GEO Content Optimizer
Improves citation readiness for ChatGPT, Perplexity, AI Overviews, Gemini, and Claude.
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Free$ npx skills add seoskills.sh/geo-content-optimizerAbout this skill
GEO Content Optimizer is a AI Search (AEO and GEO) skill for AI agents, published in the seoskills.sh catalog. Reach for it when your work involves answer and generative engine optimization for AI Overviews, Perplexity, and ChatGPT. Install it with one command and it runs inside your own agent, so the work happens in your workflow, not a separate SEO tool.
SKILL.md
GEO Content Optimizer
Optimizes content for AI-generated answers and citation surfaces such as ChatGPT, Perplexity, Gemini, Claude, and AI Overviews.
What This Skill Does
Improves structure, authority signals, factual density, quotable statements, source attribution, and overall GEO readiness.
Quick Start
Optimize this content for GEO/AI citations: [content or URL]
Make this article more likely to be cited by AI systems
Write content about [topic] optimized for both SEO and GEO
Audit this content for GEO readiness and suggest improvements
AI Overview is eating clicks on 12 head queries — build a recovery plan
See AI Overview Recovery for the 4-phase playbook (measure → diagnose → rewrite → monitor) tailored to recovery scenarios (as opposed to generic GEO optimization).
Skill Contract
Expected output: a ready-to-use asset or implementation-ready transformation plus a short handoff summary ready for memory/content/.
- Reads: the brief, target keywords, entity inputs, and quality constraints. Canonical entity profiles: if the content mentions a brand / person / product, this skill MUST consult
memory/entities/<slug>.md(per the entity-geo handoff schema) to populatedisplay_name,description_short,ai_resolution_statusand decide whether disambiguation boilerplate is needed. If the profile is missing or stale (>90 days), declareDONE_WITH_CONCERNSand recommendentity-registryas an open loop. - Writes: a user-facing content, metadata, or schema deliverable plus a reusable summary that can be stored under
memory/content/. - Promotes: approved angles, messaging choices, missing evidence, and publish blockers to
memory/hot-cache.mdandmemory/open-loops.md; propose durable decisions as pending-decision items. - Done when: each target AI query has a standalone, quotable answer block; a before/after GEO score and AI Query Coverage are reported; and the CORE-EEAT GEO self-check (C02, O03, O05, E01) has no unaddressed Fail.
- Primary next skill: use the
Next Best Skillbelow when the asset is ready for review or deployment.
Handoff Summary
Emit the standard shape from skill-contract.md §Handoff Summary Format.
Data Sources
Use ~~AI monitor and ~~SEO tool when connected; otherwise ask for target queries, content, engines, competitor examples, and known AI-citation gaps. See CONNECTORS.md.
Measuring whether GEO work paid off: the changes this skill makes (extractable, quotable, answer-shaped content) move citability — testable in minutes by handing a live-fetch engine the URL and asking the target query. That is a proxy. Whether an engine then cites you unprompted (surfacing) is gated by its crawl/index refresh — week-scale and confounded, not minute-level. Do not conflate the two or promise fast surfacing. The latency of each signal, and why outcome deltas need a control group, are defined in references/measurement-protocol.md.
Keyless AI-citation probe (Tavily): python3 "${CLAUDE_PLUGIN_ROOT}/scripts/connectors/tavily.py" search "<target query>" --answer --limit 10 runs that citability test against a real AI answer engine, no key needed — check whether the synthesized answer cites your URL/domain and where the page ranks among the scored sources. This is Measured for Tavily's own layer and an Estimated proxy for ChatGPT/Perplexity/Google AI Overviews (different indexes, different retrieval). Re-run after shipping changes for a minutes-scale citability read; unprompted surfacing stays week-scale per the paragraph above. See scripts/connectors/README.md.
Instructions
When a user requests GEO optimization, run these five steps:
- Load CORE-EEAT GEO-First Targets — prioritize C02, C09, O03, O05, E01, O02 plus engine-specific preferences.
- Analyze Current Content — score clear definitions, quotable statements, factual density, source citations, Q&A format, authority signals, freshness, and structure clarity.
- Apply GEO Techniques — add standalone 25-50 word definitions, sourced quotable statements, expert/source signals, Q&A/tables/lists, specific data, and visible-content-matching FAQ schema.
- Generate GEO Output — report Changes Made, before/after GEO score, and AI Query Coverage.
- CORE-EEAT GEO Self-Check — verify C02, C04, C09, O02, O03, O05, O06, R01, R02, R04, R07, E01, Exp10, Ept08 with Pass/Warn/Fail. Then run the slop self-check to strip AI-tell phrasing before the asset ships.
Label every metric Measured (tool/export), User-provided, or Estimated (model inference); never present an estimate as measured; if a required metric is unavailable, mark it N/A — do not invent it.
Reference: See Instructions Detail for the full CORE-EEAT GEO target tables, AI engine preferences, analysis templates, optimization report template, self-check matrix, and examples.
Example
User: "Optimize this paragraph for GEO: 'Email marketing is a good way to reach customers. It's been around for a while and many businesses use it.'"
Output adds a clear definition, dated/source-backed facts, structured list, quotable statements, and a before/after GEO score. See the full pattern in Instructions Detail — Example.
GEO Optimization Checklist
Reference: See the GEO Readiness Checklist in GEO Optimization Techniques for the full checklist covering definitions, quotable content, authority, structure, and technical elements.
Save Results
On user confirmation, save to memory/content/YYYY-MM-DD-<topic>.md — see Skill Contract §Save Results Template.
Reference Materials
- Instructions Detail - Full 5-step workflow, CORE-EEAT GEO targets, self-check matrix, worked example, tips
- GEO Optimization Techniques - Detailed before/after examples, templates, and checklists for each technique
- AI Citation Patterns - Evidence-bounded discovery, retrieval, and citation controls for Google AI features, ChatGPT Search, Perplexity, Claude, Gemini grounding, Copilot Studio, and Brave Search
- Quotable Content Examples - Before/after examples of content optimized for AI citation
- Medium / GitHub AI-Citation Surfaces - Off-site surfaces engines cite (Medium articles, GitHub repos/READMEs)
- Slop Self-Check - Pre-publish pass to strip AI-tell phrasing before content ships
- Agent-Readable File Stack (llms.txt / OKF) - Machine-readable files so agents and engines can parse your site
- Grokipedia Tactics - AI-citation tactics for Grok / Grokipedia
- GEO distribution surfaces — platform refs engines pull from: X, LinkedIn, YouTube, Reddit
Next Best Skill
- Primary: content-quality-auditor — verify the optimized content is strong enough to ship and cite.
Termination note: keep a visited-set this session; if the recommended skill was already invoked, stop and report the chain complete rather than re-running it. Honor a max handoff depth of 3 to avoid loops (per skill-contract.md §Termination rules).
Not using the CLI? Copy the SKILL.md and paste it straight into ChatGPT, Claude, or any agent.
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