🌍 E-GEO

Generative Engine Optimization (GEO) & Answer Engine Optimization (AEO) for AI-Powered Search

🚀 One command. Premium results.
Rank higher in ChatGPT, Perplexity, Claude, and Gemini.

📖 Docs • 🐛 Issues • 💬 Discussions • 📝 Research Paper

_{🤖 AI-Assisted Development — See what's AI-generated vs human-authored}

✨ What is E-GEO?

E-GEO is an open-source Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) toolkit that transforms your website content to rank higher in AI-powered search engines — including ChatGPT, Perplexity, Google AI Overviews, Claude, and Gemini.

Also known as AI SEO or LLM SEO, GEO is the practice of optimizing content so that generative AI engines can crawl, understand, cite, and recommend it. E-GEO automates this entire process.

Based on the E-GEO research paper (arXiv:2511.20867), it applies the 10 universal features that consistently improve AI-engine rankings — competitive framing, citation optimization, structured data, and semantic density improvements backed by peer-reviewed findings.

✅ No learning curve — One command to optimize
✅ Research-backed — Based on peer-reviewed findings
✅ Production-ready — Copy-paste optimized content
✅ Multi-engine — Optimizes for ChatGPT, Perplexity, Gemini, Claude & Google AI Overviews
✅ Full pipeline — Analyze → Rank → Rewrite → Schema in one command

/geo https://yoursite.com/pricing

↓

geo-output/
├── report.md
├── optimized/
│   └── pricing.md
└── schema/
    └── pricing.json

📈 Why AI Visibility Matters in 2026

AI search engines give one synthesized answer and cite a handful of sources. If your site isn't one of them, you're invisible — even if you rank #1 on Google.

User asks ChatGPT: "What's the best GEO tool?"

ChatGPT: "According to [Competitor], the best tool is..."
          ↑ They get cited. You don't.

ChatGPT serves 900M+ weekly users — a growing share of sessions that used to be Google searches.
28.3% of ChatGPT's most-cited pages have zero organic visibility on Google (Ahrefs) — AI engines reward different signals than classic SEO.
Proper JSON-LD schema lifts LLM extraction accuracy from 16% to 54% (Semrush study on GPT-4).
844,000+ sites already ship an llms.txt. Is yours one of them?

Traditional SEO optimizes for blue links. GEO optimizes for citations in AI-generated answers. E-GEO is the open-source tool that bridges this gap.

🚀 Quick Start (3 Steps)

1. Install

Copy the .claude/ folder to your project:

cp -r /path/to/eGEOagents/.claude .

2. Activate

In Claude Code, switch to GEO mode:

/output-style geo-optimizer

3. Optimize

Run your first optimization:

/geo https://yoursite.com

🧩 Install as Skills (skills.sh)

Install the complete skill collection:

npx skills add https://github.com/mverab/eGEOagents

Install one skill only:

npx skills add https://github.com/mverab/eGEOagents --skill competitive-analysis

Validate parser discovery before shipping updates:

npx skills add https://github.com/mverab/eGEOagents --list

Verify indexing pages:

Collection: skills.sh/mverab/egeoagents
Owner: skills.sh/mverab

📋 Commands

Command	What it does
`/geo <url>`	Full pipeline - Analyze, rank, rewrite, schema
`/geo:audit <url>`	Analysis only, no changes
`/geo:optimize <file>`	Optimize local content file
`/geo:batch <folder>`	Process entire folder
`/geo:report`	Generate executive report
`/geo:compete <query>`	Competitive analysis

📊 What You Get

After running /geo:

geo-output/
├── report.md           # Executive summary + scores
├── analysis.json       # Raw analysis data
├── optimized/
│   └── pricing.md      # Rewritten content (ready to use)
├── schema/
│   └── pricing.json    # JSON-LD markup (copy to site)
└── checklist.md        # Step-by-step implementation

🎯 Results: Backed by Research

E-GEO is grounded in peer-reviewed research from the E-GEO research paper (arXiv:2511.20867), building on foundational work by Aggarwal et al. (Princeton, KDD 2024) — the original study that defined Generative Engine Optimization as a discipline.

