geo-optimizer-skill 4.11.1

Generative Engine Optimization toolkit — make websites visible to AI search engines

Open-source GEO audit engine for AI search visibility and citability.

GEO Optimizer helps you audit whether a website can be crawled, understood, cited, and monitored by AI answer engines.

Quick Start · Live Demo · Pricing · Early Access · Documentation · Changelog

---

Why this exists

AI search engines give direct answers and cite their sources. If your site isn't optimized, you're invisible — even if you rank #1 on Google.

User: "What's the best mortgage calculator?"

Perplexity: "According to [Competitor.com], the formula is..."
             ↑ They appear. You don't.

GEO Optimizer audits your site against 47 research-backed methods (Princeton KDD 2024, AutoGEO ICLR 2026) and generates the fixes.

---

GEO is not traditional SEO

SEO and GEO answer different questions:

• SEO optimizes for ranking and visibility in traditional search result pages — crawlability, backlinks, keyword signals.
• GEO measures whether an AI answer engine can read, parse, understand, and cite your content when generating a response.
• A site can rank well on Google and still be largely opaque to AI systems — missing structured data, no llms.txt, bot access blocked, thin factual density.

GEO Optimizer focuses on the technical and structural signals that AI answer engines use: robots.txt bot permissions, llms.txt presence and depth, JSON-LD schema richness, brand entity coherence, and content citability across 47 methods. These complement traditional SEO work rather than replacing it.

---

Try it online

Free audit	geoready.dev — single-URL GEO score, no account required
Pricing	geoready.dev/pricing — plans and feature comparison
Early access	geoready.dev/early-access — join the list for Pro monitoring (planned)

---

Open-source vs GeoReady Platform

	GEO Optimizer CLI	GeoReady.dev Free	GeoReady Pro (early access, planned)
License / access	MIT, open-source	Free, no account	Early access waitlist — not yet publicly available
Core use	Local audit engine, CI/CD integration, JSON output	Web audit, score preview, educational pages	Monitoring, score history, regression alerts, agency reporting
Target	Developers, automation	Developers, SEO specialists	Ongoing clients, multi-site portfolios
Pricing	Free forever	Free forever	Planned — see geoready.dev/pricing

The CLI and web audit remain MIT-licensed and free. The GeoReady platform adds server-side continuity — monitoring, history, and team features — that a local CLI cannot provide on its own.

---

Quick Start

pip install geo-optimizer-skill

# Audit any site — get a score 0-100 with actionable recommendations
geo audit --url https://yoursite.com

# Audit a full sitemap and surface weakest pages first
geo audit --sitemap https://yoursite.com/sitemap.xml --max-urls 25

# Compare before/after versions of a page
geo diff --before https://yoursite.com/page-old --after https://yoursite.com/page-new

# Save history and detect regressions over time
geo audit --url https://yoursite.com --save-history --regression

# Show the saved trend for a site
geo history --url https://yoursite.com

# Passive AI visibility snapshot for a domain
geo monitor --domain yoursite.com

# Save or query archived AI answer snapshots
geo snapshots --query "best GEO tool" --from 2026-03-01 --to 2026-03-30

# Score citation quality inside an archived answer snapshot
geo snapshots --quality --snapshot-id 12 --target-domain yoursite.com

# Run recurring monitoring and generate an HTML trend report
geo track --url https://yoursite.com --report --output ./geo-track-report.html

# Auto-generate all missing files (robots.txt, llms.txt, schema, meta)
geo fix --url https://yoursite.com --apply

# Generate llms.txt from sitemap
geo llms --base-url https://yoursite.com --output ./public/llms.txt

# Generate JSON-LD schema
geo schema --type faq --url https://yoursite.com

---

What it checks

Area	Points	What GEO Optimizer looks for
Robots.txt	/18	27 AI bots across 3 tiers (training, search, user). Citation bots explicitly allowed?
llms.txt	/18	Present, has H1 + blockquote, sections, links, depth. Companion llms-full.txt?
Schema JSON-LD	/16	WebSite, Organization, FAQPage, Article. Schema richness (5+ attributes)?
Meta Tags	/14	Title, description, canonical, Open Graph complete?
Content	/12	H1, statistics, external citations, heading hierarchy, lists/tables, front-loading?
Brand & Entity	/10	Brand name coherence, Knowledge Graph links (Wikipedia/Wikidata/LinkedIn/Crunchbase), about page, geo signals, topic authority
Signals	/6	<html lang>, RSS/Atom feed, dateModified freshness?
AI Discovery	/6	.well-known/ai.txt, /ai/summary.json, /ai/faq.json, /ai/service.json?

