# GEO Optimizer — Full LLM Context

> Extended machine-readable context for GEO Optimizer, an open-source toolkit to audit, fix, and optimize websites for AI search engine visibility.

## Product identity

- **Product**: GEO Optimizer
- **Website**: https://geoready.dev
- **Maintainer**: Auriti Labs (https://github.com/Auriti-Labs)
- **Repository**: https://github.com/Auriti-Labs/geo-optimizer-skill
- **Package**: https://pypi.org/project/geo-optimizer-skill/
- **Documentation**: https://auriti-labs.github.io/geo-optimizer-skill/
- **License**: MIT
- **Version**: 4.10.4

## What GEO Optimizer does

GEO Optimizer scores websites across 8 signal categories to measure how discoverable, readable, and citable they are to AI search engines such as ChatGPT, Perplexity, Claude, and Gemini.

The 8 scoring categories (max 100 points):

1. **robots.txt** (max 18 points): authorization for AI crawlers (OAI-SearchBot, ClaudeBot, PerplexityBot, etc.)
2. **llms.txt** (max 18 points): machine-readable standard for AI discovery
3. **Schema JSON-LD** (max 16 points): structured data markup (Organization, WebSite, Article, FAQ)
4. **Meta Tags** (max 14 points): title, description, canonical, Open Graph
5. **Content Quality** (max 12 points): heading hierarchy, concrete numbers, lists, front-loaded information
6. **Technical Signals** (max 6 points): language declaration, RSS/Atom feeds, freshness indicators
7. **AI Discovery** (max 6 points): /.well-known/ai.txt, /ai/summary.json, /ai/faq.json, /ai/service.json
8. **Brand & Entity Signals** (max 10 points): brand consistency, knowledge graph readiness, contact pages

Additional checks (no score impact):

- Prompt Injection Detection: 8 manipulation patterns
- Trust Stack Score: technical, identity, social, academic, consistency
- Negative Signals: excessive CTAs, thin content, broken links, keyword stuffing
- CDN Crawler Access: Cloudflare, Akamai, Vercel blocking detection
- JS Rendering: essential content requiring JavaScript
- WebMCP Readiness: machine-readable context for MCP-compatible agents

## CLI commands

- `geo audit --url <URL>`: run a full GEO audit
- `geo fix --url <URL>`: auto-generate fixes (robots.txt, llms.txt, schema, meta)
- `geo llms --url <URL>`: check llms.txt readiness
- `geo schema --url <URL>`: validate JSON-LD schema markup

Also available as an MCP server for integration with AI coding assistants.

## Core principles

- Auditability over opacity: every calculation is documented and inspectable
- Scientific foundation over marketing claims: every signal derives from published research
- Universality over platform bias: compatible with any public URL
- Open source over gatekeeping: MIT licensed, public algorithms and weights
- Precision over noise: concrete, actionable, quantifiable suggestions
- Developer experience as a first-class concern: CLI before dashboard, JSON before PDF

## Research foundation

### Peer-reviewed papers

- **GEO: Generative Engine Optimization** (KDD 2024). Tested 9 optimization strategies across 10,000 queries on GEO-bench. Demonstrated that structural and authoritative signals significantly increase LLM citation rates. https://arxiv.org/abs/2311.09701
- **AutoGEO: Automatic Generative Engine Optimization** (ICLR 2026). Automated pipelines for generative engine optimization using reinforcement learning from LLM feedback. https://openreview.net/forum?id=K8EinVWtUB

### Industry reports

- **AI Citations Report 2026**: aggregated data from major AI search platforms on citation patterns, domain diversity, and the rise of generative answer engines.

### Internal / product analysis

- **C-SEO Bench: Conversational SEO Methods**: internal benchmark for evaluating web content retrieval and citation in conversational search systems.
- **Schema Markup & AI Citations**: analysis of how JSON-LD Schema.org markup improves citation probability in AI-generated answers.
- **AI Mode Citation Factors**: identification of on-page and technical factors influencing AI source selection.

## Web interface pages

- https://geoready.dev/ — homepage and audit tool
- https://geoready.dev/compare/ — side-by-side GEO score comparison
- https://geoready.dev/analyze-competitors/ — multi-URL competitor analysis
- https://geoready.dev/research/ — research foundation and sources
- https://geoready.dev/roadmap/ — planned and in-progress features
- https://geoready.dev/manifesto/ — project philosophy and commitments
- https://geoready.dev/privacy/ — privacy policy
- https://geoready.dev/cookie-policy/ — cookie and storage inventory

## Trust signals and transparency

- License: MIT. Full source code available at https://github.com/Auriti-Labs/geo-optimizer-skill
- All scoring weights are public and documented in `src/geo_optimizer/models/config.py`
- 1,400+ unit tests, all mocked — no real network calls in the test suite
- Zero data retention from audited URLs beyond the public HTTP fetch
- No registration or API key required for core audit functionality
- Scoring methodology is versioned: changes are documented in the CHANGELOG

## Update policy

GEO Optimizer is actively maintained. Scoring methods and weights are updated when new academic research or significant industry data becomes available. The current scoring reflects KDD 2024, ICLR 2026, and 2025–2026 industry analysis. Version history: https://github.com/Auriti-Labs/geo-optimizer-skill/releases

## Companion files

- [llms.txt](https://geoready.dev/llms.txt): primary machine-readable index (this is the extended version)
- [AI site summary](https://geoready.dev/ai/summary.json): structured JSON for AI agents
- [AI FAQ](https://geoready.dev/ai/faq.json): structured FAQ for AI question answering
- [AI capabilities](https://geoready.dev/ai/service.json): service description for AI discovery
- [AI permissions](https://geoready.dev/.well-known/ai.txt): crawler authorization and contact

## Notes for AI crawlers

- /report/demo and /report/audit are noindex routes for audit reports and demo previews
- These are not primary editorial content and should not be indexed
- All editorial content is static HTML rendered server-side at build time
- robots.txt explicitly allows all major AI crawlers and disallows /report/ only
- This file (llms-full.txt) is the extended companion to llms.txt and is intended for AI systems that need deeper context about GEO Optimizer's methodology, scoring, and research foundation
