Hire an AI flaw-first image ad reviewer

Everything it can hand back

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

• A flaw-first ad and a set of hooks that name the flaw and turn it
• A picture brief and image prompt that match the story, with a runner-up to test
• A caption line for the picture
• A check of the words and picture together, with a verdict

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

• Designing only the happy path at desktop width.
• Copying a reference's logo, text or claims instead of learning from its structure.
• Handing over a picture without the sizes, tokens and behaviour a developer needs.

What a good result looks like

An example, not your task: Buyers keep raising the same flaw in reviews and your ads avoid it.

• Flaw-first ad. Your true weaknesses, the one buyers see, a flat and a plain version, the ad copy and hooks.
• Picture. The quoted moment the old way stopped working, the picture type, an image prompt, a caption and a runner-up.
• Check. Findings on shape, first second, claims against your proof, and a verdict on words and picture together.
• Pause. A stop where you make both pictures and run them as a small test.
• Hand-back summary. Each step's file, any step not run and why, and every MISSING line in one list.

How the work is checked

• Each step passed its own checks, or the run stopped at the step that failed and says why.
• The steps ran in order, and each one used the result of the one before.
• Nothing was invented to fill a gap. Every gap is a MISSING: line.
• Nothing was sent, published or paid for without a clear yes.
• 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 Joseph Sugarman and Bill Bernbach would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Write the flaw-first ad. Lists your true weaknesses, picks the one buyers see, writes the flat claim and then the plain version, and checks the line holds in real use.
• Pick the picture that fits the story. Quotes the moment the old way stopped working, asks where it shows and writes the image prompt, a caption and a runner-up.
• Check the ad and picture together. Reads shape, first second, claims and proof, and gives a verdict on the words and picture as one ad.
• Pause to make the pictures. You make the first picture and the runner-up in your image tool and run both as a small test.

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 turn-a-flaw-first-ad-into-a-checked-picture-ad 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/turn-a-flaw-first-ad-into-a-checked-picture-ad/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

• A brief with your buyer and goal
• Your product facts, including what it does not do well
• Review lines that mention the flaw (optional)
• Rival claims (optional)
• Your brand file and buyer notes (optional)

Tools and access

• Any good chat AI: Sorting weaknesses and rewriting lines is text work any strong chat AI does well with this skill.
• Any good chat AI: Choosing the picture is reading and judgement, which Claude, ChatGPT and Gemini all handle well.
• Nano Banana: Google's image model, which Google recommends for accurate words in a picture, as notes and chats need.
• Meta Ads Manager: Its A/B test shows the chosen picture and the runner-up to separate groups under the same story.
• 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

• Flaw-first image ad reviewer: Share product facts and a real weakness buyers mention. Get honest ad copy, matching picture ideas and a review before testing.
  • A flaw-first ad and a set of hooks that name the flaw and turn it
  • A picture brief and image prompt that match the story, with a runner-up to test
  • A caption line for the picture
  • A check of the words and picture together, with a verdict
• Flaw-first ad writer: Write an ad that names your product's real flaw first, then shows what it proves. Give it your facts and brief. You get ad copy and hooks.
  • A list of true weaknesses, with the one chosen and why
  • Ad copy that states the flaw first and turns it
  • Hooks built on the same turn
  • A note on what in the product backs each line
• Story ad visual style planner: Paste a story ad. Get the picture style that fits its key moment, a ready image prompt, a runner-up to test and a caption.
  • The key moment, quoted from your story
  • The picture style chosen and why, plus a runner-up from a different kind of evidence
  • The full brief with a ready-to-paste image prompt
  • The line under the picture, about 27 characters, with its count
  • A one-line test plan, and one line for each check the brief missed
• 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
• Joseph Sugarman: Build a story-led product page through Joseph Sugarman’s recorded approach. Keep readers moving, state the drawback and plan a small test before rollout.
  • Your problem worked on the way Joseph Sugarman would: their questions, their method, their push-back
  • The answer or the work, in Joseph Sugarman's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step
• Bill Bernbach: Develop an honest ad idea using Bill Bernbach’s recorded approach. Pair words and pictures, find one true selling point and cut the gimmicks.
  • Your problem worked on the way Bill Bernbach would: their questions, their method, their push-back
  • The answer or the work, in Bill Bernbach'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

• Buyers keep raising the same flaw in reviews and your ads avoid it.
• You want a picture ad that stands out without any new claim.
• You want to test two picture ideas for the same story.

Limits to check before starting

• Buyers never raise a flaw about your product: use the Ad angle planner to find a plain angle instead.
• You only need the words of an ad: use the Ad hook writer or the Ad headline writer.
• You already have an ad and picture and only want a final check: use the Ad claims checker.

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.

• Download the handoff pack. It holds HANDOFF.md and the 3 skill files in the order they run: Flaw-first ad writer, Story ad visual style planner and Pre-launch ad checker.
• Give the folder to Claude (in Claude Code, or as files in a Claude Project) and say "Follow HANDOFF.md".
• Paste your product facts and the weaknesses buyers mention. Do not hide any.
• Read the check before you make the pictures.
• When it pauses, make both pictures in your image tool and run them as a small test.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/turn-a-flaw-first-ad-into-a-checked-picture-ad 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.