AEO & GEO skill 09 of 13
Earning Citations and Mentions for AI Answers SKILL.md
The Earning Citations and Mentions skill makes Claude, Codex or another AI agent get a brand named in AI answers the honest way. It builds a citation map from real prompts, finds which review platforms, comparison articles, media, communities and videos engines draw on, creates assets worth citing, plans authentic outreach and community participation, and keeps a risk register of tactics to avoid.
ai-citation-earning/SKILL.md, version 1.0.0, 1,301 words.
By Afeez Adebayo, Marketing, SEO & Growth Expert with 10+ years of experience.
Created 10 October 2026. Updated 10 October 2026. Free to use under CC BY 4.0.
Ask an AI assistant "what's the best accounting software for a small agency?" and the answer is built from many voices: review sites, comparison articles, forums, videos, media and vendor pages. A brand that only talks about itself on its own site rarely makes those lists. A brand that independent sources discuss, accurately and in context, usually does. [Consensus, from citation studies by Ahrefs, Semrush, Profound and others]
This skill finds the sources AI answers draw on for your topics and builds an honest plan to be present in them.
Operating principles
- Find the sources first. Collect what engines actually cite for your prompts before pitching anyone.
- Authentic only. Google states that seeking inauthentic mentions isn't as helpful as it might seem and that spam systems also protect AI features. [Confirmed] Fake reviews, planted forum posts and paid placements in "best of" lists risk penalties, removals and public embarrassment.
- Give sources a reason. Original data, expert commentary, useful tools and real customer outcomes get mentioned; announcements rarely do.
- Accuracy over volume. One accurate, detailed mention on a source engines trust beats many thin ones.
- Think in topics. The aim is "[brand] + [topic]" in the same context, repeatedly, across independent sources.
Source types AI answers draw on
| Source type | Examples | How to be present |
|---|---|---|
| Review and comparison platforms | G2, Capterra, Trustpilot, app stores, niche directories | Complete profiles, invite real customers to review, respond to reviews |
| Editorial comparisons | "Best X for Y" articles by publishers | Offer accurate product info, demos and data; never pay for ranking |
| Industry media | Trade publications, newsletters, podcasts | Original data, expert commentary, contributed articles |
| Communities | Reddit, Stack Exchange, Quora, industry forums, LinkedIn | Staff with clear affiliation answering questions helpfully |
| Video | YouTube reviews, tutorials, webinars | Your own tutorials, creator partnerships disclosed properly |
| Reference | Wikipedia, Wikidata, standards bodies, academic work | Only via notability and proper processes |
| Partners and customers | Integration directories, case studies on customer sites | Joint content, accurate partner listings |
When to use, and when not to
Use it when competitors dominate "best X" and "X vs Y" answers, when the brand is accurate but rarely mentioned, when launching into a new category, and when digital PR needs a measurable goal.
Don't use it to fix access or wrong facts on your own site (ai-crawler-access, brand-accuracy-ai-answers).
Inputs to ask for, in one message
- The prompt set and the baseline results, including cited URLs.
- Competitors that appear in answers.
- Assets available: data, experts, customers willing to speak, tools.
- Existing review profiles and their state.
- PR and community resources available each month.
Raw SKILL.md file
This is the exact file agents read, including the credit header and licence notice. Save it as ai-citation-earning/SKILL.md.
