# How to Perform a Full GEO + SEO Audit with Claude Code CLI > Perform a full GEO + SEO audit with Claude Code CLI. The geo-seo-claude repo provides a comprehensive audit with a single command, scoring up to 50 pages for optimized visibility. - Repository: [Zubair Trabzada/geo-seo-claude](https://github.com/zubair-trabzada/geo-seo-claude) - Tags: how-to-guide - Published: 2026-09-08 --- **The geo-seo-claude repository enables a complete Generative Engine Optimization (GEO) audit through a single `/geo audit` command in Claude Code CLI, crawling up to 50 pages and aggregating six weighted category scores into a composite 0-100 GEO score.** Performing a comprehensive **GEO + SEO audit** requires analyzing how AI engines perceive, cite, and rank your content across platforms like ChatGPT, Perplexity, and Google AI Overviews. The **zubair-trabzada/geo-seo-claude** open-source project implements this as a native Claude Code CLI skill, orchestrating parallel sub-agents that evaluate technical infrastructure, content authority, and platform readiness. ## The Three-Phase Audit Architecture The audit workflow defined in [`skills/geo-audit/SKILL.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/skills/geo-audit/SKILL.md) executes through three distinct phases that transform raw website data into actionable intelligence. ### Phase 1: Discovery and Crawling When you invoke the audit command, the CLI initiates **Discovery** by fetching the homepage to determine the business type, then crawls up to **50 pages** via sitemap or internal link analysis. This phase relies on [`scripts/fetch_page.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/fetch_page.py) to retrieve and parse HTML content, establishing the dataset for downstream analysis. ### Phase 2: Parallel Sub-Agent Analysis Five specialized sub-agents run concurrently to evaluate distinct optimization vectors: - **AI Visibility** ([`agents/geo-ai-visibility.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-ai-visibility.md)): Assesses citability, crawler access permissions, and brand authority metrics using [`scripts/citability_scorer.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/citability_scorer.py) and [`scripts/brand_scanner.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/brand_scanner.py). - **Platform Optimization** ([`agents/geo-platform-analysis.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-platform-analysis.md)): Evaluates readiness for ChatGPT, Perplexity, Google AI Overviews, Gemini, and Bing Copilot. - **Technical SEO** ([`agents/geo-technical.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-technical.md)): Audits robots.txt, server-side rendering (SSR), Core Web Vitals, security headers, and mobile responsiveness. - **Content E-E-A-T** ([`agents/geo-content.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-content.md)): Scores Experience, Expertise, Authoritativeness, and Trustworthiness signals. - **Schema Markup** ([`agents/geo-schema.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-schema.md)): Detects, validates, and generates JSON-LD structured data using templates from the `schema/` directory. Each sub-agent produces a **0-100 score** and a detailed findings report. ### Phase 3: Score Aggregation and Reporting The **composite GEO score** calculates as a weighted average: **citability 25%**, **brand 20%**, **E-E-A-T 20%**, **technical 15%**, **schema 10%**, and **platform 10%**. The orchestrator generates [`GEO-AUDIT-REPORT.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/GEO-AUDIT-REPORT.md) containing severity-ranked issues and a prioritized 30-day action plan. ## How to Run a Full GEO Audit from the CLI Execute the complete audit workflow with the primary command: ```text /geo audit https://example.com ``` This command coordinates the three-phase pipeline: discovery, parallel sub-agent analysis, and weighted score aggregation. The output writes to [`GEO-AUDIT-REPORT.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/GEO-AUDIT-REPORT.md) in your current working directory, containing technical diagnostics and remediation steps. ## Generating Client-Ready Reports Transform raw audit data into polished deliverables for stakeholders: ```text /geo report https://example.com ``` This generates [`GEO-CLIENT-REPORT.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/GEO-CLIENT-REPORT.md) with an executive summary, score dashboard, and prioritized action plan. For PDF distribution (requires the `reportlab` Python package): ```text /geo report-pdf https://example.com ``` This calls [`scripts/generate_pdf_report.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/generate_pdf_report.py) to produce `GEO-REPORT-.pdf` with color-coded score gauges, methodology appendices, and visual charts rendered from [`templates/geo-report-template.html`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/templates/geo-report-template.html) and [`templates/geo-report-style.css`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/templates/geo-report-style.css). ## Quick Audits and Individual Sub-Skills For rapid assessment before committing to a full crawl: ```text /geo quick https://example.com ``` Returns an inline terminal summary and GEO score within 60 seconds, optionally saving to a CRM prospect record. Run individual analysis modules by calling specific sub-skills: ```text /geo technical https://example.com ``` This invokes only the technical SEO agent ([`agents/geo-technical.