Guides.Practical guides for AI search optimization.
Clear, actionable playbooks explaining how generative engines, answer bots, and AI crawlers index, extract, and cite website content. Start with foundational optimization frameworks, then implement verified markup and crawler protocols.
Foundational search frameworks
The three core disciplines defining modern AI search readiness and indexing.
Generative Engine Optimization (GEO)
How to structure entity knowledge graphs, attribution signals, and authoritative content so generative AI models cite your brand in synthesised answers.
Read guide→Answer Engine Optimization (AEO)
How to format direct answers, concise summary blocks, and tabular data so answer engines (like Perplexity and AI Overviews) extract facts directly.
Read guide→AI Index Optimization (AIO)
How to configure crawler permissions, llms.txt endpoints, and server response pipelines so AI bot indexers discover and fetch your pages efficiently.
Read guide→Technical implementation playbooks
Step-by-step implementation guides with verified configuration snippets and test criteria.
llms.txt implementation
How to structure and publish a plain-text markdown directory at your site root to guide AI models to your high-value endpoints.
Read playbook→AI crawler access & robots.txt
Manage user-agent rules, firewall edge policies, and crawling directives for GPTBot, ClaudeBot, PerplexityBot, and Google-Extended.
Read playbook→Schema graphs for AI search
Build interconnected JSON-LD entity graphs with sameAs reconciliations, article metadata, and organization authorship to reinforce entity identity.
Read playbook→Diagnostic tracks & reference catalog
Inspect the exact criteria and tests evaluated by Benchmarq's deterministic audit engine.
Checks catalog overview
Explore all 200+ rule-based tests across CORE, AIO, AEO, and GEO, complete with deduction weights and verified remediation steps.
Browse checks catalog→Glossary of terms
Canonical definitions and architectural context for 20+ terms across generative AI, machine readability, and agentic workflows.
Explore glossary→GEO track checks
Will AI models cite and describe your brand correctly in generated answers?
View GEO checks→AEO track checks
Can answer engines and AI agents read your site, extract facts and act on it?
View AEO checks→Individual test results, failure triggers, and tailored code fixes for your domain are generated in your workspace audit report.
Questions.
Direct answers about AI search terminology and best practices.
Is GEO the same as AEO?
No. GEO is about being cited in generated answers. AEO is about making your content easy for answer engines and agents to read and quote. They overlap, and Benchmarq scores them as separate tracks. What is AEO?.
Is AIO the same as AI Overviews?
No. AI Overviews are Google's AI-generated summaries in search. AIO in Benchmarq is AI Index Optimization, the discoverability of your pages in AI-powered search.
Is llms.txt the same as robots.txt?
No. robots.txt tells crawlers what they may fetch. llms.txt describes your site and points to your best pages. AI crawler access.
Where can I see a check in detail?
In the report in the app, with its result, severity and fix. See the reports.
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