--- name: ai-citation-earning description: "Get named in AI answers by earning authentic, accurate mentions on the sources engines cite: build a citation map from real prompts, find gaps on review platforms, editorial comparisons, media, communities and video, create citable assets such as original data, run honest outreach and community participation, and track mentions and cited-source presence with a risk register for tactics to avoid. Use whenever someone asks how to get mentioned in ChatGPT or Perplexity recommendations, 'best X' AI answers, digital PR for AI search, brand mentions for LLMs, Reddit or review sites for AI visibility, or how competitors get cited." license: CC-BY-4.0 metadata: author: Afeez Adebayo author_url: https://afeezadebayo.com author_linkedin: https://www.linkedin.com/in/afeez-adebayo/ author_x: https://x.com/za_icon source: https://afeezadebayo.com/skills-md/marketing/aeo-geo/ai-citation-earning/ category: marketing subcategory: aeo-geo version: "1.0.0" created: "2026-10-10" updated: "2026-10-10" --- # Earning Citations and Mentions for AI Answers Ask an AI assistant "what's the best accounting software for a small agency?" and the answer is built from many voices: review sites, comparison articles, forums, videos, media and vendor pages. A brand that only talks about itself on its own site rarely makes those lists. A brand that independent sources discuss, accurately and in context, usually does. [Consensus, from citation studies by Ahrefs, Semrush, Profound and others] This skill finds the sources AI answers draw on for your topics and builds an honest plan to be present in them. ## Operating principles 1. **Find the sources first.** Collect what engines actually cite for your prompts before pitching anyone. 2. **Authentic only.** Google states that seeking inauthentic mentions isn't as helpful as it might seem and that spam systems also protect AI features. [Confirmed] Fake reviews, planted forum posts and paid placements in "best of" lists risk penalties, removals and public embarrassment. 3. **Give sources a reason.** Original data, expert commentary, useful tools and real customer outcomes get mentioned; announcements rarely do. 4. **Accuracy over volume.** One accurate, detailed mention on a source engines trust beats many thin ones. 5. **Think in topics.** The aim is "[brand] + [topic]" in the same context, repeatedly, across independent sources. ## Source types AI answers draw on | Source type | Examples | How to be present | |---|---|---| | Review and comparison platforms | G2, Capterra, Trustpilot, app stores, niche directories | Complete profiles, invite real customers to review, respond to reviews | | Editorial comparisons | "Best X for Y" articles by publishers | Offer accurate product info, demos and data; never pay for ranking | | Industry media | Trade publications, newsletters, podcasts | Original data, expert commentary, contributed articles | | Communities | Reddit, Stack Exchange, Quora, industry forums, LinkedIn | Staff with clear affiliation answering questions helpfully | | Video | YouTube reviews, tutorials, webinars | Your own tutorials, creator partnerships disclosed properly | | Reference | Wikipedia, Wikidata, standards bodies, academic work | Only via notability and proper processes | | Partners and customers | Integration directories, case studies on customer sites | Joint content, accurate partner listings | ## When to use, and when not to Use it when competitors dominate "best X" and "X vs Y" answers, when the brand is accurate but rarely mentioned, when launching into a new category, and when digital PR needs a measurable goal. Don't use it to fix access or wrong facts on your own site (`ai-crawler-access`, `brand-accuracy-ai-answers`). ## Inputs to ask for, in one message 1. The prompt set and the baseline results, including cited URLs. 2. Competitors that appear in answers. 3. Assets available: data, experts, customers willing to speak, tools. 4. Existing review profiles and their state. 5. PR and community resources available each month. ## Workflow ### Step 1. Build the citation map Run the prompts in each engine and collect every cited URL. Group by domain and source type. Count how often each appears and which competitors they mention. ### Step 2. Find the gaps For each frequently cited source, note whether you're mentioned, mentioned wrongly, or missing, and what it would take to be included accurately. ### Step 3. Prioritise sources Score by citation frequency, relevance to revenue prompts and feasibility. Usually: fix your own review profiles first, then editorial comparisons, then media and communities. ### Step 4. Create something worth citing | Asset | Why it works | |---|---| | Original survey or usage data | Journalists and engines cite numbers with sources | | Annual index or benchmark | Repeatable, referenced year after year | | Expert commentary on news | Fast, quotable, builds topic association | | Free tool or calculator | Linked and recommended in communities | | Customer outcomes with permission | Concrete proof for comparison writers | ### Step 5. Outreach Personal, specific pitches to editors of cited comparisons (corrections and new data), journalists covering the topic, podcast hosts and community moderators where appropriate. Offer facts, not demands. ### Step 6. Community participation Staff answer real questions with disclosed affiliation, link only when it helps, and never use sock-puppet accounts. ### Step 7. Measure Track new mentions, their accuracy and whether they appear among cited sources in the next prompt runs. ## Risk register | Tactic | Risk | |---|---| | Paying for placement in "best of" lists without disclosure | Misleading to readers; may breach advertising rules; spam signals | | Fake or incentivised reviews | Platform removals, legal action in some markets | | Undisclosed staff posts on Reddit | Bans and public backlash | | Self-published "top 10" lists ranking yourself first | Low trust with readers, editors and engines; easy to expose | | Mass guest posts for links | Link spam policies | ## Worked example A project management tool was absent from AI answers for "best project management software for agencies". The citation map showed 60% of citations came from five comparison articles, two review platforms and a popular Reddit thread. The team updated their review profiles and invited 200 real customers to review, sent comparison editors a short brief with current pricing and an agency-specific feature list, published an agency benchmark from anonymised usage data, and had their head of product answer agency questions on Reddit with clear affiliation. Three of the five comparisons added the tool, and mentions rose from 0 to 9 of 20 tracked prompts over a quarter. ## Output format ``` # Citation earning plan: <brand>, <topics>, <date> ## Citation map (domain, type, frequency, competitors named, our status) ## Priority sources and the ask for each ## Assets to create (owner, date) ## Outreach and community plan ## Risk notes ## Measurement: mentions, accuracy, appearance in cited sources ``` ## Pitch template for a comparison editor ``` Subject: Updated facts for your "[article title]" Hi [name], Your [article] is one of the clearest guides on [topic]. We noticed [our product] isn't included / is listed with [outdated fact]. Current facts (checked [date]): pricing [x], key features for [audience] [y], source links [z]. Happy to give you a demo account or answer questions. No pressure to include us; we just want readers to have accurate information. [name], [role] ``` ## Edge cases and judgement calls | Situation | What to do | |---|---| | Comparison editors ask for payment | Decline paid placement; offer facts and access instead, or treat it as clearly labelled advertising | | Negative reviews dominate a cited platform | Respond professionally, fix real issues and invite satisfied customers to review | | Competitors run fake reviews | Report through the platform; don't retaliate in kind | | No customers willing to be named | Publish anonymised outcomes with permission and clear methods | | Community bans self-promotion | Contribute expertise without links; respect the rules | ## Handoffs to related skills - Original data and citable pages: `answer-ready-content` - Accurate bios and facts: `entity-optimisation` - Correction requests: `brand-accuracy-ai-answers` - Measuring mentions: `ai-visibility-tracking` - Product reviews and comparisons: `ai-commerce-product-visibility` ## Quality bar: what an excellent plan includes - A citation map from real prompts across engines. - A specific, useful ask for each priority source. - Only authentic, disclosed tactics. - Success measured in accurate mentions on cited sources. ## Common mistakes - Pitching before knowing which sources engines cite. - Chasing links instead of accurate mentions. - Using undisclosed or fake accounts. - Announcing products instead of offering data or expertise. - Ignoring review profiles that engines cite often. ## Questions to ask before you plan - What data or expertise can the business share that others can't? - Which customers would speak publicly? - Who will own community participation, with disclosed affiliation? ## Self-check before you answer - Is the plan based on a citation map from real prompts? - Is every tactic authentic and disclosed? - Does each priority source have a specific, useful ask? - Is success measured in accurate mentions and cited-source presence? ## Official documentation - Google: generative AI features in Search, site owner guide (inauthentic mentions): https://developers.google.com/search/docs/fundamentals/ai-optimization-guide - Google spam policies: https://developers.google.com/search/docs/essentials/spam-policies - Google reviews system: https://developers.google.com/search/docs/appearance/reviews-system --- Created by Afeez Adebayo, Marketing, SEO & Growth Expert Website: https://afeezadebayo.com LinkedIn: https://www.linkedin.com/in/afeez-adebayo/ X: https://x.com/za_icon Source: https://afeezadebayo.com/skills-md/marketing/aeo-geo/ai-citation-earning/ Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). You may copy, share and adapt this skill, including for commercial use, as long as you credit Afeez Adebayo and link to the source URL above. Keep this notice in any copy or adapted version.
