GEO-SEO AnalysisSkill

Added to Onei Sep 8, 2026

MIT

Summary

Claude Code skill that audits a site for visibility in AI answers — citability scoring, AI-crawler access, llms.txt, schema markup and brand-mention scanning — plus classic technical SEO.

Features

Full parallel audit across five subagents: AI visibility, platforms, technical, content, schema
Citability scoring for how quotable each content block is to an answer engine
robots.txt analysis for 14+ named AI crawlers
llms.txt analysis and generation
Brand-mention scanning across YouTube, Reddit, Wikipedia and LinkedIn
Schema markup detection, validation and generation
Client-ready PDF reports, proposals and month-over-month delta comparisons

Install This Skill

Add this skill to your favorite AI agent in a few steps.

Any AI agent

This skill is plain instructions — it works with any assistant that accepts custom instructions or system prompts.

Copy the skill content with the button below.
Paste it into your agent's instruction file or system prompt (for example AGENTS.md, .cursorrules, or a custom instructions field).
Ask the agent to apply the skill whenever the task matches.

Claude Code & Claude apps

Claude loads skills automatically from its skills directory.

Claude Code

Create a skill folder — personal: ~/.claude/skills/geo-seo-analysis/, or per-project: .claude/skills/geo-seo-analysis/
Save the skill content as SKILL.md inside that folder.
Claude Code picks it up automatically and invokes it when relevant.

mkdir -p ~/.claude/skills/geo-seo-analysis

Claude.ai / Claude Desktop

Enable Skills under Settings → Capabilities, then upload the skill (a folder or zip containing SKILL.md).

One-prompt install

Paste this prompt into any agent with web access and it will install the skill for you.

Install the "GEO-SEO Analysis" skill from Onei AI. Fetch https://onei.ai/skills/geo-seo-analysis, extract the full skill content from the page, and save it where you load skills from (for Claude Code: .claude/skills/geo-seo-analysis/SKILL.md). From now on, apply this skill whenever it is relevant to my request.

Skill Content

Markdown Content

Copy this content and use it with your preferred AI agent

---
name: geo
description: >
  GEO-first SEO analysis tool. Optimizes websites for AI-powered search engines
  (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) while maintaining
  traditional SEO foundations. Performs full GEO audits, citability scoring,
  AI crawler analysis, llms.txt generation, brand mention scanning, platform-specific
  optimization, schema markup, technical SEO, content quality (E-E-A-T), and
  client-ready GEO report generation. Use when user says "geo", "seo", "audit",
  "AI search", "AI visibility", "optimize", "citability", "llms.txt", "schema",
  "brand mentions", "GEO report", or any URL for analysis.
allowed-tools: Read, Grep, Glob, Bash, WebFetch, Write
---

# GEO-SEO Analysis Tool — Claude Code Skill (February 2026)

> **Philosophy:** GEO-first, SEO-supported. AI search is eating traditional search.
> This tool optimizes for where traffic is going, not where it was.

---

## Quick Reference

| Command | What It Does |
|---------|-------------|
| `/geo audit <url>` | Full GEO + SEO audit with parallel subagents |
| `/geo page <url>` | Deep single-page GEO analysis |
| `/geo citability <url>` | Score content for AI citation readiness |
| `/geo crawlers <url>` | Check AI crawler access (robots.txt analysis) |
| `/geo llmstxt <url>` | Analyze or generate llms.txt file |
| `/geo brands <url>` | Scan brand mentions across AI-cited platforms |
| `/geo platforms <url>` | Platform-specific optimization (ChatGPT, Perplexity, Google AIO) |
| `/geo schema <url>` | Detect, validate, and generate structured data |
| `/geo technical <url>` | Traditional technical SEO audit |
| `/geo content <url>` | Content quality and E-E-A-T assessment |
| `/geo report <url>` | Generate client-ready GEO deliverable |
| `/geo report-pdf <url>` | Generate professional PDF report with charts and scores |
| `/geo quick <url>` | 60-second GEO visibility snapshot |
| `/geo prospect <cmd>` | CRM-lite: manage prospects through the sales pipeline |
| `/geo proposal <domain>` | Auto-generate client proposal from audit data |
| `/geo compare <domain>` | Monthly delta report: show score improvements to client |
| `/geo update` | Pull latest GEO skill updates from upstream |

