ai-search-visibility
AI search visibility
Being cited means an engine found your page useful to consult; being recommended means it put your brand on the buyer's shortlist, and that second outcome is governed mostly by what the rest of the web says about you. This skill covers both, plus whether an agent can reach and parse the site at all. Sources: Google's AI optimization guide and Search changelog, the OpenAI, Anthropic, Google and Perplexity crawler pages, the llms.txt spec, Lighthouse's agentic-browsing docs, [coreyhaines31/marketingskills, ai-seo] (MIT, Corey Haines; several of its frameworks credit Profound's MIT skills), [open-seo, ai-prompt-research and ai-visibility-audit] (MIT, Ben Senescu), [openseo.so], [aeo.js] and [freescan]. Product context (business, audience, competitors, key pages) is read from .agents/product-context.md, defined in anti-slop-copy CONTEXT.md; the ai-seo source names that file .agents/product-marketing.md. Classic search is seo SKILL.md.
Apply only the routes and checks for the selected job. Read a linked skill's named file from its installed folder when available, or from the linked source. Report an unavailable required reference instead of inventing it. [skill-authoring, DISTRIBUTION.md#composing-skills]
| The job | Read |
|---|---|
| AI user agents by purpose (training, search, user-triggered), each vendor's documented rules, a purpose-specific robots.txt, Google's parsing rules, Content Signals, firewall checks, the crawler-only noindex loop, errors in the sources | AI-CRAWLERS.md |
Access, discovery and parseability, the server-rendered check, sitemap dates, Lighthouse's agentic-browsing audits, vendor readiness scores, acting on the page with WebMCP, a /pricing.md, OKF bundles |
AGENT-READINESS.md |
The llms.txt format and locations, Markdown copies, rel="alternate" and rel="describedby", what Google says about the file, Lighthouse's check, aeo.js's generator mistakes |
LLMS-TXT.md |
| Google's limits on writing "for AI", structure rules, the definition, step, comparison, FAQ, listicle and evidence block templates, the fact-family fan-out matrix, authority by domain, content types, what not to do | CONTENT-BLOCKS.md |
| aeo.js's citability regexes and rubric, where it disagrees with Google, its CLI, MCP server and a CI gate | CITABILITY.md |
| What prompt datasets are, head terms, intent groups, openings, a tracking set, intent families, cohorts, versioning, multi-turn journeys, extracting ChatGPT's fan-out queries | PROMPT-RESEARCH.md |
| The audit workflow from evidence to one to three recommendations, the report, the visibility ladder and "recommended against", the citation-mix classes, guardrails | VISIBILITY-AUDIT.md |
| Search Console's Generative AI performance report, repeat runs and rates, volatility, the four layers of effect, AI referrer grouping, evaluation designs, reporting language | MEASUREMENT.md |
| Auditing what answers say about you: the claim ledger, seven verdicts, P0 to P3 severity, fixing the source, the report | ANSWER-ACCURACY.md |
| Being the vendor a coding agent picks: the task panel, the levers, the docs audit and fact ledger, prompt-injection limits | AGENT-DEFAULTS.md |
| Third-party profiles and consensus, repositioning, LinkedIn, YouTube and podcasts, other languages and markets, AI shopping, what is and isn't verified about each engine's index | CITATION-SURFACES.md |