Workflow
Step 1. Build the citation map
Run the prompts in each engine and collect every cited URL. Group by domain and source type. Count how often each appears and which competitors they mention.
Step 2. Find the gaps
For each frequently cited source, note whether you're mentioned, mentioned wrongly, or missing, and what it would take to be included accurately.
Step 3. Prioritise sources
Score by citation frequency, relevance to revenue prompts and feasibility. Usually: fix your own review profiles first, then editorial comparisons, then media and communities.
Step 4. Create something worth citing
| Asset | Why it works |
|---|---|
| Original survey or usage data | Journalists and engines cite numbers with sources |
| Annual index or benchmark | Repeatable, referenced year after year |
| Expert commentary on news | Fast, quotable, builds topic association |
| Free tool or calculator | Linked and recommended in communities |
| Customer outcomes with permission | Concrete proof for comparison writers |
Step 5. Outreach
Personal, specific pitches to editors of cited comparisons (corrections and new data), journalists covering the topic, podcast hosts and community moderators where appropriate. Offer facts, not demands.
Step 6. Community participation
Staff answer real questions with disclosed affiliation, link only when it helps, and never use sock-puppet accounts.
Step 7. Measure
Track new mentions, their accuracy and whether they appear among cited sources in the next prompt runs.
Risk register
| Tactic | Risk |
|---|---|
| Paying for placement in "best of" lists without disclosure | Misleading to readers; may breach advertising rules; spam signals |
| Fake or incentivised reviews | Platform removals, legal action in some markets |
| Undisclosed staff posts on Reddit | Bans and public backlash |
| Self-published "top 10" lists ranking yourself first | Low trust with readers, editors and engines; easy to expose |
| Mass guest posts for links | Link spam policies |
Worked example
A project management tool was absent from AI answers for "best project management software for agencies". The citation map showed 60% of citations came from five comparison articles, two review platforms and a popular Reddit thread. The team updated their review profiles and invited 200 real customers to review, sent comparison editors a short brief with current pricing and an agency-specific feature list, published an agency benchmark from anonymised usage data, and had their head of product answer agency questions on Reddit with clear affiliation. Three of the five comparisons added the tool, and mentions rose from 0 to 9 of 20 tracked prompts over a quarter.
Output format
# Citation earning plan: <brand>, <topics>, <date>
## Citation map (domain, type, frequency, competitors named, our status)
## Priority sources and the ask for each
## Assets to create (owner, date)
## Outreach and community plan
## Risk notes
## Measurement: mentions, accuracy, appearance in cited sourcesPitch template for a comparison editor
Subject: Updated facts for your "[article title]"
Hi [name],
Your [article] is one of the clearest guides on [topic]. We noticed [our product] isn't included / is listed with [outdated fact].
Current facts (checked [date]): pricing [x], key features for [audience] [y], source links [z].
Happy to give you a demo account or answer questions. No pressure to include us; we just want readers to have accurate information.
[name], [role]Edge cases and judgement calls
| Situation | What to do |
|---|---|
| Comparison editors ask for payment | Decline paid placement; offer facts and access instead, or treat it as clearly labelled advertising |
| Negative reviews dominate a cited platform | Respond professionally, fix real issues and invite satisfied customers to review |
| Competitors run fake reviews | Report through the platform; don't retaliate in kind |
| No customers willing to be named | Publish anonymised outcomes with permission and clear methods |
| Community bans self-promotion | Contribute expertise without links; respect the rules |
Handoffs to related skills
- Original data and citable pages:
answer-ready-content - Accurate bios and facts:
entity-optimisation - Correction requests:
brand-accuracy-ai-answers - Measuring mentions:
ai-visibility-tracking - Product reviews and comparisons:
ai-commerce-product-visibility
Quality bar: what an excellent plan includes
- A citation map from real prompts across engines.
- A specific, useful ask for each priority source.
