Seo geo

Skill ajquintal/founder-os/skills/seo-geo

Build a combined SEO + generative-engine-optimization plan to rank in search AND get cited in AI answers (ChatGPT, Perplexity, Google AI Overviews) — an entity/keyword map, a prioritized pillar-and-cluster content plan, and a technical checklist. Use for organic search strategy, topical authority, keyword/entity research, or being surfaced by AI engines. Triggers: "SEO", "GEO", "rank on Google", "keywords", "get cited by AI", "AI answers", "topical authority", "AI Overviews", "llms.txt".From its SKILL.md

Install

npx -y skills add ajquintal/founder-os --skill seo-geo

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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SKILL.md

3.5 KB, as published. Nobody here has run it

/seo-geo — SEO + Generative Engine Optimization

One entity-led plan to rank in search and get cited in AI answers: map → content → technicals. Reads /market-scan (entities, competitors) and /offer-architect (rungs to map intent to).

Load first

founder-profile/PROFILE.md, founder-profile/voice-and-brand.md, founder-profile/operating-playbooks.md (positioning/wedge), founder-profile/guardrails.md (drafts, claims)
Active ventures/<slug>/venture-context.md
Latest /market-scan and /offer-architect output for this venture.

Method (full detail + worked example in `references/method.md`)

Define the entity. Brand, the category it wants to own, ICP, and the actual questions the ICP types into search and asks an AI engine. Entity clarity is the shared root of SEO and GEO.
Map entities + keywords. Cluster by intent (informational / commercial / transactional / navigational); add conversational AI-answer queries; map each cluster to an offer rung.
Pick one beachhead cluster. Score intent-value × winnability × strategic fit. Own one cluster before widening. (Guards: too many fronts.)
Plan pillar + cluster content. One pillar page per cluster + supporting articles, internally linked — engineered for depth (rank) and citation (GEO).
Add the GEO layer. Direct-answer blocks, quotable stats with sources, comparison tables, FAQ/HowTo schema, and consistent entity data across the web so engines trust and cite you.
Technical checklist. Crawl, index, sitemap, schema, canonical/robots, Core Web Vitals, llms.txt — each with a done-criterion.

Output contract

Entity/keyword map: cluster · entities/keywords · intent · AI-answer query · offer rung · priority.
Prioritized content plan: asset · type (pillar/cluster) · target query · GEO citation hook · internal links · owner.
Technical checklist: crawlability · indexation · sitemap · schema types · CWV targets · canonical/robots · llms.txt — each with a done-criterion.
The one beachhead cluster to own first, and why.

[DRAFT — content plan for review; nothing published without approval]

Rules

Drafts only — content is drafted for review, never auto-published.
Own one cluster before widening; depth beats a thin spread.
GEO ≠ keyword stuffing: earn citations with quotable, sourced, structured answers.
Voice per founder-profile/voice-and-brand.md; no banned words. LYV firewall on content/entities.
Claims & capability (G-claims): make only substantiated claims, and never imply a capability or deliverable the venture can't provide today. Honor the venture's own claims & regulatory constraints (from its venture-context + engineering-backbone §9); route any regulated claim (health / financial / legal / environmental) for professional review before publish.

Examples & evals

references/method.md — full method + a worked example (Executive Edge).
evals/evals.md — 3 cases with expected outputs.