Remix Chatgpt Ad From Sample

remix-chatgpt-ad-from-sample

First end-to-end validated 2026-06-11 (local, no-backend loop): a Bioma-style perimenopause remix of a single-question ChatGPT source — 750×1624 record (tagged 9:16), 3-message conversation (one user question → one loading dot → one streamed assistant answer), education-only response that lands the brand as the natural recommendation, no end card. ~14s master (3.2s typing + ~0.6s send/dot + ~9s streamed answer + 1s hold), silent by default (empty SFX cue list, stitch stream-copies the video). The Gooseworks MCP publish steps (Phase 4) were stubbed in that loop; everything up to and including meta-upload/ exports ran clean.

Purpose

Given one published ChatGPT ad sample (from the Goose Ads library) + a researched brand, produce a finished ChatGPT chat-reveal video for that brand. The source sample defines the shape — the single user question → one loading dot → one streamed assistant response, the response length and streaming pace — and this skill swaps the substance: the question is rewritten as something a real person would ask ChatGPT in the brand's world, and the streamed answer is rewritten so the BRAND surfaces as the natural recommendation, with the CTA woven into the response. The punchline is the streamed response.

This skill is orchestration: it derives + gets approval for the conversation, then hands rendering to create-chatgpt-video-ad and handles all Gooseworks I/O (render rows, stage reporting, durable upload, final pin). Creative craft rules (word streaming, the one-frame send-tap, the single loading dot, SFX policy) live in the create molecule — do not duplicate or override them here.

It runs on the user's machine inside their Claude Code session (the goose-video local-worker model). The runtime contract — MCP tools, proxies, durable URLs — is the installed ads-remix master skill; this recipe assumes it.

Inputs

Composed Atoms

• create-chatgpt-video-ad — the renderer (sibling molecule): continuous Playwright recording of the typing + send-tap + streamed response, the subliminal/silent SFX policy, 9:16 + 1×1 exports. This skill never re-implements its steps. (skills/ads/packs/video-ad-formats/create-chatgpt-video-ad)
• create-chatgpt-mockup — the framed-chat renderer the create molecule drives: renderHTML(thread) builds the light-mode ChatGPT iOS HTML with every message popState: "pending", the word-stream wrapper, and the inlined keyboard. This must be present on the machine. (create-chatgpt-mockup)
• render-ios-keyboard — the iOS QWERTY keyboard fragment (suggestion bar + alpha/shift/backspace/123/space/return rows) slid up on keyboard-show / down at the send-tap; the chatgpt-mockup atom inlines this same .kbd block. (render-ios-keyboard)
• watch — watch the rendered MP4 (frames + transcript) for the output QC pass.
• mix-master — the near-noop mix stage (the format is silent by default; only an optional subliminal SFX pass routes through here), invoked via the create molecule's workflow.

Workflow

Phase 0 — Fetch + gates (no render row yet)

1. get_ad_project { project_id } → keep source_sample_id, app_url, brand_url, brand_id.
2. get_ad_template { template_id: source_sample_id } → keep recipe.conversation, extracted_script, how_to, media_url. If recipe.conversation is missing, reconstruct the beat from extracted_script (the user question line + the assistant answer) and /watch the media_url to confirm the streaming pace.
3. Brand gate: get_ad_brand { brand_id }.
   • research_status: "complete" → REUSE the existing pack — do NOT re-run research. Read it over MCP: agent-config/brands/<slug>/brand-research/*.md (voice, palette, never-say) + brand-assets/manifest.json (product/category, wordmark, CTA code). Re-research is a ~10-minute spend the user already paid for; repeating it on a complete brand is a bug, not thoroughness.
   • Not complete → run the master skill's "Set up a brand" workflow (idempotent), then continue.
   • Only exception: the status says complete but the pack files are missing/unreadable, or the user explicitly asked to refresh the research — say which case applies before re-running.
4. Machine preflight (video renders locally — fail fast and friendly): ffmpeg -version and npx playwright --version + a Chromium launch check, and confirm the renderer atom resolves — create-chatgpt-video-ad require()s the create-chatgpt-mockup atom's generate.js (the framed-chat renderer; see Local render contract below). If any of the three is missing, tell the user exactly what to install (brew install ffmpeg, npx playwright install chromium) or to run goose-video doctor, and STOP — do not open a render row that can only fail.

