Plan any piece of marketing copy before you write it, whether it's an ad, a landing page, a sales page or sales letter, an email, a subject line, a social post, a headline or a video script. Give it the goal, the reader and the offer, and it tells you which of the nine questions every reader silently asks this piece has to answer, which ones deserve the most words for this reader, and a few ways to answer each one, drawn from real advertising and linked to the Persuasion Taxonomy. One option is always the established move and the rest are less expected, because left to itself a model answers every question with the move everyone else makes, and readers have learned to skim past it. So call it before you draft, even when you're sure you know how to write the piece, and when the draft is done, check it with diagnose_marketing_copy.

Review, critique or roast any piece of marketing copy, whether it's an ad, a landing page, an email, a sales page, a social post or a script, and find out why it might not persuade. Before you call it, read the copy and label each line with the one reader question it mainly answers, quoting the words exactly. Those labels go in the moves array. You get back which of the nine questions the copy answers for its goal, which it answers weakly and which it skips, along with the biggest gap and what readers do when it is missing. It also checks the order, whether the answers agree with each other, and the craft, pointing to the exact words that read as machine-written, like em dashes, "it's not X, it's Y" lines and sentences that all run the same length. Then it checks the opening line and suggests techniques from the catalog to fill the gap. Use it before you show anyone a draft you wrote, and whenever someone asks "is this good?", "roast this", "what's wrong with this copy?" or "how do I make it better?"

Work out why an ad, a landing page, an email or a whole funnel isn't converting. Start from what you can see. Maybe people don't click (a low CTR), or they click and bounce, or they read and don't buy. Maybe they abandon the checkout or the form, the leads never buy, customers buy once and leave, or emails don't get opened or get opened and nobody clicks. Whatever the symptom, you get back the reader questions most likely going unanswered, what to check in the copy first, and the problems copy can't fix that you should rule out, along with techniques to try and the test that would confirm the diagnosis. So use it whenever someone says their marketing "isn't working", "isn't converting" or "isn't selling", or asks why results dropped.

Search the Persuasion Taxonomy, 766 named persuasion techniques documented from real advertising and organized by the nine reader questions they answer. Describe what you want the copy to do, like build trust without testimonials, create urgency without fake scarcity, handle a price objection, make an opening less generic, prove a claim or reframe a problem. It finds the techniques that do it. Each one comes with its name and ID, a one-line definition, a real example, how common it is in a category if you name one, and a link. So reach for it when a draft relies on the obvious move and you want a less expected one, or when someone asks for tactics, angles, hooks or ideas.

Look up one persuasion technique by its ID (like PT-PRV-10000), its slug or its name. You get the full definition, why it works, when it lands and when it backfires, real examples from advertising, related and opposite techniques, and a link you can cite. Use it before you apply or recommend a technique so you get it right, and whenever someone asks what a tactic is called or how it works.

Check headlines, email subject lines, ad openings, video hooks, social post openings and first lines, and compare options against each other. For each line it tells you whether the line does its job in that spot, meaning which of the nine reader questions it answers, and whether a competitor could send it unchanged. It also shows exactly what a reader sees before the cutoff, flags anything that fails outright, and brings in evidence from thousands of real headline tests. Then it tells you what each option is betting on and which two to test. Before you call it, list the reader questions each line answers and quote the exact words doing the work. Use it whenever you write headlines, hooks or subject lines, whenever you have to choose between them, and whenever someone asks "which one is best?" You won't get a score out of ten. Nobody can predict a winner from the words alone, and that includes this tool.

Check whether marketing claims and calls to action are specific enough to believe. It catches the vague superlative, like "the best" or "#1", that readers discount on sight. It catches promises with no proof behind them and results with no mechanism, and it flags the generic buttons everyone uses, like "Learn more" and "Get started". Then it tells you how to fix each one. Use it when you write or review claims like "results in days", "trusted by thousands" or "the #1 tool", and for any button text. For headlines, check_headlines does the full job.

Plan an A/B test for marketing copy. Give it the current conversion rate, the smallest lift worth detecting and the daily traffic, and it tells you how many visitors each version needs and how many days to run. It also frames the test as two different answers to the same reader question, so the result teaches you something you can reuse, and not just that "B won". Use it when someone asks how long to run a test, how much traffic they need, whether a test is worth running, or what to test next.

Read the result of an A/B test. You get each version's conversion rate and lift, whether the difference is statistically significant, the confidence interval, and the chance each version really beats the original. It also warns you about the things that make a test result lie. Those include too few conversions, traffic that didn't split the way it should (a sample ratio mismatch), stopping the moment it looked good, and testing too many versions at once. So use it whenever someone shares test numbers, or asks "did my test win?", "is this significant?", "which version won?" or "should I keep it running?"