AI Prompt Library

Act as a generative search analyst. For the brand [BRAND] in [INDUSTRY], list how you would describe it, which competitors you'd recommend alongside or instead of it, and what information you're missing that would make you recommend it more confidently.

Act as a content strategist. For [TOPIC], propose a pillar page plus 8 supporting articles, each mapped to a specific buyer question and the AI engine most likely to surface it.

Compare [BRAND] against [COMPETITOR 1] and [COMPETITOR 2] for the query "[BUYER QUERY]". Which would you recommend first and why? What would [BRAND] need to change to be recommended first?

Act as a buyer-research analyst. For a company selling [PRODUCT/SERVICE] to [AUDIENCE], list the 25 questions buyers most likely ask AI assistants across awareness, comparison and decision stages — then flag the 5 questions my brand must win to be recommended, and why.

Act as a GEO editor. Rewrite the following post so AI engines can extract and cite it: add a 40–60 word answer-first summary, convert key points into clear factual claims, add an FAQ block for the 3 most likely follow-up questions, and flag any claim that needs a source or statistic. Post: [PASTE CONTENT].

Act as a generative search analyst. For the query [QUERY], compare [MY BRAND] and [COMPETITOR]: which would you recommend and why, what evidence or signals favour them, and what specific content, data or third-party proof would change the recommendation in my favour?

Act as a GEO strategist. For [BRAND] in [INDUSTRY] targeting [AUDIENCE], build a 90-day content calendar to grow AI visibility: 12 pieces, each with target question, format (comparison, FAQ, data study, guide), the AI engines it targets, and the order to publish for fastest compounding authority.

You are an AEO specialist. Generate 10 natural-language questions a buyer of [SERVICE] would ask an AI assistant, with concise, citable answers (under 60 words each) written in a neutral, factual tone.

Turn this case study into an AI-citable format: a one-sentence outcome, the problem, the solution, and 3 quantified results, each as a standalone factual statement.

Act as an answer engine optimizer. For the question [QUESTION], write a 40–60 word direct answer optimised to be quoted by AI engines, then a 200-word supporting explanation, 3 related questions with short answers, and the FAQPage schema for all of it.

Act as an AEO analyst. Starting from the question [QUESTION], map the follow-up questions a user would ask an AI assistant next — 3 levels deep. Group them into themes, mark which my existing pages answer ([LIST PAGES]), and identify the gaps competitors could win.

Act as an AEO editor. Review this page for Google AI Overviews eligibility: check answer-first structure, heading hierarchy, question coverage, scannable claims and schema opportunities. Return a prioritised fix list, then rewrite the opening 150 words. Page: [PASTE CONTENT/URL].

Generate valid schema.org JSON-LD for a [PAGE TYPE] page about [SUBJECT], including the properties most useful for rich results and AI ingestion.

Act as a technical AI-SEO specialist. Generate an llms.txt file for [SITE URL]: summarise what the business does in one paragraph, list the key pages AI systems should prioritise ([LIST KEY PAGES]) with one-line descriptions, and note any sections to de-prioritise. Follow the llms.txt convention and keep it under 60 lines.

Act as a technical SEO auditor. For [SITE URL], produce an AI-crawlability checklist: robots.txt rules for GPTBot, Google-Extended, PerplexityBot and ClaudeBot; whether key content renders without JavaScript; sitemap health; canonical and hreflang sanity; and structured-data coverage. Rank findings by what most limits AI visibility.

Act as an automation consultant. For the workflow [DESCRIBE WORKFLOW], break it into discrete steps, identify which steps an AI agent can own, and recommend the tools and triggers to automate it end to end.

Act as an AI automation architect. Design a lead-qualification agent for [BUSINESS TYPE]: the questions it asks, the scoring rules for [IDEAL CUSTOMER CRITERIA], when it routes to a human, what it writes to the CRM, and the guardrails that stop it over-promising. Output as a build spec I can hand to a developer.

Act as an automation consultant. For leads arriving via [CHANNEL], design a follow-up sequence: timing and channel for each touch over 14 days, message intent per touch, the personalisation data to pull from [CRM/TOOL], exit conditions, and which steps an AI agent can write versus a human should approve.

Act as an operations automation specialist. Design an automated weekly report for [BUSINESS/TEAM] pulling from [TOOLS/SOURCES]: the 5–8 metrics that matter, how to detect anomalies worth flagging, a plain-English summary template an AI should draft, and the trigger/delivery setup (schedule, channel, owner).

Write a service page for [SERVICE] following this structure: outcome-focused hero, the business challenge, our solution, what's included, benefits, a 6-step process, why choose us, 8 FAQs, and a final CTA. Keep it jargon-free and benefit-led.

Act as a conversion copywriter. Write a comparison page for [MY PRODUCT] vs [COMPETITOR]: honest feature-by-feature table, who each option genuinely suits, an answer-first verdict AI engines can quote, objection-handling FAQ, and a CTA. Fair enough to be citable, persuasive enough to convert.

Act as a content strategist. From these support conversations — [PASTE TICKETS/QUESTIONS] — extract the questions customers actually ask, group duplicates, and write clear 40–80 word answers in our brand voice for the top 10. Flag which belong on product pages versus a help centre, and which deserve a full article.

Act as a local search analyst. For a [BUSINESS TYPE] in [CITY/AREA], list the questions locals ask AI assistants when choosing a provider, describe how you would answer each today, which local competitors you'd name, and what information about [BUSINESS NAME] is missing or inconsistent that stops you recommending it.

Act as a local GEO copywriter. Write a service-area page for [SERVICE] in [CITY/AREA]: answer-first intro naming the area served, locally specific proof points, an FAQ block with the 5 questions locals actually ask, and the LocalBusiness schema fields the page should carry. Avoid generic filler that could describe any city.

Act as a Google Business Profile specialist. For [BUSINESS NAME], category [CATEGORY], review this profile info: [PASTE DETAILS]. Identify gaps and inconsistencies versus my website and directories, rewrite the business description for AI extraction, and list the attributes, services and Q&A entries to add — prioritised by impact on AI recommendations.

Act as an eCommerce GEO copywriter. Rewrite this product description so AI shopping assistants can extract and compare it: lead with what it is and who it's for, state specs as clear attribute–value pairs, cover the top 3 buyer questions, and keep the persuasive tone for human readers. Product: [PASTE DESCRIPTION].

Act as a structured-data auditor. For this product page markup — [PASTE JSON-LD/HTML] — check Product, Offer, AggregateRating and Review coverage against what AI shopping surfaces require: price, availability, GTIN/MPN, shipping and returns. List what's missing or invalid, ranked by impact, with corrected JSON-LD for the top 3 fixes.

Act as an AI shopping analyst. For the query “best [PRODUCT TYPE] under [PRICE]”, explain what attributes, proof and sources an AI assistant uses to build its shortlist, assess how [MY PRODUCT] scores on each today, and give me the 5 highest-impact changes to product data, reviews or content to make the list.