Phase 1 — Derive the brand's conversation

Map the source conversation onto the brand. Rules:

• Keep the source's structure: the single user question → one loading dot → one streamed assistant response beat, the same response length and streaming pacing, the same header (plain-title "ChatGPT", rightIcons → rightIconsAlt), keyboard, and composer. The structure is why this ad works — one ask, one streamed answer, the answer is the punch.
• Swap the substance into the BRAND's world: the user question is something a real person would actually type into ChatGPT (8–12 words, lowercase ok, a contraction, no marketing tone), and the streamed assistant answer is rewritten as an education-first response where the BRAND surfaces as the natural recommendation — lead with validation, then the why, then 2–3 short bullets that map to the brand's USP, with the CTA (code or tagline) woven into the response. Set stream: true on the assistant message so its words wrap for the reveal.
• No end card: this format has none by default — the answer carries the whole brand load. Surface the brand inside the streamed response (the natural recommendation + CTA), not on a slate.
• Compliance: zero source-brand leakage — no source product, name, code, or competitor reference may survive anywhere in the question or the response.

Phase 1.5 — Approval gate (in-session)

Show the user the drafted conversation as a readable script (the user question, then the assistant answer, formatted as it streams) and ask them to approve or edit. Persist the draft so the app can see it: write_file → agent-config/brands/<slug>/projects/<project_id>/working/conversation.json, append_project_message { role: "agent", content: <the script> }, and mirror it to the project row so the APP's Review panel shows it: update_ad_project_script { project_id, script_drafts: { format: "chatgpt", conversation, audio: { treatment: "silent" | "sfx" }, materials: [...] }, script: <the readable question + answer text> }. Ingredients for the in-app review — the user reviews on the project page, not in the CLI. A path ingredient shows a real thumbnail / player; a pending: true one shows only a grey placeholder line. This format is usually pure UI, so list whatever visual inputs ARE chosen (an avatar, an attachment image, an end card if the template has one) as { container: "image" | "endcard", label, path: "working/review/<name>" } (legacy { kind, label, path } still works) after get_upload_url → PUT to working/review/; render any composed end card now so it previews as a real image, never pending. Omit ingredients entirely when there truly are none. Do not render until the user says go — a render is minutes of their machine time. If they edit, update conversation.json + re-mirror and re-confirm once.

Draft-only mode (free review): if the user's instruction says "draft only" / "script only" / "just the draft", STOP right after the mirror above — no render row, no asset generation, zero credits spent. Tell the user the draft is now visible on the project page in the app, and that re-running the prompt (or replying "render it") completes the ad.

Phase 2 — Render (open the row FIRST, report stages)

Video runs are long, so unlike the static flow the render row opens BEFORE generating:

1. submit_render { project_id, kind: "full" } → keep render_id.

2. update_render_status { render_id, status: "running", stage: "script" } — then keep the stage current as you work. The app shows it live; a silent >10 min run shows as stalled:

   stage	when
   script	conversation approved, assets being lined up
   assets	keyboard/streaming HTML + (optional) SFX downloads ready
   record	Playwright recording the typing + send-tap + streamed response
   assemble	concat / mux of the continuous chat recording
   mix	near-noop — silent by default (the create molecule ships an empty SFX cue list and stitch stream-copies the video; only an optional subliminal SFX pass touches audio here)
   export	9:16 master + 1:1 variant encode (tagged 9:16, recorded 750×1624)