- Only authentic, disclosed tactics.
- Success measured in accurate mentions on cited sources.
Common mistakes
- Pitching before knowing which sources engines cite.
- Chasing links instead of accurate mentions.
- Using undisclosed or fake accounts.
- Announcing products instead of offering data or expertise.
- Ignoring review profiles that engines cite often.
Questions to ask before you plan
- What data or expertise can the business share that others can't?
- Which customers would speak publicly?
- Who will own community participation, with disclosed affiliation?
Self-check before you answer
- Is the plan based on a citation map from real prompts?
- Is every tactic authentic and disclosed?
- Does each priority source have a specific, useful ask?
- Is success measured in accurate mentions and cited-source presence?
Official documentation
- Google: generative AI features in Search, site owner guide (inauthentic mentions): https://developers.google.com/search/docs/fundamentals/ai-optimization-guide
- Google spam policies: https://developers.google.com/search/docs/essentials/spam-policies
- Google reviews system: https://developers.google.com/search/docs/appearance/reviews-system
On this page
- When to use this skill, and when not to
- Example prompts
- Example output
- What the agent needs from you
- How this skill hands off to related skills
- How to run the Earning Citations skill step by step
- Situations this skill handles
- What makes this skill different
- Practical tips from real projects
- Frequently asked questions
- Changelog
When to use this skill, and when not to
Use it when competitors dominate “best X” and “X vs Y” answers, when the brand is described correctly but rarely mentioned, when launching into a new category and when digital PR needs a goal you can measure.
Answers to recommendation questions are built from many voices. A brand that only talks about itself on its own site rarely makes the shortlist. Google’s guidance is explicit that seeking inauthentic mentions isn’t as helpful as it looks, because its AI features rely on the same quality and spam systems as Search. This skill only uses tactics that would survive public scrutiny.
Don’t use it to fix access or wrong facts on your own site (use AI Crawler Access or Brand Accuracy).
Example prompts
- “Build a plan to get into AI answers for best payroll software for startups.”
- “Collect every source ChatGPT and Perplexity cite for our 20 category prompts and group them.”
- “Which comparison articles mention our competitors but not us, and what should we send their editors?”
- “Design an original data study journalists and AI engines would cite.”
- “Write community guidelines for our team answering questions on Reddit with disclosure.”
Example output
The skill returns a fixed structure. A shortened example for an imaginary site:
# Citation earning plan: Example PM, agencies, 10 October 2026 ## Citation map (20 prompts, 4 engines) | Source | Type | Times cited | Competitors named | Us | | capterra.com/... | Review platform | 31 | 6 | Thin profile | | publisher.com/best-pm-agencies | Editorial | 24 | 5 | Missing | | reddit.com/r/agency/... | Community | 17 | 4 | Missing | ## Priority asks 1. Complete review profile; invite 200 verified customers 2. Send comparison editor current pricing and agency features 3. Publish agency benchmark from anonymised usage data
The plan starts from sources engines actually cite, so outreach goes where it can change answers rather than where it is easiest.
What the agent needs from you
The skill asks for the prompt set and baseline results with cited URLs, the competitors that appear in answers, the assets you can share (data, experts, customers willing to speak, tools), the state of your review profiles and how much PR and community time you have each month.
Research behind this skill
| Finding | Source | Label |
|---|---|---|
| Seeking inauthentic mentions isn’t as helpful as it might seem; AI features rely on quality and spam systems | Google Search Central, 2026 | Confirmed |
| Recommendation answers draw on review platforms, comparisons, communities and media | Citation studies by Ahrefs, Semrush and others | Consensus |
| Original data and expert commentary earn coverage more than product announcements | Digital PR practice | Consensus |
| Paid placement in lists without disclosure breaches advertising rules in many markets | Advertising regulators (for example ASA, FTC) | Confirmed |
How this skill hands off to related skills
Earned mentions build on and feed other skills. Original data comes from Answer-Ready Content, accurate bios and facts from Entity Optimisation, correction requests from Brand Accuracy, and results are measured with AI Visibility Tracking. Retailers apply the same approach to product reviews through AI Commerce.
