toolseogeoaeoschemaentitiescitabilityai-searchllms-txtUpdated 2026-07-04

SEO + GEO

Optimize pages for both classic search retrieval and AI citation. SEO is the discovery layer; GEO is the extraction, entity understanding, and recommendation layer.

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The 5 Required Rules

These rules are the minimum routing checklist encoded in the SEO/GEO skills, not an exhaustive SEO course. They keep agent work focused on page structure, entities, schema, and crawlability before deeper growth work. Source: seo-geo/SKILL.md; seo-geo/references/seo-geo-playbook.md

  1. Keyword placement -- primary keyword in at least 4 of 6 locations: URL slug, title tag, meta/social title, H1, at least one H2, body copy (ideally intro).
  2. Entity placement -- primary entity and supporting entities in title, H1, intro, core sections, and schema.
  3. Entity gap analysis -- extract entities from top competitors, add missing relevant entities that improve topical completeness. Do not add irrelevant brands.
  4. JSON-LD schema -- place in page <head>, not only through client-side injection.
  5. Schema entity reinforcement -- mirror on-page entities inside schema fields (name, description, about, sameAs, knowsAbout, mentions, author, publisher).

Jesper Nissen's screenshot is a small field proof for why these rules stay bundled. The root post reports a homepage ranking jump after keyword placement, entity placement, entity-gap completion, and schema/entity reinforcement; the attached reply claims a CTR bump after applying the entity-gap tip and says schema is still underused. Treat this as anecdotal operational evidence for the existing checklist, not as a new ranking guarantee. Source: X/@JespernissenSEO and local image review, 2026-07-04

Master GEO Scorecard

Category Weight
AI citability and extractability 25%
Brand authority and off-site signals 20%
Content quality and E-E-A-T 20%
Technical foundations 15%
Structured data 10%
Platform optimization 10%

Bands: 90-100 elite, 75-89 strong, 60-74 mixed, 40-59 weak, 0-39 critical.

AI Citability Engineering

Models cite passages that are direct, self-contained, fact-rich, structurally legible, and make sense outside their original context. The 134-167 word passage target is a heuristic for high-value answer blocks.

5-part citability model: (1) Answer block quality -- question-based H2, direct answer in first 1-2 sentences, named entities, precise claims. (2) Self-containment -- names subject explicitly, no dangling pronouns, at least one concrete fact. (3) Structural readability -- one H1, clean H2-H3 nesting, short paragraphs, lists for steps, tables for comparisons. (4) Statistical density -- percentages, dollar values, dated claims, named studies, benchmarks. (5) Uniqueness -- original data, case studies, experiments, screenshots.

E-E-A-T

Experience: first-hand language, implementation notes, screenshots, case studies with numbers. Expertise: visible author, credentials, sourced claims, correct terminology. Authoritativeness: external citations, strong topic coverage across the site, media mentions. Trustworthiness: clear contact, privacy policy, accurate claims, visible dates, HTTPS.

Technical GEO Foundations

Crawlability: allow Googlebot, Bingbot, GPTBot, ChatGPT-User, ClaudeBot, PerplexityBot. Blocking Google-Extended is not the same as blocking Googlebot. If the goal is AI visibility, blanket AI-bot blocking is self-sabotage.

Rendering: prefer SSR/SSG. Make schema server-rendered. Some AI crawlers are limited in JavaScript execution.

Core Web Vitals: LCP < 2.5s, INP < 200ms, CLS < 0.1.

Internal linking: high-value pages within ~3 clicks of homepage, descriptive anchor text.

Googlebot byte ceiling: Googlebot currently fetches up to 2MB for any individual URL, excluding PDFs, and that counter includes the HTTP header. If the HTML response exceeds that limit, Google processes the first 2MB as the fetched resource; referenced CSS/JS/image/video resources have their own fetch limits, and PDFs use a 64MB limit. Keep title, robots directives, canonicals, structured data, and primary content before bloated inline assets, menus, or hydration payloads. Source: Google Search Central, 2026-03-31; Source: local artifact review, 2026-07-03

Schema Design

Baseline graph: Organization/Person + WebSite + page-specific type + BreadcrumbList. Use sameAs to disambiguate across Wikipedia, Wikidata, LinkedIn, YouTube, GitHub, Crunchbase, etc. Prefer one @graph block with @id references. Use absolute URLs and ISO dates.

llms.txt

Machine-readable summary at domain root: what the site is, what sections matter, canonical pages, core facts. 10-30 most important pages with clear descriptions. Aligned with real site structure. Not a replacement for good structure, schema, or crawlability.