---

## Market Context (Why GEO Matters)

| Metric | Value | Source |
|--------|-------|--------|
| GEO services market (2025) | $850M-$886M | Yahoo Finance / Superlines |
| Projected GEO market (2031) | $7.3B (34% CAGR) | Industry analysts |
| AI-referred sessions growth | +527% (Jan-May 2025) | SparkToro |
| AI traffic conversion vs organic | 4.4x higher | Industry data |
| Google AI Overviews reach | 1.5B users/month, 200+ countries | Google |
| ChatGPT weekly active users | 900M+ | OpenAI |
| Perplexity monthly queries | 500M+ | Perplexity |
| Gartner: search traffic drop by 2028 | -50% | Gartner |
| Marketers investing in GEO | Only 23% | Industry surveys |
| Brand mentions vs backlinks for AI | 3x stronger correlation | Ahrefs (Dec 2025) |

---

## Orchestration Logic

### Full Audit (`/geo audit <url>`)

**Phase 1: Discovery (Sequential)**
1. Fetch homepage HTML (curl or WebFetch)
2. Detect business type (SaaS, Local, E-commerce, Publisher, Agency, Other)
3. Extract key pages from sitemap.xml or internal links (up to 50 pages)

**Phase 2: Parallel Analysis (Delegate to Subagents)**
Launch these 5 subagents simultaneously:

| Subagent | File | Responsibility |
|----------|------|---------------|
| geo-ai-visibility | `agents/geo-ai-visibility.md` | GEO audit, citability, AI crawlers, llms.txt, brand mentions |
| geo-platform-analysis | `agents/geo-platform-analysis.md` | Platform-specific optimization (ChatGPT, Perplexity, Google AIO) |
| geo-technical | `agents/geo-technical.md` | Technical SEO, Core Web Vitals, crawlability, indexability |
| geo-content | `agents/geo-content.md` | Content quality, E-E-A-T, readability, AI content detection |
| geo-schema | `agents/geo-schema.md` | Schema markup detection, validation, generation |

**Phase 3: Synthesis (Sequential)**
1. Collect all subagent reports
2. Calculate composite GEO Score (0-100)
3. Generate prioritized action plan
4. Output client-ready report

### Scoring Methodology

| Category | Weight | Measured By |
|----------|--------|-------------|
| AI Citability & Visibility | 25% | Passage scoring, answer block quality, AI crawler access |
| Brand Authority Signals | 20% | Mentions on Reddit, YouTube, Wikipedia, LinkedIn; entity presence |
| Content Quality & E-E-A-T | 20% | Expertise signals, original data, author credentials |
| Technical Foundations | 15% | SSR, Core Web Vitals, crawlability, mobile, security |
| Structured Data | 10% | Schema completeness, JSON-LD validation, rich result eligibility |
| Platform Optimization | 10% | Platform-specific readiness (Google AIO, ChatGPT, Perplexity) |

---

## Business Type Detection

Analyze homepage for patterns:

| Type | Signals |
|------|---------|
| **SaaS** | Pricing page, "Sign up", "Free trial", "/app", "/dashboard", API docs |
| **Local Service** | Phone number, address, "Near me", Google Maps embed, service area |
| **E-commerce** | Product pages, cart, "Add to cart", price elements, product schema |
| **Publisher** | Blog, articles, bylines, publication dates, article schema |
| **Agency** | Portfolio, case studies, "Our services", client logos, testimonials |
| **Other** | Default — apply general GEO best practices |

Adjust recommendations based on detected type. Local businesses need LocalBusiness schema and Google Business Profile optimization. SaaS needs SoftwareApplication schema and comparison page strategy. E-commerce needs Product schema and review aggregation.

