Render Chatgpt Chat logo

Render Chatgpt Chat

OrganizationPopular
gooseworks-ai
render-chatgpt-chat

Assemble a ChatGPT chat-reveal video ad from a thread + timeline JSON — one continuous Playwright recording of a ChatGPT mobile chat (user types with the iOS keyboard up → taps send → keyboard slides down + header cluster swaps in one beat → one gray loading dot → the assistant answer streams in word-by-word) crossfaded into a designed end card, with subliminal ChatGPT SFX and an optional ducked music bed. FREE assembly (Playwright + ffmpeg); the recipe supplies the per-brand thread + timeline + end-card config and gates the paid music call to its own capability. The ChatGPT sibling of render-imessage-chat. Use for the chatgpt-chat format.

Overview

Publishergooseworks-ai
Repositorygoose-skills
Skill namerender-chatgpt-chat
Stars
1.2K
Forks
208
Bundled files
15
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.

  • 15 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 Chatgpt Chat 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.
  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-chatgpt-chat .claude/skills/render-chatgpt-chat
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Render Chatgpt Chat 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 Chatgpt Chat 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 Chatgpt Chat 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-chatgpt-chat

The free renderer for the chatgpt-chat video ad format — the "I just asked ChatGPT…" creative, where someone asks ChatGPT a question and the streamed assistant answer is the punchline (the brand surfacing as the natural response). Deterministic Playwright + ffmpeg assembly; no generative video of the UI, so the bubble text and streamed answer stay pixel-crisp.

This is the ChatGPT sibling of render-imessage-chat. Reach for this one when ChatGPT is the more credible host for the answer; reach for iMessage when the punchline is a peer's reaction in a DM. The template recipe (DB) supplies the per-brand thread + timeline + end_card config and gates the paid music call (music bed → create-music-elevenlabs) to its own capability.

What it renders

One continuous take — never scene-by-scene (every reload flickers):

  1. User types in the composer with the iOS keyboard up (composer-type).
  2. Send-tap is ONE beat — the user bubble pops, the keyboard slides down, and the header right-cluster swaps (personPlus/dottedCircleedit/more) all on the same t. Never sequence them across frames.
  3. One gray loading dot holds ~500ms (never three — three reads as iMessage typing, wrong app), silently (no SFX on the dot).
  4. The assistant answer streams in word-by-word (stream-words, ~7 wps) with a soft opacity ramp; the conversation auto-scrolls to keep it in view.
  5. Crossfade to a designed end card (wordmark + ⭐ proof row + trust trio + CTA pill) and mux a ducked music bed → master MP4.

The chat records at the ChatGPT-native ~9:19.5 (default 750×1624) to match a real iPhone screen recording. Never stretch the chat to a different aspect ratio — the end card is scaled-to-fit + padded to the chat's dimensions in stitch, so the chat is never touched.

Run

bash
cd scripts && npm install            # once — installs Playwright
npx playwright install chromium      # once
node record-chat.js     --config config.json --out-dir <work>   # → master-chat.mp4 + .sfx.json
node render-end-card.js --config config.json --out-dir <work>   # → scene-end-endcard.mp4
bash stitch.sh --chat <work>/master-chat.mp4 --end <work>/scene-end-endcard.mp4 \
     --sfx <work>/master-chat.sfx.json --out <work>/master-final.mp4 \
     --pad-color "#ffffff" [--music <work>/music-bed.mp3] [--also-1x1]
  1. record-chat.js — reads config.json (thread + timeline + geometry), renders the bundled create-chatgpt-mockup HTML once with every message pending, walks the timeline on requestAnimationFrame inside the page, records it as one continuous MP4, and emits the deterministic SFX cue list.
  2. render-end-card.js — fills end-card.template.html from config.end_card (wordmark/logo_svg, stars, proof, trust trio, CTA, colors) → still MP4. This is the SAME generic end card as render-imessage-chat (copied verbatim).
  3. stitch.sh — normalizes the end card to the chat's dimensions, crossfades chat → end card, layers the subliminal ChatGPT SFX, optionally ducks a music bed under it, and optionally derives a 1:1 crop. All FREE ffmpeg. Pass --pad-color = end_card.bg (default #ffffff, ChatGPT light mode) so the pad under the end card is seamless.