Competitive Comparison Capture

Capture branded commercial-intent queries directly. Publish exact-match vs, review, and alternatives pages. Make answer blocks so explicit that AI Overviews can lift them verbatim.

Per competitor: at minimum one standalone review page + one exact-match comparison page. Structure for answer extraction: question-led H2s, quotable verdict sentences, side-by-side tables, FAQ blocks.

Comparison page anatomy: exact-match title/slug/H1, first-paragraph verdict, Key Takeaways block, side-by-side table, pricing with dates, best-for guidance, honest tradeoffs, FAQ, clear CTA.

Firsthand testing required: sign up, use the products, take notes and screenshots. Fake reviews are obvious. Combine firsthand testing + external review language (G2, Capterra, Reddit) + your own positioning.

AIO conquest loop: pick 3-6 named competitors, ship one honest competitor-vs-product page and one standalone review per competitor, then inspect Google AI Overview / AI Mode / ChatGPT / Perplexity answers for those exact queries. The durable pattern from Kleo's bookmark is not "write attack pages"; it is firsthand use + external review language + extraction-friendly verdicts. Their screenshot shows Google returning a direct AI Overview answer for "kleo vs stanley" and citing Kleo's comparison/review pages. Source: X/@RobHoffman_, 2026-03-13

Local-service agent loop: for local businesses, route Claude/Cowork/browser agents through competitor page extraction, high-intent local keyword discovery, Google Business Profile completeness, service-page locality signals, review-response drafting, schema checks, and weekly rank/citation monitoring. The Claude Cowork bookmark is useful as a workflow sketch, but its attached images are only Claude and Google Business Profile logos; the durable asset is the checklist, not the visuals. Source: X/@bloggersarvesh, 2026-03-14

Programmatic SEO Domain Boundary

Programmatic SEO is a brand-authority decision, not only a template-generation tactic. Thin, short-term, or unproven pSEO experiments should not live on the primary brand domain: if they collapse, they can dilute topical trust, create crawl waste, and leave the brand with a footprint of disposable pages. Main-domain pSEO is reserved for durable pages with unique value, first-party or defensible data, useful internal links, clear indexation rules, and a long-term maintenance owner. Disposable experiments belong on a separate property, in noindex/staging, or outside the brand graph until quality and demand are proven.

The EXM row is useful as a blunt risk boundary rather than a precise traffic forecast: do not borrow the main site's authority for mass pages that are meant to be short-lived. Build authority and backlinks for the durable domain; keep churny pSEO tests isolated. Source: X/@EXM7777, 2026-03-12

Search Console Query Refresh Loop

Google Search Console is the cheapest refresh signal because it shows the queries a page already earns impressions for. Use it for pages that have traction but under-capture intent.

Workflow:

  1. Pick one page with meaningful clicks or impressions in the last 90 days.
  2. Export the page-filtered query CSV from Search Console.
  3. Ask Claude to group queries into satisfied intent, missing intent, title/H2 opportunities, FAQ opportunities, and internal-link opportunities.
  4. Update the page with answer blocks, missing subtopics, schema fields, and clearer headings.
  5. Re-measure clicks, impressions, CTR, and average position after the next crawl window.

The reviewed artifact shows the intended input shape: a Search Console performance view with hundreds of clicks, six-figure impressions, low CTR, and average position around page one. The durable lesson is not the screenshot metrics; it is the page-refresh loop from query evidence to editorial changes. Source: X/@ayushtweetshere, 2026-03-14

The reviewed @hridoyreh artifact sharpens the target selection: filter Search Console for high-impression queries where an existing page ranks around positions 8-20, then update that page with missing answer blocks, People Also Ask coverage, headings that match search intent, and a few internal links from stronger pages. This is a refresh loop for pages already near the prize, not a generic "publish more posts" tactic. Source: X/@hridoyreh and local image review, 2026-07-03