---

## Sub-Skills (14 Specialized Components)

| # | Skill | Directory | Purpose |
|---|-------|-----------|---------|
| 1 | geo-audit | `skills/geo-audit/` | Full audit orchestration and scoring |
| 2 | geo-citability | `skills/geo-citability/` | Passage-level AI citation readiness |
| 3 | geo-crawlers | `skills/geo-crawlers/` | AI crawler access and robots.txt |
| 4 | geo-llmstxt | `skills/geo-llmstxt/` | llms.txt standard analysis and generation |
| 5 | geo-brand-mentions | `skills/geo-brand-mentions/` | Brand presence on AI-cited platforms |
| 6 | geo-platform-optimizer | `skills/geo-platform-optimizer/` | Platform-specific AI search optimization |
| 7 | geo-schema | `skills/geo-schema/` | Structured data for AI discoverability |
| 8 | geo-technical | `skills/geo-technical/` | Technical SEO foundations |
| 9 | geo-content | `skills/geo-content/` | Content quality and E-E-A-T |
| 10 | geo-report | `skills/geo-report/` | Client-ready deliverable generation |
| 11 | geo-prospect | `skills/geo-prospect/` | CRM-lite prospect and client pipeline management |
| 12 | geo-proposal | `skills/geo-proposal/` | Auto-generate client proposals from audit data |
| 13 | geo-compare | `skills/geo-compare/` | Monthly delta tracking and progress reports |
| 14 | geo-update | `skills/geo-update/` | Pull latest updates from upstream repository |

---

## Subagents (5 Parallel Workers)

| Agent | File | Skills Used |
|-------|------|-------------|
| geo-ai-visibility | `agents/geo-ai-visibility.md` | geo-citability, geo-crawlers, geo-llmstxt, geo-brand-mentions |
| geo-platform-analysis | `agents/geo-platform-analysis.md` | geo-platform-optimizer |
| geo-technical | `agents/geo-technical.md` | geo-technical |
| geo-content | `agents/geo-content.md` | geo-content |
| geo-schema | `agents/geo-schema.md` | geo-schema |

---

## Output Files

All commands generate structured output:

| Command | Output File |
|---------|------------|
| `/geo audit` | `GEO-AUDIT-REPORT.md` |
| `/geo page` | `GEO-PAGE-ANALYSIS.md` |
| `/geo citability` | `GEO-CITABILITY-SCORE.md` |
| `/geo crawlers` | `GEO-CRAWLER-ACCESS.md` |
| `/geo llmstxt` | `llms.txt` (ready to deploy) |
| `/geo brands` | `GEO-BRAND-MENTIONS.md` |
| `/geo platforms` | `GEO-PLATFORM-OPTIMIZATION.md` |
| `/geo schema` | `GEO-SCHEMA-REPORT.md` + generated JSON-LD |
| `/geo technical` | `GEO-TECHNICAL-AUDIT.md` |
| `/geo content` | `GEO-CONTENT-ANALYSIS.md` |
| `/geo report` | `GEO-CLIENT-REPORT.md` (presentation-ready) |
| `/geo report-pdf` | `GEO-REPORT.pdf` (professional PDF with charts) |
| `/geo quick` | Inline summary (no file) |
| `/geo prospect` | Updates `~/.geo-prospects/prospects.json` |
| `/geo proposal` | `~/.geo-prospects/proposals/<domain>-proposal-<date>.md` |
| `/geo compare` | `~/.geo-prospects/reports/<domain>-monthly-<YYYY-MM>.md` |

---

## PDF Report Generation

The `/geo report-pdf <url>` command converts `GEO-AUDIT-REPORT.md` into a styled, client-ready PDF.

### Requirements
- **pandoc** — `brew install pandoc`
- **Google Chrome** — `/Applications/Google Chrome.app/` (standard Mac install)

No Python dependencies required for PDF generation.

### What the PDF Includes
- **Cover page** — dark navy gradient, GEO score badge, brand/domain/date/location metadata
- **Color-coded score tables** — cells with `XX/100` values are automatically colored green/blue/amber/orange/red
- **Severity-tagged findings** — Critical/High/Medium/Low sections get colored left-border callout blocks
- **Section page breaks** — major sections break to new pages automatically
- **Styled code blocks** — JSON schema templates render with dark monospace theme

### Templates
Bundled at `~/.claude/skills/geo/templates/`:
- `geo-report-style.css` — stylesheet (edit colors, fonts, layout here)
- `geo-report-template.html` — pandoc HTML template (edit cover fields here)

