns from docs/ARCHITECTURE.md. Lint + render + frame-verify each scene before moving on. Re-encode.
  5. Generate any face photos up front so they bake while you build the timeline.
  6. Do the sound pass last: edit the cue list, build master.wav, mux the -sound.mp4.

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 Demo Studio AI skill do?

Build a premium, fully-animated PRODUCT-DEMO / launch motion-graphics video from a written brief about your product — the "one seamless film" style: scene-by-scene motion graphics with camera moves, real UI mockups, and full sound design, rendered from HTML+CSS+GSAP to MP4 via HyperFrames. Use whenever someone wants to "make a product demo video", "launch video", "animated walkthrough", "hype/demo reel for <product>", an animated feature or flywheel story, or to add any of these set-pieces: a notification/feedback FLOOD of bubbles, real photos of people as circular avatars, a GitHub/changel...

Why use Demo Studio on TypingMind?

Because you install it once and use it with any model. Demo Studio 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 Demo Studio in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/tryproduck/produck-skills/tree/main/skills/demo-studio. 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 Demo Studio?

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 Demo Studio?

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

Is the Demo Studio AI skill free?

Yes. It is published on GitHub by tryproduck under the Apache-2.0 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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