AI Search Measurement Loop

Treat AI search visibility as a parallel measurement lane, not a replacement label for SEO. Google's public guidance still centers on unique, helpful, satisfying content for Search and AI experiences; John Mueller's GEO-vs-SEO reply is best used as an audience-behavior signal: if customers discover or evaluate through ChatGPT, Gemini, Perplexity, AI Mode, or AI Overviews, measure those surfaces explicitly instead of assuming ordinary rankings explain the funnel. Source: Google Search Central, 2025-05-21; Source: Search Engine Journal summary of Mueller reply, 2026-07-03 lookup

The reviewed @alexgroberman artifact is useful as a KPI bundle, not as proof that a specific SEO product is canonical. The images show: Google Search Console scale (3.46M clicks, 18.4M impressions, 18.8% CTR), rising organic charts, a ChatGPT 5.2 answer listing SEO tools, and a Keywords Explorer table with AI Overview and citation columns. The reusable loop is: track Search Console clicks/impressions, monitor whether AI answers mention or cite the brand, inspect AI Overview citation columns where tools expose them, and repeat the comparison/review-page refresh cycle above. Source: X/@alexgroberman, 2026-03-12; Source: local artifact review, 2026-07-03

Platform-Specific Notes

Google AIO: question-led H2s, direct answer after heading, tables, FAQ, visible dateModified. ChatGPT: Bing index matters, entity consistency across site/schema/profiles. Perplexity: community validation, sourced quotable content, Reddit footprint. Gemini: Google ecosystem signals, YouTube, strong schema, meaningful images/videos.

Audit Workflow

  1. Define target (keyword, entity, page type, geography, platform mix)
  2. Fast SEO/GEO audit (title, H1, slug, intro, schema, canonical, dates, author, crawlability)
  3. Keyword and entity gap
  4. Score (citability, E-E-A-T, technical, schema, platform fit)
  5. Rewrite (title, H1, H2 outline, intro, answer blocks, schema)
  6. Strengthen graph (author pages, sameAs, external profiles, llms.txt)
  7. Deliver prioritized action plan

Agent Skills (Enforced)

Three agent skills auto-load when SEO/GEO work is detected:

  • seo-audit (~/.cursor/skills/seo-audit/SKILL.md) - Systematic SEO auditing across 5 priority areas: crawlability/indexation, technical foundations, on-page optimization, content quality, authority/links. Now includes Social Preview / OG Cards section. Triggers on "SEO audit", "check SEO", "audit this site." Based on coreyhaines31/marketingskills (68.9K weekly installs).
  • seo-geo-optimization (~/.cursor/skills/seo-geo-optimization/SKILL.md) - GEO optimization for AI search engines. Covers the 9 Princeton GEO methods, entity engineering, schema markup, AI citability engineering, platform-specific strategies, competitive comparison capture, and Next.js OG implementation patterns. Triggers on "GEO", "AI search", "optimize for ChatGPT." Based on resciencelab/opc-skills (21.1K weekly installs).
  • og-metadata-audit (~/.cursor/skills/og-metadata-audit/SKILL.md) - OpenGraph/Twitter card audit for Next.js App Router. Cross-references metadata exports, identifies missing fields, DRY violations, middleware naming traps, canonical inheritance bugs, and metadataBase resolution issues. Includes buildPageMetadata pattern. Triggers on "audit OG", "fix opengraph", "twitter cards broken."

All skills reference this wiki page as the canonical playbook and encode the 5 Required Rules, GEO Scorecard, and AI Citability Model directly.

OG / Social Preview Lessons

Learned from Loop (loooop.dev) cross-referenced against Dedalus monorepo (April 2026):

  • twitter: namespace is permanent - X/Twitter did not change the meta tag namespace. The crawler still reads twitter:card, twitter:image, etc.
  • Next.js middleware naming is strict - file must be middleware.ts, export must be middleware or default. A file named proxy.ts is silently ignored. This was the root cause of broken Twitter cards on Loop.
  • max-image-preview: "large" in root robots metadata tells Google (and helps Twitter) to render full-size image cards instead of thumbnails.
  • Canonical inheritance trap - In Next.js App Router, child pages that don't export alternates.canonical inherit the root layout's canonical (usually /). Every page needs its own.
  • htmlLimitedBots + middleware - Two complementary layers. Middleware intercepts social bots with custom HTML. htmlLimitedBots in next.config.ts serves lightweight HTML to SEO/AI crawlers. They overlap for social bots but htmlLimitedBots extends coverage.
  • DRY pattern - buildPageMetadata(input) returns complete { openGraph, twitter, alternates, title, description } from one function call. Eliminates 15-line boilerplate per page and ensures canonical consistency.

