Free AI citation grader

Free AI Citation Readiness Index

Paste any section of your brand copy and this tool scores how structurally ready it is to be cited by generative answer engines. It checks entity anchor density, verifiable claim frequency, opening-section structure, content block integrity, and semantic friction against hard benchmarks for your industry.

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What this free grader checks

Most website copy is written for human readers and optimized for keyword rankings. Neither of those goals prepares your content for the way AI answer engines actually work. Perplexity, Gemini, and SearchGPT do not rank pages by keyword frequency. They extract short blocks of text, score those blocks mathematically, and cite the ones with the highest structural density of named entities and verifiable facts.

This free grader applies five checks to your pasted text. First, it counts your entity anchor density: how many proper nouns, named tools, geographic areas, certifications, and methodologies appear per 100 words, and whether that number meets the benchmark for your industry. Second, it checks your verifiable claim ratio: the proportion of concrete data points (dollar figures, percentages, timelines, counts) relative to your total word count. Third, it runs a BLUF check on the first 20% of your text to confirm your brand name and primary service topic appear together early. Fourth, it slices your content into 150-word vector chunks and flags any that contain claims but no entity anchor, because those blocks get dropped by retrieval pipelines when extracted out of context. Fifth, it scores semantic friction: the number of vague marketing phrases that carry no weight in citation algorithms.

The score runs from 10 to 98, not 0 to 100. A perfect AI citation profile does not exist for real-world business copy, and a score of 10 means the text has essentially no structural retrievability. Scores above 66 indicate content a retrieval engine can confidently cite. Scores above 81 indicate copy engineered close to the theoretical maximum for citation probability.

Use this before you publish a new service page, rewrite your homepage, or ask us to refactor your copy for AEO. It runs entirely in your browser, produces a printable report, and requires no account.

Who this free grader is for

We built this for marketing leads, content strategists, and founders who need to know whether their brand copy is actually structured for AI answer engines, not just written well. If you manage a service page, a company bio, a case study library, or a product description set and you are not sure whether any of it gets cited by Perplexity, Gemini, or SearchGPT, start here. It takes two minutes, needs no account, and gives you a score you can act on the same day.

See our AEO services →

Common questions about AI citation and content structure

Straight answers about entity density, RAG pipelines, BLUF structure, and what actually makes brand copy citable by AI answer engines.

Is there a free AI citation checker for website content?
Yes. This grader is free and runs entirely in your browser with no account required. Paste any section of your brand copy, enter your business name and primary service topic, and select your industry. The tool checks five structural properties that AI answer engines use to decide whether to cite your content: entity anchor density, verifiable claim frequency, opening-section brand proximity, content block integrity, and semantic friction. Results appear in under three seconds with a score from 10 to 98, a highlighted text view, and three specific prescriptions for improving your score.
How do I check whether my website content gets cited by AI search engines?
Paste your content into this grader and look at two numbers: your entity density score and your vector chunk orphan count. Entity density tells you whether your text contains enough named entities for an AI engine to anchor it to a topic. Orphaned vector chunks tell you how many 150-word blocks in your text contain factual claims but no brand or entity anchor, which causes those blocks to be discarded during RAG retrieval. Fix those two problems and your citation probability increases measurably.
What is RAG and why does it affect my content?
RAG stands for Retrieval-Augmented Generation. It is the technical process that powers AI answer engines like Perplexity, SearchGPT, and Gemini. When someone asks a question, the engine does not read your whole website. It retrieves short text blocks from an index, scores them by relevance, and generates an answer from the highest-scoring blocks. If your content is not structured to score well in that retrieval step, it will not be cited regardless of how well-written or keyword-optimized it is.
What are entity anchors and why do AI engines use them?
An entity anchor is a proper noun or named thing: your company name, the city you serve, a certification you hold, a software platform you use, or a named methodology you follow. AI engines use entity anchors to place your content in a knowledge graph. Content without entity anchors is harder for machines to classify and less likely to be retrieved in response to a specific named query. This grader counts entity anchors per 100 words and compares that count to the benchmark for your industry.
What is BLUF writing and does it help with AI citation?
BLUF stands for Bottom Line Up Front. It means stating who you are and what you do in the first sentence rather than building up to it. For AI citation, BLUF matters because retrieval engines apply higher weight to the opening section of a page. If your brand name and core service topic appear together in the first 20% of your text, the engine has immediate confirmation of what the page is about. If they do not, the page is harder to classify. This grader checks whether your brand name and primary service topic appear within 30 words of each other in your opening section.
What is an orphaned vector chunk?
When a retrieval engine indexes your page, it slices the text into blocks of roughly 150 words. Each block is stored independently. If a block contains a verifiable claim (a percentage, a price, a timeline) but does not contain your brand name or any named entity, the engine cannot reliably attribute that claim to you when extracting it from context. The block becomes orphaned. This grader identifies orphaned blocks and tells you exactly which ones need an entity anchor added.
How is this different from regular SEO keyword optimization?
Keyword SEO is about matching the words in your content to the words in a user's search query. AI citation optimization is about structural density: how many proper nouns you name, how many verifiable facts you state, how early your brand identity appears, and whether every section of your text can stand alone as a citable block. A page can rank well for keywords while scoring poorly for AI citation, and vice versa. This grader measures the structural properties that retrieval engines weight, not keyword frequency.
What content types work best for AI citation?
Content that gets cited most often by AI answer engines shares four characteristics: it names specific entities rather than referring to generic categories, it states concrete facts with numbers rather than vague claims, it establishes the brand and topic early rather than building toward a conclusion, and it uses consistent entity anchors throughout rather than switching terms. Service page overviews, FAQ answers, case study summaries, and executive bios tend to score best because their format naturally supports these properties. Long-form blog posts often score lower unless they are structured with consistent brand mentions and verifiable claims throughout.

