seo-ai-search
Skill0 starsChanged 2 months agoMITView on GitHub
Make a site rank on Google and get cited by AI assistants (ChatGPT, Perplexity, Gemini, Copilot, Claude). Use when implementing SEO on any site or framework, auditing search visibility, choosing structured data, researching keywords without paid tools, planning local or map-pack presence, improving AI-answer visibility (GEO/AEO), or diagnosing why traffic or AI citations are low. Covers technical SEO, schema, E-E-A-T, content strategy, and measurement.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- yeer0s/ultimate-seo-collectiontheir own version, first seen Oct 15, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- yeer0s/ultimate-seo-collection★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈2
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 43
Never fabricate review counts, invent business facts for schema, buy link packages, or spin scaled thin content — Google's …
- Distinctive: line 44
Every CTR/adoption statistic in these references carries a date.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
SEO + AI search visibility
Research-backed playbook (compiled September 2026 from primary sources: Google/Bing docs, Vercel/Cloudflare crawler data, Pew/Ahrefs/Semrush studies). Facts marked VOLATILE age within months — web-search them before relying on them; unmarked principles are stable.
The one rule that covers everything
Everything you want indexed, ranked, or cited must be in the initial server-rendered HTML. Googlebot renders JavaScript (late, in a second pass); no major AI crawler executes JavaScript at all (GPTBot, ClaudeBot, PerplexityBot, CCBot fetch but never render — Vercel/MERJ data; VOLATILE per-bot, stable as a rule). Client-side-rendered content is invisible to the systems the client wants to win. SSG/ISR > SSR > CSR; CSR only behind login.
Pick the workflow
- Building or relaunching a site → do "Implement" below, then read references/technical.md and references/structured-data.md for the details of each step.
- Auditing an existing site ("why don't we rank / why doesn't AI mention us") → run
node scripts/audit.mjs https://the-sitefirst (automates layers 1–2: robots/sitemap health, raw-HTML completeness, per-bot access), then follow the 8-step order in references/audit-checklist.md. Never audit from lab data alone; use field data and raw-HTML checks. - Keyword/content strategy → the no-paid-tools method and honesty tiers in references/keywords-content.md. Never promise rankings on head terms owned by aggregators; tier targets and say which are winnable.
- A local/physical business (shop, clinic, restaurant, gym) → profiles beat websites; read references/local.md FIRST. The map pack and AI business cards are fed by business profiles + reviews, not by web pages.
- AI-answer visibility program (get recommended by ChatGPT/Perplexity/Gemini) → references/ai-search.md: what feeds each assistant, the crawler/robots recipe, IndexNow, measurement.
- The client wants OUT (or paid) — limit AI reuse, block or monetize crawlers → the "other direction" section of references/ai-search.md: snippet controls, Bing NOCACHE/NOARCHIVE, Cloudflare default-blocking, bot verification.
- Migrating a domain or URL structure → the migration checklist in references/audit-checklist.md before anything moves.
Implement (new site checklist — the stable core)
- Rendering: critical content, metadata, and JSON-LD in initial HTML (curl the page and grep for them — this one check covers Google freshness AND every AI crawler). Real 404 status codes from the server (SPA "not found" UIs with HTTP 200 become soft-404s).
- Metadata: unique title (≤60 chars, primary keyword + brand) and description (≤155) per page; absolute canonical on every page (set the metadata base URL); OpenGraph/Twitter with absolute image URLs (broken share cards = lost WhatsApp/Slack distribution). Make titles/descriptions editable by the client (CMS-driven with code fallbacks) — SEO iteration must not need deploys.
- Structured data: JSON-LD only; emit only types Google currently rewards — the supported list changes often (VOLATILE: re-fetch https://developers.google.com/search/docs/appearance/structured-data/search-gallery at use time; FAQ and HowTo rich results are dead, seven more types died June 2025). Always: Organization (with
sameAslinks — this grounds the brand entity for knowledge panels and LLMs) + BreadcrumbList. Per-archetype recipes: references/structured-data.md. Never mark up content that isn't visible on the page. - Crawl surface: sitemap.xml with real lastmod for every canonical URL; robots.txt allowing all legitimate crawlers including AI crawlers explicitly (roster in ai-search.md) and blocking low-value faceted/parameter URLs (robots block, not noindex — noindex still spends crawl budget; and never combine disallow with noindex — a blocked page can't show its noindex; mechanics in technical.md); paginated fallbacks for infinite scroll; noindex thin/placeholder pages.
- Performance: field-data Core Web Vitals — LCP ≤ 2.5 s, INP ≤ 200 ms, CLS ≤ 0.1 at p75 (thresholds stable since Mar 2024). Ship less hydration JS, don't lazy-load the LCP image, break long main-thread tasks. CWV is a tiebreaker, not a dominant signal — don't oversell it.
- Indexing pipelines: Google Search Console (verify, submit sitemap) AND Bing Webmaster Tools + IndexNow — Bing's index is the retrieval layer behind ChatGPT search and Copilot; a page Bing hasn't indexed cannot be cited there. Automate an IndexNow ping post-deploy (key file + POST sitemap URLs to api.indexnow.org).
- Content shape for AI citation (evidence: Princeton GEO study — statistics, quotations, citations lift generative visibility 30–40%): self-contained factual passages with numbers and dates, question-shaped headings, tables, definition-first sentences. Third-party coverage of the brand beats brand-owned pages in AI citation weighting — earned media is part of the technical plan, not separate marketing.
- Bilingual/multilingual: separate URLs per language with full bidirectional hreflang clusters (each page lists all variants including itself + x-default) when both languages must rank; a single mixed-language page ranks for its primary language only (acceptable when the second language is decorative). Subfolders > ccTLDs > subdomains by default.
Honesty rules (apply to every engagement)
- Tier every keyword target: T1 winnable weeks–months (brand + local/low-competition), T2 winnable 6–18 months (content + links), T3 not winnable organically (aggregator-owned head terms) → the answer there is presence ON the ranking aggregators ("barnacle SEO") + paid search, and say so plainly.
- Quote timelines as ranges tied to actions, never guarantees. Rankings are not promisable; the work is.
- Never fabricate review counts, invent business facts for schema, buy link packages, or spin scaled thin content — Google's scaled-content-abuse and site-reputation-abuse policies are actively enforced (details in keywords-content.md).
- Every CTR/adoption statistic in these references carries a date; re-verify any number older than ~6 months before quoting it to a client.
Measure
Google Search Console (+ its generative-AI performance report — impressions in AI surfaces; VOLATILE, metrics expanding), Bing Webmaster Tools AI Performance report (citations + the reformulated "grounding queries"), referral segments for chatgpt.com/perplexity.ai/copilot, server logs for AI-crawler hits, and a quarterly manual prompt-sampling audit (20–40 buyer prompts × 3 runs per assistant, scored for brand mention/position/sources). Full measurement stack and free tooling: references/ai-search.md and references/audit-checklist.md.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