Tools

GEO-SEO-Claude (GitHub): open-source Claude Code GEO/AEO reference with /geo audit, citability, crawler, schema, brand, platform, report, and PDF routes. Keep it reference-only unless a future pass extracts a missing capability into Kevin's active ai-seo, seo-geo, seo-geo-optimization, or seo-audit skills. Source: GitHub/source review, 2026-07-03

Jam / SpreadJam: growth-channel agent platform that turns AI-search visibility and SEO/GEO audits into workflow actions. Use Kevin's installed SEO/GEO skills for direct audits; evaluate Jam when the task needs repeated growth-channel workflows, repo/site analysis, content-gap actions, warm leads, inboxes, or deliverability loops. Source: SpreadJam site/docs and local X video review, 2026-07-02

Cloudflare /crawl endpoint: single API call to crawl an entire site via Cloudflare Browser Rendering. Alternative to Firecrawl for automation use - compare latency, JavaScript rendering fidelity, and rate limits.

Signals (April 2026)

  • Googlebot 2MB fetch ceiling (Google Search Central, March 2026): Googlebot currently fetches up to 2MB for an individual URL, excluding PDFs, and the counter includes HTTP headers. The SEO implication is response-ordering, not "total page weight": keep metadata, canonical tags, schema, and primary content early in the HTML response, while external resources are fetched separately with their own limits. PDFs get 64MB. Source: X/@Charles_SEO local screenshot review, 2026-07-03
  • Claude Code SEO workflow (Cody Schneider, March 2026, 4K bookmarks): Set up a .env with Keywords Everywhere API key, DataForSEO API key, data warehouse for Google Search Console, and CMS access. Then use Claude Code for: keyword universe mapping (related keywords + SERP API for gap analysis), programmatic landing pages at scale (per-vertical with semantic terms + schema), link building (DataForSEO domain intersection for competitor backlink gaps), internal linking maps (topical relevance clusters from keyword data), and content refreshing. Source review resolved the self-thread to Graphed, a hosted marketing-agent service that positions this workflow as an autonomous growth operations system. Source: X/@codyschneider self-thread and Graphed site review, 2026-07-04
  • Free backlinks from high-authority domains: WordPress and Medium both offer free backlink surfaces - republish or cross-post carefully and set canonical links back to the source page when appropriate. The reviewed WordPress artifact shows a high-authority WordPress domain snapshot (DR 95, AR 31), so route this as authority-surface evidence, not a license to spray thin duplicate pages. Source: X/@kalashvasaniya and local image review, 2026-07-03
  • Google's John Mueller recommends tracking AI search traffic separately in analytics. No standard referrer header yet, but Perplexity and ChatGPT are increasingly identifiable.
  • Awesome Design MD (GitHub): reverse-engineered design systems of Apple, Spotify, Airbnb, and other companies as single markdown files. Useful as reference data for schema and entity modeling on design-related pages.

Taxonomy

12 operational categories: Foundations, Research & Intent, Site Architecture, Technical Crawl & Indexing, On-Page Entities & Schema, Content Systems & Page Types, GEO/AEO/AI Platforms, Authority Links & Brand, Distribution & Feedback, Measurement & Experiments, International, Growth Systems. Cross-cutting: UX, conversion, accessibility, legal, performance, editorial quality.

Hridoy Rehman's folder-style SEO bookmark is useful as a curriculum-shaped view of the same taxonomy: foundations, research, SERP analysis, search intent, competitor research, and keyword gaps belong before tactical page edits. Because the enriched record has no resolved source beyond the tweet and is visibly truncated, it is supporting structure for this page rather than a separate SEO skill or a claim about a complete course outline. Source: X/@hridoyreh, 2026-03-15

Timeline

Related Pages

Social Content OSBrin - Agent Context SecurityJam (SpreadJam)Frontend and Design Skills