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-technical.md)), outputting [`GEO-TECHNICAL-AUDIT.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/GEO-TECHNICAL-AUDIT.md) with detailed infrastructure checklists. ## Core Components and File Structure The audit system relies on these key files within the repository: | Component | Role | Key Files | |-----------|------|-----------| | **Skill Router** | Routes `/geo` commands to sub-skills | [`geo/SKILL.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/geo/SKILL.md) | | **Audit Orchestrator** | Implements the three-phase workflow | [`skills/geo-audit/SKILL.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/skills/geo-audit/SKILL.md) | | **Sub-Agents** | Domain-specific analysis modules | [`agents/geo-ai-visibility.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-ai-visibility.md), [`agents/geo-platform-analysis.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-platform-analysis.md), [`agents/geo-technical.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-technical.md), [`agents/geo-content.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-content.md), [`agents/geo-schema.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/agents/geo-schema.md) | | **Python Utilities** | Data fetching and scoring logic | [`scripts/fetch_page.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/fetch_page.py), [`scripts/citability_scorer.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/citability_scorer.py), [`scripts/brand_scanner.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/brand_scanner.py), [`scripts/llmstxt_generator.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/llmstxt_generator.py), [`scripts/generate_pdf_report.py`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/scripts/generate_pdf_report.py) | | **Schema Templates** | JSON-LD examples for validation | `schema/*.json` | | **Report Templates** | PDF generation assets | [`templates/geo-report-template.html`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/templates/geo-report-template.html), [`templates/geo-report-style.css`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/templates/geo-report-style.css) | Reference these files in [`docs/architecture.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/docs/architecture.md) and [`docs/commands-reference.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/docs/commands-reference.md) for deep technical implementation details. ## Summary - **Single-command execution**: Run `/geo audit ` to trigger the complete three-phase workflow. - **Parallel analysis**: Five specialized sub-agents evaluate AI visibility, platform readiness, technical SEO, E-E-A-T, and schema markup simultaneously. - **Weighted scoring**: The composite GEO score applies specific weights (citability 25%, brand 20%, E-E-A-T 20%) to prioritize AI-citation factors. - **Multiple output formats**: Generate Markdown technical reports, client-ready summaries, or styled PDFs via `/geo report` and `/geo report-pdf`. - **Modular architecture**: Individual sub-skills like `/geo technical` allow targeted audits without full site crawls. ## Frequently Asked Questions ### How long does a full GEO audit take to complete? A standard audit crawls up to 50 pages and typically completes in 3-5 minutes depending on site speed and complexity. The `/geo quick` command provides a 60-second snapshot for rapid assessment, while full PDF generation adds additional processing time for rendering charts and formatting. ### What is the difference between GEO and traditional SEO? **Generative Engine Optimization** focuses specifically on how AI systems (ChatGPT, Perplexity, Google AI Overviews) cite, summarize, and recommend content, whereas traditional SEO targets ranking in conventional search results. The audit weights **citability** (25%) and **platform optimization** (10%) heavily because these metrics directly influence AI citation behavior rather than just SERP positioning. ### Can I customize the audit crawl depth or scoring weights? The default configuration in [`skills/geo-audit/SKILL.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/skills/geo-audit/SKILL.md) limits crawling to 50 pages to balance thoroughness with execution time. While the weighted scoring formula (citability 25%, brand 20%, etc.) is hardcoded in the current implementation, you can run individual sub-skills like `/geo technical` or `/geo content` to focus analysis on specific categories without the composite score aggregation. ### What files are generated after running the audit? The primary output is [`GEO-AUDIT-REPORT.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/GEO-AUDIT-REPORT.md) containing technical findings and action plans. When using `/geo report`, the system creates [`GEO-CLIENT-REPORT.md`](https://github.com/zubair-trabzada/geo-seo-claude/blob/main/GEO-CLIENT-REPORT.md) for stakeholder presentations. The `/geo report-pdf` command generates `GEO-REPORT-.pdf` using the HTML/CSS templates in the `templates/` directory and the `reportlab` Python library for professional distribution.