3. Follow create-chatgpt-video-ad end-to-end with the approved conversation. Local translations:

   • Scaffold a temp working dir (NOT a brand repo folder) in the create molecule's layout: thread.json + timeline.json at the run root (the recorder reads them from the root, not working/); clips/ (record-master.js → master-chat.mp4 + master-chat.sfx.json); edits/stitch.sh → master-final.mp4; meta-upload/ (the 9:16 + 1:1 exports). Copy the closest reference build and swap.
   • Run the recorder with the messaging atom's deps on NODE_PATH (NODE_PATH=<atom>/node_modules node clips/record-master.js) — the recorder require()s the atom's generate.js and reuses its Playwright; the recipe folder bundles no node_modules.
   • Audio: silent by default. No Apple chime, no music bed, no end card. The create molecule emits {"cues": []} and stitch stream-copies the video, so the mix stage is a near-noop — only opt into the bundled subliminal SFX (key-tap −28dB / send-tap −20dB / stream-tick −32dB / response-done −22dB) at the create molecule's pre-normalized levels if the brief explicitly asks. Do not add a bed or an end card.

Local render contract. Rendering is the create molecule's record script + one stitch script driving the create-chatgpt-mockup atom — that atom (generate.js + templates/) is the framed-chat renderer, and it must be present on the machine. It ships with the installed ads-remix master skill (the goose-video local-worker installs it alongside this recipe), not inside the recipe folder. A bare clone of the canonical skills repo currently carries only the atoms/messaging/render-ios-lockscreen proxy, so do not try to render from one — point the recorder's atom require() + NODE_PATH at the installed atom (or the lab atom in a dev loop). The atom's DOM contract the recorder depends on: data-pending rows the timeline pops, the .conversation scroller, the inlined .kbd keyboard slid by data-state, .word[data-stream] spans for the streamed reveal (set stream: true on the assistant message), and light mode (this atom renders light mode only — do not inject a dark theme).

Phase 3 — QC by watching

Run watch on the rendered master (or step its frames + audio directly): the keyboard is up the whole time the user types and slides down on the send-tap beat, the send-tap is one beat (bubble pop + keyboard-down + header right-cluster swap on the same frame), exactly one gray loading dot holds ~500ms (not three), the response streams word-by-word with the soft opacity ramp and auto-scrolls to stay in view, the brand surfaces inside the answer as the natural recommendation (not the source's), no OpenAI spiral appears above any assistant title, the track is silent (or subliminal if you opted in), and duration is within ±20% of the source. Fix-and-re-render at most once per issue; then run the create molecule's own Quality Checks list.

Phase 4 — Publish (durable URLs, then the links)

1. get_upload_url → PUT the master MP4 to agent-config/brands/<slug>/projects/<project_id>/working/final.mp4 (content_type: video/mp4); grab a poster frame (ffmpeg -ss 1 -frames:v 1) and PUT it as working/final-thumb.jpg.
2. update_render_status { render_id, status: "complete", output_url: "/api/ads/projects/<project_id>/render-file?path=working/final.mp4", thumbnail_url: "/api/ads/projects/<project_id>/render-file?path=working/final-thumb.jpg", stage: "export", duration_sec: <ffprobe seconds> } — the render-file path is the DURABLE form; never store a CDN or raw S3 URL.
3. One render → done (latest shows by default). Multiple kept versions → set_final_render with the best render_id.
4. End with BOTH links exactly as the master skill requires: app_url + brand_url, verbatim.

