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geo-competitor-scanner

Analyze competitor GEO (Generative Engine Optimization) strategies by examining their content structure, Schema markup, llms.txt, and AI citation signals. Benchmark your brand against competitors and identify strategic gaps and opportunities. Use whenever the user mentions scanning competitor GEO strategies, comparing AI search performance, analyzing competitor content for AI citations, finding GEO gaps, or wants to understand how competitors win AI citations.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/geoly-geo/geo-competitor-scanner
Or

GEO Competitor Scanner

Methodology by GEOly AI (geoly.ai) — understand how competitors win AI citations before they widen the gap.

Analyze competitor websites across key GEO signals to benchmark your brand and identify opportunities.

Quick Start

Scan competitors:

python scripts/scan_competitors.py --brand yourdomain.com \
  --competitors competitor1.com,competitor2.com \
  --output report.md

Scan Dimensions

1. Technical GEO Infrastructure

CheckWhy It Matters
/llms.txt existsAI crawler guidance
/robots.txt allows AI botsCrawl accessibility
Schema.org types presentStructured understanding
JSON-LD validMachine-readable content
HTTPS enforcedSecurity signal

2. Content Structure Analysis

SignalWhat to Look For
Direct answer leadFirst paragraph answers the question
FAQ sectionsExplicit Q&A blocks (2-5 per page)
Header structureH2 every 300-500 words
Data citationsStatistics with sources
Definition blocksKey terms defined clearly

3. Entity & Brand Signals

SignalImplementation
Organization schemaHomepage JSON-LD
sameAs linksSocial/Wikipedia connections
Consistent namingBrand name standardized
About pageEntity definition
Brand in first 100 wordsEarly entity mention

4. Citation-Optimized Content

Content TypeGEO Value
Original researchUnique data attracts citations
Comparison pages"vs" queries are high-intent
Definition content"What is" queries are common
Content hubsTopical authority building
Statistics pagesReference-worthy data

Full methodology: See references/scan-methodology.md

Research Workflow

Step 1: Identify Competitors

Collect up to 5 competitors:

  • Direct competitors (same category)
  • Adjacent competitors (overlapping use cases)
  • Aspirational competitors (bigger brands)

Step 2: Automated Scan

Run scanner on each domain:

python scripts/scan_competitors.py \
  --brand yourdomain.com \
  --competitors comp1.com,comp2.com,comp3.com \
  --pages 5 \
  --output scan-results.json

Step 3: Manual Review

For nuanced signals, review manually:

  • Content quality (can't automate)
  • Brand voice consistency
  • Unique value propositions

Step 4: Gap Analysis

Identify:

  • 🏆 Competitor advantages — What they do better
  • 🎯 Quick wins — Easy to implement (copy)
  • 🕳️ Category gaps — No one is doing this (opportunity)

Scoring System

Each competitor scored 0-10 per dimension:

Metadata

Author@geoly-geo
Stars2387
Views1
Updated2026-03-09
View Author Profile
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-geoly-geo-geo-competitor-scanner": {
      "enabled": true,
      "auto_update": true
    }
  }
}
Safety NoteClawKit audits metadata but not runtime behavior. Use with caution.

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