Hire an AI buyer research image ad maker

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• A buyer sheet showing which insights are backed and which are only hunches
• A list of reasons to buy with the proof for each, and the ones it cut
• A plan of the set by ad type and look, then a concept per ad with headline options and word counts
• After your approvals, the finished ads and a table of what each one tests

How it does the job well

• Start from the user's task and the content, then the layout. Decoration comes last.
• Design every state: empty, loading, error, long text and mobile.
• Keep one visual system. Reuse spacing, type and colour tokens instead of one-off values.
• Check text contrast (at least 4.5:1 for body text) and keyboard focus as you go.

Mistakes it avoids

• Type made inside a generated picture.
• A discount on a product shot as the plan for winning strangers.
• Six looks of one claim counted as six ads.
• Letting the AI pick the arguments when the owner hasn't approved ahead. When they have, pick by the rules and mark the stop "(approve)".
• Designing only the happy path at desktop width.
• Copying a reference's logo, text or claims instead of learning from its structure.

What a good result looks like

An example, not your task: You're launching to a new audience and need a first set that tests real differences, not six colours of one ad.

• Sources. What counts as a source for this run, so every claim can be traced back.
• Buyer sheet. Each buyer's insights with their sources, and the hunches left out because too few buyers said them.
• Reasons to buy. Each reason with buyer, problem, what only this product does and proof, plus the ones cut or merged.
• Stop 1. A pause where you pick which reasons to turn into ads.
• The set on the map. Each ad placed by ad type and look, with a note on how varied the set is.
• Concepts. For each ad: the picture, which product photo it uses, headline options with word counts, and a support line.

How the work is checked

• Every used insight has 3 buyers, or 1 buyer and a result. Hunches stay out of copy.
• "Why now?" types are at most 1 in 5, and a batch of 6 or more has 3 types and 2 dresses.
• No two ads share a code and an argument.
• Both stops were shown to the owner, or marked "(approve)" when they said go ahead or asked to run in one go.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

A second opinion

Before it hands back, your AI reviews the draft the way John Caples and Eugene Schwartz would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Builds the buyer sheets. Uses this workflow's own research step. An insight needs three separate buyers, or one buyer and a past ad that beat your usual cost per sale.
• Lists reasons to buy. Writes more reasons than ads, cuts any a rival could say word for word, and stops so you can pick (stop 1).
• Spreads the set. Places each ad on a map of nine ad types and three looks, with discount and deadline ads at one in five or fewer.
• Plans each concept. Uses a skill that plans an image ad around the buyer's problem to set each picture, then stops for the concepts and the first picture of each look (stop 2).
• Writes the words. Uses a skill that writes every word an image ad needs. Headlines are 7 words or fewer and trace to the buyer sheet.
• Checks every finished ad. Uses a skill that finds flaws in finished ads to check type, claims, the product against its photo, and that the brand shows with the logo covered.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id scroll-stopping-image-ads only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/scroll-stopping-image-ads/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• Your brand facts, approved claims, voice, colours and never-say list
• Customer reviews, comments or survey answers, with where each came from
• Product photos, named by what each shows (front, in hand, in use)
• How many ads and which sizes
• Past ad results with cost per sale (optional)

Helpful context (optional)

• Support tickets or survey answers, so more insights reach the three-buyer bar
• Cost per purchase for each past ad, so a single review backed by a result can count
• Photos of the product in real use, so In use and The moment ads don't need staged scenes
• Your typeface files and logo as an SVG, so the type layer matches your brand

Tools and access

• Claude: Keeps track of a long workflow with stops, and holds every fact and source you gave it.
• GPT Image: Follows detailed scene prompts and takes several product reference photos at once.
• Nano Banana: Good with many reference images and with lighting on shiny packs.
• Figma: Sets real type over each picture and keeps the batch in one file.
• GPT Image: Keeps your real product close to its reference photo, and sets short headlines better.
• Nano Banana: Takes up to 6 product photos and is Google's pick for brand consistency, so the product and colours stay true.
• Any good chat AI: Writing to field limits from your proof works well in any strong chat AI.
• Meta Ads Manager: Its ad preview shows where the main text and headline get cut off on each placement.
• Claude: Reads full-size images closely, so it can spell-check the words in the picture and spot the safe zones.
• Meta Ads Manager: Its safe zone guardrail marks the area the app's buttons and labels won't cover, so you see what might get hidden.

