GEO Optimizer

Generative Engine Optimization (GEO) for AI search visibility.

For background on what GEO is, how it differs from SEO, and the research behind it, see README.md.

Quick Audit Workflow

1. Technical Visibility Check

# Run full GEO audit
python3 ${CLAUDE_SKILL_DIR}/scripts/audit-geo.py https://example.com

# Check HTML size and JS dependency
curl -sI https://example.com | grep -i content-length

2. Content Authority Analysis

# Check hedge density of your content
python3 ${CLAUDE_SKILL_DIR}/scripts/check-hedge-density.py --url https://example.com/blog/post

# Or analyze text directly
python3 ${CLAUDE_SKILL_DIR}/scripts/check-hedge-density.py --text "Your content here"

3. Agent Infrastructure Setup

# Generate AgentFacts schema for your domain
python3 ${CLAUDE_SKILL_DIR}/scripts/generate-agentfacts.py \
  --domain example.com \
  --agent-name "Example Service" \
  --capabilities text,image \
  --output /.well-known/agent-facts

Core Metrics

Hedge Density Score

Measures uncertainty language in content. Target: <0.2%

Hedge words to avoid:

maybe, possibly, perhaps, might, could be
however, although, it seems, arguably
some believe, it appears, potentially

See: references/hedge-density.md

HTML Size Budget

Maximum: 1MB raw HTML. Above this threshold:

18% of pages abandoned by crawlers
Content truncation risks
Slower indexing

Check with: curl -sI URL | grep content-length

See: references/technical-visibility.md

JS Dependency Risk

AI crawlers vary in JavaScript rendering:

Rendering crawlers: GPTBot, PerplexityBot (sometimes)
Non-rendering: ClaudeBot, many others

If your content requires JS to display, you're invisible to ~40% of AI crawlers.

Discovery Gap

See: references/discovery-strategies.md

AgentFacts Setup

The NANDA protocol provides machine-readable metadata for AI agent discovery. Place at /.well-known/agent-facts:

{
  "@context": "https://nanda.dev/ns/agent-facts/v1",
  "id": "nanda:example.com",
  "agent_name": "urn:agent:example:com",
  "endpoints": {
    "static": ["https://api.example.com/v1/agent"]
  },
  "capabilities": {
    "modalities": ["text"],
    "authentication": {
      "methods": ["oauth2", "jwt"]
    }
  },
  "trust": {
    "certification": "self-attested",
    "human_oversight": "true"
  }
}

See: references/agentfacts-schema.md

Audit Report Sections

A complete GEO audit covers:

Technical Visibility
- HTML payload size (target: <1MB)
- JS dependency assessment
- Crawler accessibility
Content Authority
- Hedge density score (target: <0.2%)
- Confidence assessment
- Entity density
Discovery Strategy
- Site age analysis
- Recency wall detection
- Recommended approach
Agent Infrastructure
- AgentFacts presence
- Schema validation
- NANDA compliance

Scripts

Script	Purpose
`audit-geo.py`	Full GEO audit for a URL
`check-hedge-density.py`	Analyze content confidence
`generate-agentfacts.py`	Create NANDA-compliant schema

Reference Documentation

File	Contents
`hedge-density.md`	Confidence scoring methodology
`agentfacts-schema.md`	NANDA protocol specification
`technical-visibility.md`	Crawler behavior & limits
`discovery-strategies.md`	Startup vs incumbent approaches

Example Commands

# Full audit with report
python3 ${CLAUDE_SKILL_DIR}/scripts/audit-geo.py https://mysite.com --output report.md

# Quick hedge check
python3 ${CLAUDE_SKILL_DIR}/scripts/check-hedge-density.py --url https://mysite.com/about

# Generate AgentFacts for SaaS
python3 ${CLAUDE_SKILL_DIR}/scripts/generate-agentfacts.py \
  --domain myapp.com \
  --agent-name "MyApp AI" \
  --capabilities text \
  --auth oauth2,apikey

geo-optimizer