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Geo Content Optimizer

CommunityPopular
aaron-he-zhu
geo-content-optimizer

Use when the user asks to "optimize for AI citations"; improves citation readiness for ChatGPT, Perplexity, AI Overviews, Gemini, and Claude. Not for structural on-page SEO — use on-page-seo-checker; not for net-new drafting — use content-writer. AI引用优化/GEO优化/AI搜索

Overview

Publisheraaron-he-zhu
Repositoryaaron-marketing-skills
Skill namegeo-content-optimizer
Stars
2.9K
Forks
373
Bundled files
6
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by aaron-he-zhu on GitHub. Read the source before you install it.

Installation

Install the Geo Content Optimizer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/seo-geo/implement/geo-content-optimizer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/aaron-he-zhu/aaron-marketing-skills.git /tmp/aaron-marketing-skills
mkdir -p .claude/skills
cp -r /tmp/aaron-marketing-skills/seo-geo/implement/geo-content-optimizer .claude/skills/geo-content-optimizer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Geo Content Optimizer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Geo Content Optimizer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Geo Content Optimizer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

text
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 populate display_name, description_short, ai_resolution_status and decide whether disambiguation boilerplate is needed. If the profile is missing or stale (>90 days), declare DONE_WITH_CONCERNS and recommend entity-registry as 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.md and memory/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 Skill below 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:

  1. Load CORE-EEAT GEO-First Targets — prioritize C02, C09, O03, O05, E01, O02 plus engine-specific preferences.
  2. Analyze Current Content — score clear definitions, quotable statements, factual density, source citations, Q&A format, authority signals, freshness, and structure clarity.
  3. 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.
  4. Generate GEO Output — report Changes Made, before/after GEO score, and AI Query Coverage.
  5. 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

Next Best Skill

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).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Geo Content Optimizer AI skill do?

Use when the user asks to "optimize for AI citations"; improves citation readiness for ChatGPT, Perplexity, AI Overviews, Gemini, and Claude. Not for structural on-page SEO — use on-page-seo-checker; not for net-new drafting — use content-writer. AI引用优化/GEO优化/AI搜索

Why use Geo Content Optimizer on TypingMind?

Because you install it once and use it with any model. Geo Content Optimizer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Geo Content Optimizer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/seo-geo/implement/geo-content-optimizer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Geo Content Optimizer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Geo Content Optimizer?

As many as you like. As long as a model supports skills, you can use Geo Content Optimizer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Geo Content Optimizer AI skill free?

Yes. It is published on GitHub by aaron-he-zhu under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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