Score bands: 86-100 Excellent · 68-85 Good · 36-67 Foundation · 0-35 Critical

Bonus checks (informational, do not affect score):

Check	What it detects
CDN Crawler Access	Does Cloudflare/Akamai/Vercel block GPTBot, ClaudeBot, PerplexityBot?
JS Rendering	Is content accessible without JavaScript? SPA framework detection
WebMCP Readiness	Chrome WebMCP support: registerTool(), toolname attributes, potentialAction schema
Negative Signals	8 anti-citation signals: CTA overload, popups, thin content, keyword stuffing, missing author, boilerplate ratio
Prompt Injection Detection	8 manipulation patterns: hidden text, invisible Unicode, LLM instructions, HTML comment injection, monochrome text, micro-font, data-attr injection, aria-hidden abuse
Trust Stack Score	5-layer trust aggregation (Technical, Identity, Social, Academic, Consistency) — composite grade A-F
RAG Chunk Readiness	Content segmentation for RAG retrieval: section word counts, definition openings, heading boundaries, anchor sentences 🆕 v4.7
Content Decay Prediction	Detects temporal, statistical, version, event, and price decay patterns — evergreen score 0-100 🆕 v4.7
Platform Citation Profile	Per-platform readiness scores for ChatGPT, Perplexity, Google AI 🆕 v4.7

Plus a separate Citability Score (0-100) measuring content quality across 47 methods: Quotation +41% · Statistics +33% · Fluency +29% · Cite Sources +27% · and 43 more.

Additional tools

geo coherence --sitemap https://example.com/sitemap.xml  # Cross-page terminology consistency
geo logs --file access.log                                # AI Crawler Activity — crawler evidence from user-agent logs
geo access --url https://example.com                      # Agent Access Audit — browser vs AI bot access simulation

GEO Optimizer checks whether websites can be crawled, understood, cited, and monitored by AI answer engines:

• Crawled — robots.txt, CDN access, AI-bot reachability
• Understood — schema, llms.txt, content structure
• Cited — citability signals across 47 research-backed methods
• Monitored — geo logs (crawler evidence) and geo access (access simulation)

Note on wording: AI Crawler Activity reports crawler evidence from server-log user-agents, not AI answer citation tracking. Agent Access Audit reports citation readiness (whether bots can reach and parse the page) — it does not guarantee AI citations.

Optional LLM-powered analysis (pip install geo-optimizer-skill[llm]): brand sentiment, citation attribution, multi-turn persistence, cross-platform citation map, prompt library.

---

Output formats

geo audit --url https://example.com --format text     # Human-readable (default)
geo audit --url https://example.com --format json      # Machine-readable
geo audit --sitemap https://example.com/sitemap.xml    # Batch sitemap audit (text)
geo audit --sitemap https://example.com/sitemap.xml --format json  # Batch sitemap audit (JSON)
geo audit --url https://example.com --format rich      # Colored terminal
geo audit --url https://example.com --format html      # Self-contained report
geo audit --url https://example.com --format sarif     # GitHub Code Scanning
geo audit --url https://example.com --format junit     # Jenkins, GitLab CI
geo audit --url https://example.com --format github    # GitHub Actions annotations
geo monitor --domain example.com                       # Passive AI visibility readiness
geo snapshots --query "best GEO tool"                 # Saved AI answer archive
geo snapshots --quality --snapshot-id 12              # Citation quality tiers for a saved answer
geo history --url https://example.com                  # Saved score trend
geo track --url https://example.com --report           # Monitoring HTML report

The JSON output format is intended to remain stable across minor versions and acts as the machine-readable integration contract for the GeoReady platform.

---

CI/CD Integration

# .github/workflows/geo.yml
- uses: Auriti-Labs/geo-optimizer-skill@v1
  with:
    url: https://yoursite.com
    min-score: 70        # Fail if score drops below 70
    format: sarif        # Upload to GitHub Security tab

Works with GitHub Actions, GitLab CI, Jenkins, CircleCI, and any CI that runs Python.