The E-GEO paper reports that:

Competitive framing produces the strongest immediate ranking lift among all GEO strategies tested.
A universal optimization strategy (applying all 10 features together) outperforms individual heuristics by a wide margin.
The 10 GEO features (ranking emphasis, user intent matching, competitive edge, social proof, authority signals, scannability, citation density, structured data, factual language, and freshness) consistently appear in higher-ranking content across ChatGPT, Perplexity, and Gemini.

Feature	What E-GEO Does
Ranking Emphasis	Positions your content as the top choice
User Intent	Directly answers what users are looking for
Competitive Edge	Highlights your unique advantages
Social Proof	Integrates trust signals and testimonials
Authority	Establishes expert, confident tone
Scannability	Structures for easy AI parsing

Results vary by content quality and competition. See the paper for full methodology and findings: arXiv:2511.20867.

🧪 Reproducible Results

E-GEO ships an evaluation harness so you can measure prompt quality yourself — no trust required. It scores whether the GEO rewriter moves a target item up in an LLM-simulated ranking.

pip install pyyaml jsonschema

# Deterministic, offline smoke run (no API key needed)
GEO_EVAL_MOCK=1 python geo_eval.py evaluate \
  --dataset eval/datasets/geo_smoke.jsonl --limit 5 --verbose

This is the exact check that runs in CI on every pull request. Reported metrics: avg_rank_improvement, win_rate, and stderr_rank_improvement.

Honest scope: these numbers are a proxy produced by an LLM-ranker, not a measurement of real ChatGPT/Perplexity rankings. See docs/evaluation.md for the full methodology, metric definitions, and limitations.

🖥️ Standalone CLI (`egeo`)

Beyond Claude Code, E-GEO ships a runtime-agnostic command line so the same GEO engine runs anywhere Python runs — local shells, notebooks, Docker, or CI. The CLI is a thin wrapper around the exact same geo_eval.py and llm_client.py modules used by the Claude Code agents, so there is no duplicated optimization logic — both runtimes share one source of truth.

Install

# From the repo root — installs the `egeo` console script + deps
pip install -e .

# ...or run without installing (deps: pip install pyyaml jsonschema)
python -m egeo --help

Commands

Command	What it does
`egeo optimize <file>`	Full pipeline — analyze → rank → rewrite → schema, writes `report.md`, `optimized/.md`, `schema/.json`, `analysis.json`
`egeo evaluate`	Run the evaluation harness (reuses `geo_eval.py`, identical metrics)
`egeo optimize-prompts`	Meta-optimize the rewriter prompt (non-destructive by default)
`egeo runtimes`	List available runtime adapters and their status

# Optimize a local content file (output dir defaults to ./geo-output)
egeo optimize examples/sample-input.md --out-dir ./geo-output

# Score prompt quality on a dataset
egeo evaluate --dataset eval/datasets/geo_smoke.jsonl --limit 5

# Inspect the runtime adapters
egeo runtimes

Offline / deterministic mode

Every command honors GEO_EVAL_MOCK=1, which swaps in a deterministic mock LLM client — no API key required. This is exactly how the CLI is exercised in CI:

GEO_EVAL_MOCK=1 egeo optimize examples/sample-input.md --out-dir /tmp/egeo
GEO_EVAL_MOCK=1 egeo evaluate --dataset eval/datasets/geo_smoke.jsonl --limit 3

Supported Runtimes

E-GEO exposes a small runtime adapter layer so the same agents (Analyzer, Ranker, Rewriter, Indexer) can be driven by different execution hosts:

Runtime	Aliases	Mode	Status	Description
`python`	`cli`, `local`	in-process	✅ Available	Pure-Python runtime behind the `egeo` CLI. Runs the full pipeline in-process and honors `GEO_EVAL_MOCK` for offline, deterministic runs.
`claude-code`	`claude`	host-executed	✅ Available	Executes the `.claude/` agents through Claude Code `/geo` slash commands on the host. Auto-detected when a `.claude/` directory is present.