The chat body: bundled create-chatgpt-mockup

The ChatGPT chat HTML comes from create-chatgpt-mockup (its generate.js + templates/ produce the light-mode ChatGPT iOS HTML — status bar, header, message rows, streaming word-spans, composer, and the inline iOS keyboard). Those files are bundled into scripts/mockup/ so this capability renders the chat body standalone — no sibling fetch of create-chatgpt-mockup is required. record-chat.js does require('./mockup/generate.js').

The keyboard is inlined by the mockup (renderKeyboard) — no separate keyboard atom.

Timeline events (consumed by record-chat.js)

KindMeaning
composer-type{ text, dur_sec } — type into the composer. SFX = one key-tap per word.
composer-clearWipe the composer instantly (fire at send-tap).
keyboard-show / keyboard-hideSlide the iOS keyboard up / down.
send-tapPulse the send button. SFX = send-tap.
pop{ target: <msg-id> } — reveal a message row.
header-swap{ value: "alt" } — swap the header right-cluster.
loading-dot-show / loading-dot-hide{ target: <dot-id> } — the single gray dot.
send-state{ value: "streaming"|"active" } — composer send-button state.
stream-words{ target, dur_sec, wps } — reveal the assistant answer word-by-word. SFX = stream-tick every 12 words + response-done at the end.
scroll-to{ target, dur_ms } — smooth-scroll a row into view.

See scripts/config.example.json for the canonical thread + timeline (the "one beat" send-tap and the streamed list answer are both wired there).

Contract

  • FREE assembly: Playwright record + ffmpeg composite/mux + the bundled SFX. No AI-rendered text — the bubbles, the streamed answer, and the end-card copy are all real HTML/PIL, never invented by a model.
  • The recipe (DB) supplies the per-brand config: the thread (light-mode ChatGPT, assistant message set stream: true), the timeline, the end_card (prefer a real logo_svg wordmark), and an optional music bed.
  • SFX are subliminal by design (ChatGPT has no native chime): key-tap -28dB, send-tap -20dB, stream-tick -32dB, response-done -22dB, and never a cue on the loading dot. Set "sfx": false in the config to ship the chat silent.

Gaps / routing notes

  • Music bed is an input, not generated here — the recipe gates it to create-music-elevenlabs (paid, proxy-routed, billed to the Ads agent) and passes the file into stitch.sh --music.
  • Bundled SFX are synthesized stand-ins. The original four wavs (key-tap/send-tap/stream-tick/response-done) were lost from Git LFS (the objects 404 on the server), so assets/sfx/*.wav are freshly synthesized subliminal clicks/ticks. They work as-is; swap in real wavs (same filenames) for tuned SFX.
  • Portability: everything runs from the fetched /tmp/gooseworks-scripts/render-chatgpt-chat/scripts/… — the chatgpt-mockup generator + templates are bundled under scripts/mockup/, and the generic end card is bundled under scripts/. No /Users/… or repo-relative paths, and no required sibling fetch.
  • Requires ffmpeg/ffprobe on PATH and Playwright Chromium (npx playwright install chromium).

Self-QC (per project rule — always /watch the master)

  • Keyboard is up the whole time the user types, and slides down only on the send-tap beat (never visible while the answer streams).
  • Send-tap is one beat: user bubble + keyboard-down + header-swap on the same frame.
  • Exactly one gray loading dot for ~500ms (not three), and no SFX on the dot.
  • The answer streams word-by-word, left-to-right / top-to-bottom, not all-at-once.
  • No OpenAI spiral logo above any assistant title (the spiral is empty-state only).
  • No micro-flicker / scene cuts; the end-card pad color matches end_card.bg.

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 Chatgpt Chat AI skill do?

Assemble a ChatGPT chat-reveal video ad from a thread + timeline JSON — one continuous Playwright recording of a ChatGPT mobile chat (user types with the iOS keyboard up → taps send → keyboard slides down + header cluster swaps in one beat → one gray loading dot → the assistant answer streams in word-by-word) crossfaded into a designed end card, with subliminal ChatGPT SFX and an optional ducked music bed. FREE assembly (Playwright + ffmpeg); the recipe supplies the per-brand thread + timeline + end-card config and gates the paid music call to its own capability. The ChatGPT sibling of rend...

Why use Render Chatgpt Chat on TypingMind?

Because you install it once and use it with any model. Render Chatgpt Chat 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 Chatgpt Chat 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-chatgpt-chat. 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 Chatgpt Chat?

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 Chatgpt Chat?

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

Is the Render Chatgpt Chat 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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