How to run the Earning Citations skill step by step
- Install the skill as
ai-citation-earning/SKILL.md. - Share the prompt set and baseline, including every URL engines cited.
- Name competitors that appear in answers.
- List your assets: data, experts, customers willing to speak and free tools.
- Review the citation map and the specific ask for each priority source.
- Run outreach and community work with disclosure, then track new mentions and cited-source presence.
Situations this skill handles
Recommendation answers draw on many sources. The skill handles these situations:
| Situation | What the skill does |
|---|---|
| Competitors dominate “best X” answers | Maps the comparisons and reviews engines cite and plans inclusion |
| Thin review profiles | Completes profiles and invites real customers to review |
| Absent from a cited comparison | Sends the editor accurate, current facts and access |
| Reddit threads cited often | Has staff help with clear affiliation, following community rules |
| No news to pitch | Creates original data or expert commentary worth citing |
| Editors ask for payment | Declines paid placement or treats it as labelled advertising |
What makes this skill different
Most “get mentioned in ChatGPT” advice is either vague digital PR or manipulation: fake reviews, planted posts and paid list placements. This skill starts by collecting the sources engines actually cite for your prompts, then earns accurate, authentic mentions on them, with a risk register of tactics to avoid.
Google states that seeking inauthentic mentions isn’t as helpful as it might seem and that its AI features rely on the same spam systems as Search, so every tactic here is one you could defend publicly.
Practical tips from real projects
- Map before you pitch. Know which sources engines cite.
- Offer facts, not demands, to editors.
- Disclose affiliation in every community post.
- Measure accurate mentions on cited sources, not links.
A worked example: a project management tool was absent from AI answers for software for agencies. The citation map showed most citations came from five comparison articles, two review platforms and one Reddit thread. Updating review profiles, inviting real customers to review, briefing comparison editors, publishing an agency benchmark from anonymised usage data and answering Reddit questions with disclosure got the tool into three of the five comparisons and 9 of 20 tracked prompts within a quarter.
The best citable assets are repeatable: an annual index or benchmark gets referenced year after year by journalists, communities and AI answers alike.
Review platforms deserve early attention because engines cite them often and you control much of the profile. Complete every field, keep pricing and features current, respond to reviews and invite real customers on a steady schedule rather than in bursts.
Frequently asked questions
How do I get my brand recommended by ChatGPT or Perplexity?
Be present, accurately, on the sources they cite for your category: review platforms, independent comparisons, media and communities. Find those sources first by collecting citations from real prompts.
Does Reddit help AI visibility?
Reddit threads are often cited in AI answers. Helpful answers from staff with clear disclosure can help; undisclosed or fake accounts break Reddit’s rules and backfire.
Should I pay to be in "best of" lists?
Paid placement without disclosure misleads readers and may break advertising rules. Offer editors accurate information and data instead.
What assets earn citations?
Original surveys and usage data, annual benchmarks, expert commentary on news, free tools and real customer outcomes. Product announcements rarely earn mentions.
How do I measure citation earning?
Track new mentions and their accuracy, then check whether those sources appear among cited sources in your next prompt runs.
Is this just digital PR?
It uses digital PR methods but aims at a specific outcome: being on the sources AI engines cite for your prompts, described accurately.
Changelog
- 1.0.0, 10 October 2026: first release.
Use, adapt and share this skill under CC BY 4.0: credit Afeez Adebayo and link to this page.
All AEO & GEO skills
- AI Search Visibility Audit
- AI Visibility Tracking and Reporting
- Query Fan-Out and Prompt Research
- Answer-Ready Content for AI Search
- Google AI Overviews and AI Mode
- ChatGPT Search Visibility
- Perplexity, Copilot, Claude and Gemini Visibility
- Entity Optimisation for AI Search
- AI Crawler Access and Technical Readiness
- Brand Accuracy in AI Answers
- Agent Readiness for AI Browsers and Assistants
- Product Visibility in AI Shopping and Commerce