### Workflow
1. Run `/geo audit <url>` to produce `GEO-AUDIT-REPORT.md`
2. Run `/geo report-pdf` — extracts metadata from the report and runs:
   ```bash
   pandoc GEO-AUDIT-REPORT.md \
     --to html5 --standalone --embed-resources \
     --template ~/.claude/skills/geo/templates/geo-report-template.html \
     --css ~/.claude/skills/geo/templates/geo-report-style.css \
     --metadata brand_name="..." --metadata geo_score="..." \
     -o GEO-REPORT.html

   "/Applications/Google Chrome.app/Contents/MacOS/Google Chrome" \
     --headless=new --disable-gpu --no-sandbox \
     --print-to-pdf="$(pwd)/GEO-REPORT.pdf" \
     --print-to-pdf-no-header --no-pdf-header-footer \
     --virtual-time-budget=5000 \
     "file://$(pwd)/GEO-REPORT.html"
   ```
3. Output: `GEO-REPORT.pdf` in the current directory

---

## Quality Gates

- **Crawl limit:** Max 50 pages per audit (focus on quality over quantity)
- **Timeout:** 30 seconds per page fetch
- **Rate limiting:** 1-second delay between requests, max 5 concurrent
- **Robots.txt:** Always respect, always check
- **Duplicate detection:** Skip pages with >80% content similarity

---

## Quick Start Examples

```
# Full GEO audit of a website
/geo audit https://example.com

# Check if AI bots can see your site
/geo crawlers https://example.com

# Score a specific page for AI citability
/geo citability https://example.com/blog/best-article

# Generate an llms.txt file for your site
/geo llmstxt https://example.com

# Get a 60-second visibility snapshot
/geo quick https://example.com

# Generate a client-ready report
/geo report https://example.com
```

Usage Instructions

Learn how to use this skill with different AI agents.

Claude Desktop

Install into Claude Code with the project's shell installer:

curl -fsSL https://raw.githubusercontent.com/zubair-trabzada/geo-seo-claude/main/install.sh | bash

Then run /geo audit https://example.com. The skill uses only Read, Grep, Glob, Bash, WebFetch and Write, so no API keys or extra services are required.

Generic Instructions

Copy the geo/ folder — SKILL.md plus its agents/ subagent definitions — into your agent's skills directory. The skill assumes an agent that can fetch URLs and run shell commands.

Example Usage

/geo quick https://example.com

A 60-second visibility snapshot: whether AI crawlers are allowed, whether an llms.txt exists, how citable the main content blocks are, and what schema the page already emits. /geo audit runs the same checks across up to fifty pages with the full subagent fan-out.

Description

GEO-SEO Analysis is an Agent Skill built around a bet: that a growing share of search traffic now arrives via AI answers rather than blue links, and that optimising for it is a different job from optimising for Google's index. GEO here means generative engine optimization — being cited by ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews.

The skill exposes about seventeen sub-commands behind a /geo prefix. /geo audit <url> is the full run: it fetches the homepage, classifies the business type, pulls up to fifty pages from the sitemap, then fans out to five subagents in parallel — AI visibility, platform-specific optimisation, technical SEO, content quality and E-E-A-T, and schema markup — before synthesising the findings.

The GEO-specific checks are the interesting part. Citability scoring evaluates whether content blocks are shaped the way answer engines like to quote — the skill targets roughly 134-167 words per block. /geo crawlers reads robots.txt for more than fourteen named AI crawlers, which is where a site quietly blocks itself out of AI answers. /geo llmstxt analyses or generates an llms.txt file. /geo brands scans for brand mentions across the platforms AI models tend to cite, including YouTube, Reddit, Wikipedia and LinkedIn — a proxy for the off-site authority that correlates with being named in an answer.

The rest is agency plumbing, and unusually candid about it: /geo report-pdf produces a client-ready PDF with charts and scores, /geo proposal drafts a proposal from audit data, /geo compare generates a month-over-month delta report, and /geo prospect is a lightweight CRM for moving prospects through a pipeline. If you sell SEO work, that is most of a deliverable pipeline; if you are auditing your own site, you can ignore it.

It needs only Claude Code's standard tools — Read, Grep, Glob, Bash, WebFetch and Write — with no API keys, and installs through a one-line shell script. MIT licensed. Note that the market-context figures the skill quotes are dated 2025 and cite mixed-quality sources; treat them as framing, not evidence.

Install

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