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Render ChatGPT Chat

Free

Create engaging ChatGPT chat-reveal video ads.

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Free · Opens the source repo

What Render ChatGPT Chat does

Render ChatGPT Chat is a specialized tool designed for creating video advertisements that showcase ChatGPT interactions. By leveraging Playwright and ffmpeg, this skill allows users to assemble a continuous video that captures the essence of a ChatGPT conversation. The process involves recording a user typing on an iOS keyboard, sending a message, and then displaying the assistant's response in a visually appealing format. The final output is a polished video ad that seamlessly transitions into a branded end card, complete with optional background music and sound effects.

The skill operates by utilizing a structured timeline and thread configuration that can be customized for different brands. Users can input a JSON configuration that defines the chat thread, the timing of user interactions, and the design of the end card. This ensures that each video ad is tailored to the specific branding and messaging needs of the user. The assembly process is deterministic, meaning that the output is consistent and replicable, which is crucial for maintaining brand integrity across multiple video ads.

This tool is particularly beneficial for marketers and content creators who want to produce high-quality video content that highlights the capabilities of ChatGPT in a conversational format. By using real HTML and CSS for the chat interface, the rendered videos maintain a crisp and professional appearance, avoiding the pitfalls of AI-generated text that may not align with brand messaging. The inclusion of subliminal sound effects enhances the viewing experience without overwhelming the content, making it suitable for various advertising platforms.

Overall, Render ChatGPT Chat is an essential tool for those looking to create engaging and authentic video ads that effectively communicate the value of ChatGPT interactions. Its ease of use and customization options make it a valuable addition to any marketing toolkit.

When to use it

Use this tool when you need to create a video advertisement that features a ChatGPT conversation, especially for marketing purposes.

When not to use it

This skill is not suitable for generating dynamic or interactive video content beyond the pre-defined chat interactions it supports.

What you can build with it

Creating Marketing Videos

Use Render ChatGPT Chat to produce engaging marketing videos that highlight the capabilities of ChatGPT in real-time.

Brand-Specific Customization

Tailor the video ads for different brands by adjusting the JSON configuration to fit specific messaging and design needs.

Professional Video Production

Utilize this skill to maintain a high level of professionalism in video ads, ensuring that all visual elements are crisp and aligned with brand standards.

How to install Render ChatGPT Chat

View source

1. Install with the skills CLI

npx skills add gooseworks-ai/goose-skills/render-chatgpt-chat --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by gooseworks-ai

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

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.

Frequently asked questions about Render ChatGPT Chat

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