Decision Rules

• This skill vs create-chatgpt-video-ad: remixing a library sample for a brand → this skill (it feeds the create molecule). A net-new ChatGPT ad from a brief with no source sample → the create molecule directly.
• Conversation derivation source: recipe.conversation when present (normal); else extracted_script + watching media_url. Never invent a structure the source doesn't have.
• Audio: silent by default — no Apple chime, no music bed, no end card. Only opt into the create molecule's subliminal SFX pass (the four bundled wavs at their pre-normalized levels) when the brief explicitly asks; the mix stage is otherwise a near-noop (stitch stream-copies).
• Render variant: ChatGPT has no plain/iphone-frame variant axis — the format always records at 750×1624 and is tagged/exported 9:16. Ignore any recipe.render_variant on a ChatGPT sample; it does not apply here (that axis is iMessage-only).
• Approval: always pause at Phase 1.5 on the first render of a project. On an explicit re-run where the user already gave conversation edits in the same message, apply them and proceed without a second pause. No-review escape: if the user's instruction says to skip review ("no review", "single-shot", "don't ask for approval"), skip the pause entirely — still write working/conversation.json + the append_project_message script mirror, then render immediately.
• Batch runs (the prompt lists several project ids): run Phases 0–1.5 for each first (collect all approvals in one message), then render sequentially — Playwright recordings fight for the display, and parallel ffmpeg encodes thrash laptop CPUs.

Output

• working/conversation.json — the approved brand conversation (in the project's Gooseworks folder): header + keyboard + the user question / loading dot / streamed assistant answer.
• working/final.mp4 (9:16 master) + working/final-thumb.jpg in the project folder; the 1:1 export variant uploaded alongside when produced (working/final-1x1.mp4).
• A complete render row carrying the render-file output_url, thumbnail_url, duration_sec, and final stage; set_final_render pin when >1 version.
• A closing message with the project app_url + brand brand_url.

Quality Checks

• The user question reads like a real person typing into ChatGPT (8–12 words, lowercase ok, a contraction) — not ad copy.
• Source structure preserved: the single ask → one loading dot → one streamed answer beat, the response length/pacing match the sample.
• The brand surfaces inside the streamed answer as the natural recommendation, with the CTA woven in — never on an end card (there is none).
• Zero source-brand leakage anywhere (question, response) — compliance-critical.
• Send-tap is one beat (bubble pop + keyboard-down + header right-cluster swap), exactly one gray loading dot (~500ms), response streams word-by-word with auto-scroll; passes the create molecule's checks.
• Track is silent by default ({"cues": []}, stitch stream-copies) — or every cue sits at the bundled subliminal level if the optional SFX pass was used; no cue on the loading dot.
• Recorded 750×1624 and the SHIPPED file preserves that exact ratio — native, or an aspect-true upscale like 1080×2338 (scale=1080:-2). A 1080×1920 export is a horizontal stretch (live incident 2026-06-11, Alitu) — ffprobe the PUBLISHED file, not just the master. Tagged 9:16; duration_sec reported matches ffprobe; render row carries render-file URLs, not CDN links.

Failure Modes

• ffmpeg / Playwright missing → caught in Phase 0 preflight; user told the install commands (goose-video doctor); no render row opened.
• Renderer atom missing (Cannot find module '.../create-chatgpt-mockup/generate.js') → the framed-chat renderer isn't installed (a bare canonical skills-repo clone ships only the render-ios-lockscreen proxy). Caught in Phase 0 preflight — point at the atom installed by the ads-remix master skill (see Local render contract) before opening a render row.
• Sample has no recipe.conversation and no usable extracted_script → tell the user this sample isn't remix-ready yet and stop; do not improvise a structure (the admin needs to fill the sample's remix payload).
• Assistant text appears all at once / not streaming → stream: true is missing on the assistant message; set it so the atom wraps every word in a .word[data-stream] span.
• Render dies mid-run (Playwright crash, encode failure) → one retry of the failed phase; on second failure update_render_status { status: "failed", error_message } and report — never leave the row running.
• Upload fails → retry the presigned PUT once; persistent failure → mark the render failed with the local file path in error_message so nothing is lost.

Tests

See tests/ — structural smoke, a sample project/sample input pair, the expected artifact list, a manual end-to-end script, and the verifier checklist.

Skill Location & Related

• This skill: skills/ads/packs/video-ad-formats/remix-chatgpt-ad-from-sample/
• Renderer: create-chatgpt-video-ad
• iMessage sibling: remix-imessage-ad-from-sample
• Registry entry: formats.json → "chatgpt" (the app + CLI route here through it)