The complete system, for any brand: from 35 competitor ads to 50-60 launch-ready creatives. Every step has its input, its deliverable and a copy-paste prompt.
Module 2 — See it run on a real brand →
Every improvement requested on the system is added here and applied to every step below.
| # | Rule | Added |
|---|---|---|
| R1 | Any template is accepted. Whatever the concept, niche or product in it, every template gets re-adapted. Never skip one because it doesn't look like our angles. | 1 Oct 2026 |
| R2 | Sort first. Templates are grouped into concept families before anything is written, then run concept by concept. | 1 Oct 2026 |
| R3 | Spread the angles inside each concept. One ad per template. Inside each concept family, the winning angles from the research are spread across its templates so every family covers every angle, each with headlines from that angle's bank. Every ad maps to one of the research's top angles: no extra "other" group. | 1 Oct 2026 |
| R4 | Volume = number of templates. 79 templates in = 79 ads out. Extra headline variations only on request. | 1 Oct 2026 |
| R5 | Research once. After step 1, the brand kit is locked: we provide the templates, the AI never researches again. | 1 Oct 2026 |
| R6 | Side by side. The comparison site always shows each ad next to its template, as a pair, on desktop and mobile. | 1 Oct 2026 |
| R8 | Only the research angles. If a template doesn't fit an angle naturally, rewrite it until it does. Never create a 6th group outside the top angles. | 1 Oct 2026 |
| R9 | Headlines come from the research. Every ad's main headline is one of the top 5 headlines or a near-verbatim line from the research's headline bank, adapted only for our facts (price, offer, guarantee, no competitor names). Hyper-aggressive, hyper-precise, never outside the 5 angles. | 1 Oct 2026 |
| R10 | 1 Oct 2026 | |
| R11 | Decode protocol, before writing anything. 1) Decode the concept: why did they build it like this? 2) Pick the angle that fits it best (not a forced spread). 3) Understand the humor or emotion between the image and the text, who it targets and what it shows, and check our angle keeps it. | 1 Oct 2026 |
| R12 | Same amount of text as the template. Never add a context line, tagline or disclaimer the template doesn't have. (Replaces R10.) | 1 Oct 2026 |
| R13 | Speak the customer's problem, not the product. Name who it's for by their problem ("For stubborn beer belly", not "For men over 40"). Benefits = the result he wants, compared with what he already tried. No mechanism jargon the avatar doesn't know. | 1 Oct 2026 |
| R14 | Keep the winner's mechanism. Same angle as the template → keep their words. Cheeky or sexual template → stay cheeky. A known reference (Ozempic, Minoxidil, coffee) → swap for something our avatar already knows and uses. | 1 Oct 2026 |
| R7 | English. Site, prompts and briefs are written in English. | 1 Oct 2026 |
It turns a brand and a concept into an ad JSON blueprint with a paste-ready prompt for ChatGPT Images 2.0 (high quality, 1:1 square). Every step below feeds it.
In Claude Code: /creas command or the ad-blueprint-gpt-image-2 skill.
Open the full skillThe kickoff message, to paste as-is into a new session. Fill in the fields in brackets.
Role: you are my head of creative strategy for an e-commerce brand selling on Meta. Context - My brand: [BRAND] — [PRODUCT] — [OUR WEBSITE URL] - The competitor: [COMPETITOR] — [URL] — they sell the same product under a different brand (same product, same promise). - I'm giving you a folder of 35 of their ads: [FOLDER] (static images + videos). - I'm also giving you a folder of winning templates, sorted by concept: [TEMPLATES FOLDER]. Tools to use - The ad-blueprint-gpt-image-2 skill (JSON + ChatGPT Images 2.0 prompts). - mr-transcribe to transcribe the videos (OpenAI API). - The TrendTrack MCP for competitive intelligence. Mission, in this order 1. Full market research: analyze every static, transcribe every video, then complete it with TrendTrack on the competitor AND on our brand. Deliverable: top angles, top headlines, avatar, winning formats, offer, weaknesses (in the format of the provided template). 2. 1:1 adaptation of the winning templates: for each concept, adapt every ad to every winning angle with its headlines, double every creative, aggressive conversion-driven headlines. One JSON per creative (50 to 60 total). 3. Generation with GPT Image 2 (quality high, 1:1), then QC of every image by a dedicated agent. 4. Delivery: a comparison site (template vs our ad), then a demo link with only the final images. Rules - Nothing invented: every angle and every headline points back to its source ad. - Headlines in English, quoted word for word in the research, then rewritten for our creatives. - Get my sign-off on the market research before moving to step 2.
