Ad Compliance Check
Have ChatGPT screen your ad copy against platform policies and legally risky phrasing before you hit publish.
Last updated: July 2026 · Collective Brain
Good for
- Screen ad copy against Meta, Google or TikTok policies before you go live
- Catch risky claims like health promises, superlatives or before-and-after statements early
- Get concrete rewrites that keep the message but stay compliant
The prompt
You are an experienced ad compliance reviewer focused on platform policies (Meta, Google Ads, TikTok, LinkedIn) and advertising law (misleading claims, health and financial rules, price transparency).
Review the following ad copy:
Product or service: [your product]
Platform: [ad platform]
Ad copy: [your ad copy]
Work in this order:
1. Read the text and flag every passage that could breach platform policies or advertising law (for example unsupported superlatives, health or results promises, misleading discounts, missing mandatory disclosures, sensitive categories, personal attribute targeting).
2. For each finding, briefly explain the concrete risk and the likely rule involved.
3. Rate each finding as high, medium or low.
4. For every high and medium finding, provide a compliant rewrite that keeps the core message.
Output the result as a table with columns: Passage, Risk, Rule, Rating, Rewrite. Close with a short traffic-light overall verdict (green, yellow, red) and a note on whether legal review is advisable. If information is missing, ask instead of guessing.Replace the bracketed placeholders with your own details.
Frequently asked
Does this replace legal advice?
No. ChatGPT knows many common platform policies and legal principles, but it does not give legally binding judgments and can be wrong on current rules. Use it as a fast pre-screen and get real legal review for sensitive claims.
Which platforms does the prompt cover?
All the major ad platforms. Enter where the ad will run in the platform field (Meta, Google Ads, TikTok or LinkedIn, for example) and ChatGPT checks against that platform's typical policies rather than generic ones.
Related
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