Run egeo runtimes to print the live status of each adapter in your environment. Additional hosts (Cursor, Codex, Windsurf, …) can be added by implementing the RuntimeAdapter interface in egeo/runtimes.py.

🆚 E-GEO vs Other GEO Tools

Feature	E-GEO	GEO Optimizer	GEO-optim/GEO	Awesome GEO	Traditional SEO
Type	CLI + Claude Code	CLI + MCP	Research repo	Curated list	—
Content Rewriting	✅ Full pipeline	⚠️ Audit only	❌	❌	❌ No
AI-Ranking Simulation	✅ LLM-based	❌	❌	❌	❌ No
Schema Generation	✅ Auto JSON-LD	⚠️ Partial	❌	❌	❌ Manual
Competitive Analysis	✅ Built-in	❌	❌	❌	❌ No
Academic Foundation	✅ arXiv:2511.20867	✅ KDD 2024	✅ Original GEO paper	❌	❌ Heuristics
Multi-Runtime	✅ Python + Claude Code	✅ Python + MCP	❌	❌	❌
llms.txt Support	✅	✅	❌	📖 Listed	❌
Cost	Free / MIT	Free / MIT	Free	Free	Expensive

E-GEO is the only open-source GEO tool that combines content rewriting, ranking simulation, and schema generation in a single pipeline. Others focus on auditing or listing — E-GEO does the full optimization.

💎 Premium Output

E-GEO delivers outputs that look like they came from a $100M company:

┌─────────────────────────────────────────────────────────────┐
│  🎯 GEO AUDIT REPORT                                        │
├─────────────────────────────────────────────────────────────┤
│  URL: yoursite.com/pricing                                  │
│  Score: 78/100                                              │
│  Ranking Potential: ████████░░ 78%                          │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  ✅ STRENGTHS                                               │
│  • Clear value proposition                                  │
│  • Good content structure                                   │
│                                                             │
│  ⚠️ GAPS                                                    │
│  • Missing social proof → Add customer count                │
│  • No urgency signals → Add limited-time offer              │
│                                                             │
│  📈 PRIORITY ACTIONS                                        │
│  1. Add testimonials (+15 points)                           │
│  2. Include pricing comparison (+10 points)                 │
│  3. Add schema markup (+5 points)                           │
│                                                             │
└─────────────────────────────────────────────────────────────┘

🤖 How It Works

E-GEO uses 4 specialized AI agents orchestrated by Claude Code:

Agent	What it does	Output
🔍 Analyzer	Extracts content, scores GEO signals, identifies gaps	`analysis.json`
📊 Ranker	Simulates AI-engine ranking, predicts positions	Baseline score
✍️ Rewriter	Optimizes content while preserving brand voice	`optimized/*.md`
🗂️ Indexer	Generates schema markup and technical assets	`schema/*.json`

📁 What's Included

.claude/
├── CLAUDE.md                    # System knowledge base
├── output-styles/
│   └── geo-optimizer.md         # Premium formatting mode
├── agents/
│   ├── geo-analyzer.md          # Content analysis
│   ├── geo-rewriter.md          # Content optimization
│   ├── geo-ranker.md            # Ranking simulation
│   └── geo-indexer.md           # Schema generation
├── skills/
│   ├── competitive-analysis/    # Auto-triggered competitor analysis
│   ├── content-scoring/         # Auto-triggered scoring
│   └── schema-generator/        # Auto-triggered schema
└── commands/
    ├── geo.md                   # Main command
    ├── geo-audit.md
    ├── geo-optimize.md
    ├── geo-batch.md
    ├── geo-report.md
    └── geo-compete.md