Here is the folder of 35 ads from [COMPETITOR]: [FOLDER]. 1. Transcribe every video with mr-transcribe (API, never local whisper). 2. For EACH ad, fill one row: # · format (static/video) · exact headline (word for word) · subheadline · video hook (first 3 seconds) · angle · mechanism used · visual format · proof shown · offer · CTA. 3. Group the ads by angle. For each angle: the idea in 2 sentences, the number of ads, duplicates, the best headlines. 4. Rank the angles by weight (volume + duplicates + run time). Don't summarize too early: give me the 35-ad table first, then the synthesis.
| TrendTrack tool | To get |
|---|---|
| search_advertisers · lookup | The Meta pages of the competitor and of our brand |
| search_ads · get_brandtracker_scaling_ads | Active ads, past ads and the ones scaling |
| get_brandtracker_transcripts | Video transcripts already indexed |
| analyze_tracked_brand · brief_competitor | The brand's strategic overview |
| search_shops · analyze_brand_changes | Traffic, trends, offers, sales pages |
| search_emails · analyze_shop_emails | Email sequences and promotions |
Using the TrendTrack MCP, pull as much information as possible on [COMPETITOR] AND on [BRAND]: - Meta pages, number of active ads and trend over 6 months; - scaling ads and most duplicated ads; - available video transcripts; - website traffic and 30-day trend; - offers, prices, guarantees, sales pages; - emails and promotions. Cross-check with the 35-ad analysis: confirm or correct the angle ranking. Cite the source of every number.
Write the final market research report, in exactly this structure: 1. Top 5 angles — table: # · Angle · The idea (2-3 sentences, including the mechanism) · Weight. 2. 5 secondary angles — one line each. 3. Top 5 headlines — word for word. 4. Headline bank — sorted by category: Pain & mechanism · Comparison · Product · Story · Urgency. 5. Video hooks — word for word. 6. Avatar — age, situation, visible problem, what they've tried and spent, everyday shame behaviors. 7. What proves it to them — concrete everyday proof. 8. Winning formats — with the static / video split. 9. Their offer — price, subscription, guarantee, social proof. 10. Their weaknesses — backed by TrendTrack numbers. 11. Recommendation for [BRAND] — the 3 angles and 10 headlines to attack first. These angles and headlines become the source for our future creative JSONs.
Here is the folder of winning templates: [TEMPLATES FOLDER], sorted by concept (about 6 ads per concept). My brand: [BRAND]. Logo and packaging locked, product photo attached. First: accept EVERY template, whatever its concept, niche or product. Never skip one because it doesn't look like our angles. Then sort the templates into concept families and work concept by concept. For EACH template: 1. Describe its structure: layout, text hierarchy, visual format, type of proof, product placement. 2. Adapt it 1:1 to [BRAND]: same structure, same layout, our product in place of theirs. 3. Inside each concept family, spread the winning angles from the market research across the templates so the family covers every angle. One ad per template, with headlines from its angle's bank. 5. Extreme, aggressive, conversion-driven headlines, taken from the winning headline bank and then rewritten (never copied word for word). Output: one JSON per creative using the ad-blueprint-gpt-image-2 skill. - Image 1 = our product (to be reproduced identically). - Image 2 = the template (layout reference only: not its text, not its product). - Fields: concept, angle, headline_id, headline_final, gpt_image_prompt. Volume = 1 ad per template. Start with 1 complete concept family and show it to me before running the rest.
