geo-fundamentals

geo-fundamentals is a cursor rule for Cursor from MN-Lizard-Team/aiyu-multi-agent. It costs 18 tokens per session (872 once invoked), scanned A, original, Apache-2.0.

A guide to Generative Engine Optimization (GEO), the practice of structuring content so AI search tools such as ChatGPT, Claude, and Perplexity can find and cite it.

In plain words
What is it for?
It is for planning content, data, and authority signals intended to earn citations in AI search results.
Why use it?
It helps address the problem of content being overlooked or left uncited in AI-generated answers, which differs from ranking in traditional search engines.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/. Also seen: mentions Cursor.

Good fit It is for planning content, data, and authority signals intended to earn citations in AI search results.

Compare 6 cursor rules from other repositories ↓
Install with agentmods
npx agentmods add rules/mn-lizard-team/aiyu-multi-agent/geo-fundamentals
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/MN-Lizard-Team/aiyu-multi-agent

Made for: Cursor.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for geo-fundamentals

README.md
[![agentmods](https://agentmods.dev/badge/rules/mn-lizard-team/aiyu-multi-agent/geo-fundamentals.svg)](https://agentmods.dev/rules/mn-lizard-team/aiyu-multi-agent/geo-fundamentals)
Your own site
<a href="https://agentmods.dev/rules/mn-lizard-team/aiyu-multi-agent/geo-fundamentals"><img src="https://agentmods.dev/badge/rules/mn-lizard-team/aiyu-multi-agent/geo-fundamentals.svg" alt="Measured on agentmods" height="20"></a>
Per session 18 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 872 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00018 $0.00872
Opus 5 $0.00009 $0.00436
Sonnet 5 $0.00004 $0.00174
Haiku 4.5 $0.00002 $0.00087

Measured 4d ago against content hash e67b0e9ecd9a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

geo-fundamentals scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/skills/geo-fundamentals.mdc · 160 lines

How it starts

The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill: geo-fundamentals

Cursor Agent-Requested Rule — applied when AI determines relevance.


GEO Fundamentals

Optimization for AI-powered search engines.


1. What is GEO?

GEO = Generative Engine Optimization

Goal Platform
Be cited in AI responses ChatGPT, Claude, Perplexity, Gemini

SEO vs GEO

Aspect SEO GEO
Goal #1 ranking AI citations
Platform Google AI engines
Metrics Rankings, CTR Citation rate
Focus Keywords Entities, data

2. AI Engine Landscape

Engine Citation Style Opportunity
Perplexity Numbered [1][2] Highest citation rate
ChatGPT Inline/footnotes Custom GPTs
Claude Contextual Long-form content
Gemini Sources section SEO crossover

3. RAG Retrieval Factors

How AI engines select content to cite:

Factor Weight
Semantic relevance ~40%
Keyword match ~20%
Authority signals ~15%
Freshness ~10%
Source diversity ~15%

4. Content That Gets Cited

Element Why It Works
Original statistics Unique, citable data
Expert quotes Authority transfer
Clear definitions Easy to extract
Step-by-step guides Actionable value
Comparison tables Structured info
FAQ sections Direct answers

5. GEO Content Checklist

Content Elements

  • Question-based titles
  • Summary/TL;DR at top
  • Original data with sources
  • Expert quotes (name, title)
  • FAQ section (3-5 Q&A)
  • Clear definitions
  • "Last updated" timestamp
  • Author with credentials

Technical Elements

  • Article schema with dates
  • Person schema for author
  • FAQPage schema
  • Fast loading (< 2.5s)
  • Clean HTML structure

6. Entity Building

Action Purpose
Google Knowledge Panel Entity recognition
Wikipedia (if notable) Authority source
Consistent info across web Entity consolidation
Industry mentions Authority signals

Read the full file on GitHub · 160 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 160 lines · 18 tokens per session scan A e67b0e9ecd9a

Subscribe to this mod's changes

geo-fundamentals is a cursor rule published in the GitHub repository MN-Lizard-Team/aiyu-multi-agent (7 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 872 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.