How the free AI Citation Readiness Index works

This grader evaluates whether your brand copy is structured for extraction by generative answer engines. It runs five deterministic checks: entity anchor density, verifiable claim frequency, opening-section brand presence, content block integrity, and semantic friction. The output is a structural score tied to hard benchmarks for your industry.

  1. Enter your brand name, primary search topic, and select the industry that best describes your business. These inputs set the scoring benchmarks and calibrate the entity detection.
  2. Paste any section of your website copy: homepage hero text, a core service page overview, an executive bio, a FAQ answer, a case study summary, or a product specification. Longer content blocks (150 to 1,000 words) produce the most complete analysis.
  3. The grader analyzes your text across five dimensions and returns an integer score from 10 to 98, a highlighted text view marking what was found and what was flagged, a prime citation snippet you can place in structured data, and three specific prescriptions for improving your score.

Why Not Just Ask an AI Chatbot?

Asking ChatGPT or Claude whether your content is AI-ready gives you a writing critique, not an engineering audit. These tools are trained to be agreeable and helpful. They will tell you your copy is clear and well-structured without ever checking whether a retrieval pipeline can actually extract it as a citation.

Perplexity, SearchGPT, and Gemini do not read your page from top to bottom the way a person does. They use Retrieval-Augmented Generation: your page gets sliced into roughly 150-word blocks, each block gets embedded as a mathematical vector, and those vectors are ranked by how closely they match the user's query. If your brand name and service topic do not appear together in enough of those blocks, your content ranks too low to be cited.

This grader runs the same mathematical checks that real retrieval pipelines apply. It counts the density of proper noun anchors your content establishes, checks whether your brand name and core service topic appear in the first fifth of the text, identifies which content blocks are missing entity anchors, and scores the result against hard-coded benchmarks for your industry. The output is a structural engineering report, not a writing opinion.

Who this free AI citation grader is for

We built this for marketing leads, content strategists, and founders who need to know whether their brand copy is actually structured for AI answer engines, not just written well. If you manage a service page, a company bio, a case study library, or a product description set and you are not sure whether any of it gets cited by Perplexity, Gemini, or SearchGPT, start here. It takes two minutes, needs no account, and gives you a score you can act on the same day.

Key scoring dimensions

Entity anchor density: the ratio of proper nouns, named entities, brand mentions, and industry terms to total word count, compared against industry benchmarks ranging from 6.0% for home services to 8.5% for B2B software. Verifiable claim ratio: the proportion of concrete data points including dollar figures, percentages, timelines, and client counts, benchmarked from 15% to 22% depending on industry. BLUF proximity: whether the brand name and core service topic appear within a 30-word window in the first 20% of the text. Vector chunk integrity: whether all 150-word content blocks contain at least one entity anchor. Semantic friction: the count of vague marketing phrases that AI citation engines deprioritize.

Related services from Brevard SEM

Brevard SEM provides AEO (Answer Engine Optimization), GEO (Generative Engine Optimization), and brand copy engineering for businesses that need to appear in AI-generated answers. Services include entity-structured content writing, schema markup, and citation architecture. Visit brevardsem.com/answer-engine-optimization for AEO services or contact Brevard SEM at brevardsem.com for a strategy session.