Generate each JSON with GPT Image 2 (quality high, 1:1 square), Image 1 = our product, Image 2 = template. Then launch a QC agent that checks EACH image at full resolution (never a thumbnail): [ ] product identical to the reference (shape, colors, label, label text) [ ] exact headline, no typos, no extra words, no duplicated text [ ] offer, price and guarantee match our product sheet [ ] structure faithful to the template (layout, hierarchy, product placement) [ ] one-second test: problem, cause, product and guarantee are obvious to the avatar [ ] no distorted hands or faces, no stray logos, no watermark [ ] nothing banned by our product sheet Any non-compliant image is regenerated using "change only X, keep Y". Give me a table: creative · status · fix applied.
Publish two pages on the VPS (<name>.machineroom.app, noindex, clean URLs): 1. Comparison: for each creative, template on the left and our ad on the right, grouped by concept, with the angle and headline under each pair. 2. Demo: a grid with ONLY our final images, no templates, no concept or angle names, no technical text. It's a demo link for someone outside the team. Both pages must work on mobile. Give me both links.
The template the AI must fill at the end of the market research, whatever the brand. Every line points back to a source ad.
| # | Angle | The idea | Weight |
|---|---|---|---|
| A1 | [Short angle name] | [The reframed problem + the mechanism that explains it, in 2-3 sentences] | [# ads · copies · run time] |
| A2 | [Angle 2] | […] | […] |
| A3 | [Angle 3 — often "us vs them"] | […] | […] |
| A4 | [Angle 4 — often an advertorial / comparison test] | […] | […] |
| A5 | [Angle 5] | […] | […] |
One line each. Common leads: results timeline (day 3 / 7 / 14 / 30), origin or heritage, scarcity and authenticity, alternative mechanism, the expert who let the customer down.
Word for word, in the ad's language, with the source ad and its angle.
Age, gender, situation, visible problem, what they've already tried and how much they've spent, everyday shame behaviors.
The concrete everyday proof they would notice themselves (a piece of clothing, a gesture, a reaction from people around them).
Static / video split, then the dominant formats mapped to the skill's 21 formats.
Price, subscription, guarantee, social proof shown. Weaknesses quantified with TrendTrack: traffic, number of active ads, trend.
The 3 angles and 10 headlines our brand should attack first.
Once steps 1 to 4 are done, there is nothing left to research. You drop new concept templates, and the AI clones them using everything already built: same angles, same headlines, same avatar, same product. No new research, no TrendTrack.
At the end of the first run, the AI saves everything in one place. This is what it reloads for every new batch.
Save the brand kit for [BRAND] in a single folder: [BRAND KIT FOLDER]. It must contain: - the final market research report (angles, headline bank, video hooks, avatar); - the product sheet (exact price, offer, guarantee, allowed claims, banned words); - the product reference photo; - the list of every creative already produced: concept · angle · headline · JSON · image. This kit is the only source for every future batch.
New batch for [BRAND]. 1. Reload the brand kit: [BRAND KIT FOLDER]. Do NOT research anything new, do NOT use TrendTrack: the angles, headlines, avatar and product sheet are locked. 2. Here are the new concept templates I picked: [NEW TEMPLATES FOLDER]. Accept every one of them, whatever the concept or niche. 3. Sort them into concept families, then work concept by concept. 4. Inside each concept family, spread the kit's winning angles across the templates so every family covers every angle. 5. For each template: copy its structure 1:1 (layout, text hierarchy, visual format, type of proof, product placement) and adapt it to [BRAND] on its assigned angle, with headlines from that angle's bank (rewritten, aggressive, conversion-driven). One ad per template. 6. Skip any combination already in the list of creatives made. 7. One JSON per creative with the ad-blueprint-gpt-image-2 skill, then generation with GPT Image 2 (quality high, 1:1) and QC by an agent (step 3). 8. Add the new creatives to the comparison site (each ad side by side with its template) and the demo link (step 4), and add them to the brand kit's list. Start with the first concept family and show it to me before running the rest.