🎁 Perfect For

🚀
SaaS Founders
_{AI-engine traffic}

💼
B2B Marketers
_{Landing pages}

🛍️
E-commerce
_{Product descriptions}

✍️
Content Creators
_{AI discoverability}

🏢
Agencies
_{GEO services}

📚 Documentation

Resource	Description
📖 Getting Started	Step-by-step tutorial
⚙️ How It Works	Technical deep dive
❓ FAQ	Common questions answered
🧩 skills.sh Playbook	Listing, ranking, and metadata checklist
🧪 Evaluation Harness	Dataset format, commands, metrics, and honest limitations
📝 Usage Guide	Complete command reference
📝 Research Paper	The science behind E-GEO

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Quick ways to contribute:

Report bugs via issues
Submit pull requests for features
Improve documentation
Share your GEO results

🔍 SEO & AI Search Glossary

E-GEO covers the full spectrum of AI search optimization. If you're searching for any of these, you're in the right place:

Term	What it means
GEO (Generative Engine Optimization)	Optimizing content for AI answer engines like ChatGPT, Perplexity, Gemini
AEO (Answer Engine Optimization)	Structuring content so AI engines can parse and cite it
AI SEO	Adapting traditional SEO for AI-powered search
LLM SEO	Optimization specifically for large language model responses
AI Visibility	How often and how well your brand appears in AI-generated answers
Citation Tracking	Monitoring whether AI engines cite your site as a source
llms.txt	A standard file (like robots.txt) that tells AI crawlers what content to prioritize

📜 License

MIT License - use it, modify it, sell with it. See LICENSE for details.

🙋 Support & Community

Issues: GitHub Issues
Discussions: GitHub Discussions
Research: E-GEO Paper (arXiv:2511.20867)

🚀 Ready to Rank Higher?

# Install
cp -r eGEOagents/.claude .

# Activate (in Claude Code)
/output-style geo-optimizer

# Optimize your first page
/geo https://yoursite.com

Built for the AI-first web — optimize your content for ChatGPT, Perplexity, Claude, and Gemini with E-GEO, the open-source GEO tool. 🌐

_{Made with ❤️ by Vera Badias • Based on research from arXiv:2511.20867}

_{🤖 This project is AI-assisted. See AI Transparency for details.}

Name		Name	Last commit message	Last commit date
Latest commit History 13 Commits
.claude		.claude
.github		.github
assets		assets
docs		docs
egeo		egeo
eval/datasets		eval/datasets
examples		examples
geo-output		geo-output
openspec		openspec
prompts		prompts
scripts		scripts
.gitignore		.gitignore
AGENTS.md		AGENTS.md
CHANGELOG.md		CHANGELOG.md
CLAUDE.md		CLAUDE.md
CODE_OF_CONDUCT.md		CODE_OF_CONDUCT.md
CONTRIBUTING.md		CONTRIBUTING.md
GEO-SYSTEM-BLUEPRINT.md		GEO-SYSTEM-BLUEPRINT.md
LICENSE		LICENSE
README.md		README.md
USAGE.md		USAGE.md
geo_eval.py		geo_eval.py
llm_client.py		llm_client.py
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt

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🌍 E-GEO

Generative Engine Optimization (GEO) & Answer Engine Optimization (AEO) for AI-Powered Search

✨ What is E-GEO?

📈 Why AI Visibility Matters in 2026

🚀 Quick Start (3 Steps)

1. Install

2. Activate

3. Optimize

🧩 Install as Skills (skills.sh)

📋 Commands

📊 What You Get

🎯 Results: Backed by Research

🧪 Reproducible Results

🖥️ Standalone CLI (egeo)

Install

Commands

Offline / deterministic mode

Supported Runtimes

🆚 E-GEO vs Other GEO Tools

💎 Premium Output

🤖 How It Works

📁 What's Included

🎁 Perfect For

📚 Documentation

🤝 Contributing

🔍 SEO & AI Search Glossary

📜 License

🙋 Support & Community

🚀 Ready to Rank Higher?

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