For longitudinal checks, persist snapshots and fail on regressions:

geo audit --url https://yoursite.com --save-history --regression

---

MCP Server

Use GEO Optimizer from Claude, Cursor, Windsurf, or any MCP client:

pip install geo-optimizer-skill[mcp]
claude mcp add geo-optimizer -- geo-mcp

Then ask: "audit my site and fix what's missing"

Tool	Purpose
geo_audit	Full audit with score + recommendations
geo_fix	Generate fix files
geo_llms_generate	Generate llms.txt
geo_citability	Content citability analysis (47 methods)
geo_schema_validate	Validate JSON-LD
geo_compare	Compare multiple sites
geo_gap_analysis	Explain the gap between two sites and prioritize fixes
geo_ai_discovery	Check AI discovery endpoints
geo_check_bots	Check bot access via robots.txt
geo_trust_score	5-layer trust signal aggregation
geo_negative_signals	8 anti-citation signal detection
geo_factual_accuracy	Audit unsourced claims, contradictions, and broken citations

---

Use as AI Context

Load the right file into your AI assistant for GEO expertise:

Platform	File
Claude Projects	ai-context/claude-project.md
ChatGPT Custom GPT	ai-context/chatgpt-custom-gpt.md
Cursor	ai-context/cursor.mdc
Windsurf	ai-context/windsurf.md
Kiro	ai-context/kiro-steering.md

---

Internal Skill System

The repository now includes a structured internal skill catalog for maintainers at src/geo_optimizer/skills/catalog/ plus validation rules and examples. See docs/skill-system.md for the v1 architecture.

---

Python API

from geo_optimizer import audit

result = audit("https://example.com")
print(result.score)                      # 85
print(result.band)                       # "good"
print(result.citability.total_score)     # 72
print(result.score_breakdown)            # {"robots": 18, "llms": 14, ...}
print(result.recommendations)            # ["Add FAQPage schema..."]

Async variant:

from geo_optimizer import audit_async
result = await audit_async("https://example.com")

---

Dynamic Badge

Show your GEO score in your README:

![GEO Score](https://geoready.dev/badge?url=https://yoursite.com)

Colors: 86-100 green · 68-85 cyan · 36-67 yellow · 0-35 red. Cached 1h.

---

Plugin System

Extend the audit with custom checks via entry points:

[project.entry-points."geo_optimizer.checks"]
my_check = "mypackage:MyCheck"

See examples/example_plugin.py for a working example.

---

Research Foundation

Paper	Venue	Key Finding
GEO: Generative Engine Optimization	KDD 2024	9 methods tested on 10k queries. Cite Sources: +115%, Statistics: +40%
AutoGEO	ICLR 2026	Automatic rule extraction. +50.99% over Princeton baseline
C-SEO Bench	2025	Most content manipulation is ineffective. Infrastructure matters most

We focus on technical infrastructure (robots.txt, llms.txt, schema, meta) over content rewriting. The research confirms: if crawlers can't find and parse your content, prose optimization doesn't matter.

GEO Optimizer translates these findings into technical and content-level signals that can be operationally audited and tracked over time.

---

Roadmap

This project follows a deliberate release cadence — focused waves, not noisy patches.

Version	Window	Codename
v4.10.0	Late Apr 2026	Veil
v4.11.0	Mid / Late Jul 2026	Static
v4.12.0	Sep 2026	Ledger
v4.13.0	Nov 2026	Quiet Glass
v4.14.0-rc1	Jan 2027	Threshold
v4.14.0-rc2 / v4.15.0	Mar 2027	Pale Signal
v5.0.0	May 2027	Black Archive

Next focus areas: signal architecture, retrieval surface analysis, scoring recalibration, and structural pattern recognition. The v5.0 cycle represents a broader architectural evolution.

Full release calendar, philosophy, and direction → docs/ROADMAP.md

---

Security

All URL inputs are validated against private IP ranges (RFC 1918, loopback, link-local, cloud metadata) with DNS pinning before any request. See SECURITY.md for reporting vulnerabilities.

---

Contributing

git clone https://github.com/YOUR_USERNAME/geo-optimizer-skill.git
cd geo-optimizer-skill && pip install -e ".[dev]"
pytest tests/ -v   # 1309 tests, all mocked

Bug reports · Feature requests · CONTRIBUTING.md

---

Run the CLI locally, try the free audit online, check planned pricing, or join the early access list for monitoring.

---

MIT License · Built by Auriti Labs

If this saved you time, a star helps others find it.

Star History