Functions and deliverables

• Buyer research image ad maker: Share brand facts, customer evidence and exact product photos. Get varied ad arguments, concepts, image files or prompts and a check record.
  • A buyer sheet showing which insights are backed and which are only hunches
  • A list of reasons to buy with the proof for each, and the ones it cut
  • A plan of the set by ad type and look, then a concept per ad with headline options and word counts
  • After your approvals, the finished ads and a table of what each one tests
• Visual twist image ad maker: Turn a buyer's own words into one image ad with a single twist. You get the headline, layout notes and an image prompt to paste into your image tool.
  • A concept card with the one thought, the moment, the twist and the unexpected-and-relevant check
  • A headline with its job, a support line and the line under the image
  • Layout notes and how to draw the product from your photo
  • An image prompt ready to paste, plus a MISSING list
• Image ad copy writer: Get every word your image ad needs, on the picture and around it, in two or three versions that each test a different appeal.
  • For each version, the headline and support line on the image, main text, headline under the image, description and button, with counts
  • A note naming the ad type, what the buyer knows and the appeal each version tests
  • A story for the main text, if you asked for one
• Pre-launch ad checker: Share your ad, audience and approved facts. Get located issues, fixes, human checks and a custom score before launch.
  • A version-bound list of observed problems and the smallest fixes
  • The buyer argument checked against the supplied facts and proof
  • A clear list of media, destination, tracking or spec checks still needed
  • A scoped verdict and observed/eligible coverage
  • An internal editing score, with any post-fix score marked provisional
• Brand profile builder: Share your website. Get a reusable profile covering your products, customers, voice and approved claims, with sources.
  • A folder of eight plain files, from a start file for your AI to a claims list and a change log
  • A tag on every fact, and every claim marked approved, pending or banned
  • A two-sentence diagnosis of your biggest gap, and a list of what's missing and who can answer it
  • A short slice for your next step, if you name one
• John Caples: Write headlines and plan a fair ad test through John Caples’s recorded approach. Lead with the reader’s gain and count replies by version.
  • Your problem worked on the way John Caples would: their questions, their method, their push-back
  • The answer or the work, in John Caples's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step
• Eugene Schwartz: Match a headline or sales page to what buyers already want and know. Apply Eugene Schwartz’s recorded approach to research, claims and proof.
  • Your problem worked on the way Eugene Schwartz would: their questions, their method, their push-back
  • The answer or the work, in Eugene Schwartz's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• You're launching to a new audience and need a first set that tests real differences, not six colours of one ad.
• Your best ads open on the product or a discount and strangers scroll past them.
• You have lots of reviews but no clear idea which reasons to buy are worth an ad.

Limits to check before starting

• You have no customer reviews, survey answers or product photos yet. Gather those first, or build your brand facts with the Brand profile builder.
• You only need the words for one ad. Ask your AI for headline options, or use the Image ad copy writer.
• You want to check an ad you already made. Use the Pre-launch ad checker.
• Your ads make health, body or money claims and you have no approved wording for them. Get the claims approved first, because the platform's ad policy applies.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Start a chat with the skill. Open it if you added it to your AI, or copy it and paste it in.
• Paste your brand file, then your reviews and any past ad results underneath.
• List the product photos you actually have and what each one shows. Say plainly if you only have one or two.
• Say how many ads and which sizes, for example "4 ads, 4:5 and 9:16".
• It pauses twice so you can pick the reasons and approve the concepts. Say "go ahead" at the start and it does both stops for you, marking each one (approve).

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/scroll-stopping-image-ads for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.