Key takeaways
- GEO-first approach — optimizes for AI search engines (ChatGPT, Perplexity, Gemini, Google AI Overviews) while maintaining traditional SEO foundations
- 8,075 stars and 1,310 forks as of June 2026, MIT license, Python. 15 slash commands and 5 parallel subagents for comprehensive audits
- Citability scoring engine analyzes content blocks for AI citation readiness — optimal passages are 134-167 words, self-contained, and fact-rich
- Monetization angle built in — paired with a Skool community teaching GEO agency services ($2K-$12K/month engagements)
FAQ
What is geo-seo-claude?
A Claude Code skill that audits and optimizes websites for AI-powered search engines. It scores content citability, analyzes AI crawler access, scans brand mentions, generates schema markup, and produces client-ready PDF reports.
How much does geo-seo-claude cost?
The tool is free and open source under MIT license. The creator monetizes through a paid Skool community that teaches how to sell GEO services to businesses.
Who competes with geo-seo-claude?
claude-seo (AgriciDaniel, 8,686 stars) is the closest competitor with broader SEO coverage. SEO Machine (TheCraigHewitt, 7,121 stars) focuses on content creation. Marketing Skills (coreyhaines31, 32,921 stars) covers the broader marketing stack.
What makes geo-seo-claude different?
It prioritizes GEO over SEO — most competitors bolt GEO onto traditional SEO tooling. geo-seo-claude treats AI search visibility as the primary objective with traditional SEO as the foundation layer.
Overview
geo-seo-claude is a Claude Code skill that takes a GEO-first approach to search optimization — treating AI-powered search engines as the primary target rather than an afterthought. Where most SEO tools bolt on AI search features, this one inverts the priority: optimize for ChatGPT, Perplexity, Gemini, and Google AI Overviews first, then ensure traditional SEO foundations are solid.
Key stats: 8,075 stars, 1,310 forks, MIT license, Python. Created February 2026. Last pushed May 27, 2026 — roughly two weeks of quiet as of June 11, 2026, after a steady run of merged community PRs.
| Attribute | Value |
|---|---|
| Stars | 8,075 (June 2026) |
| Forks | 1,310 |
| License | MIT |
| Language | Python |
| Created | February 2026 |
| Slash commands | 15 |
| Subagents | 5 (parallel) |
| Dependencies | Python 3.8+, Claude Code CLI |
| Category | SEO/GEO Agent Skills |
How It Works
Running /geo audit on a URL launches 5 parallel subagents that each handle a different dimension of the analysis:
- AI Visibility — citability scoring, AI crawler access, llms.txt analysis, brand mention scanning
- Platform Analysis — ChatGPT, Perplexity, Google AI Overview readiness
- Technical SEO — Core Web Vitals, SSR, security, mobile optimization
- Content Quality — E-E-A-T assessment, readability, content freshness
- Schema Markup — detection, validation, JSON-LD generation
Results synthesize into a composite GEO Score (0-100) weighted across six categories: AI Citability (25%), Brand Authority (20%), Content Quality (20%), Technical Foundations (15%), Structured Data (10%), and Platform Optimization (10%).
Citability Scoring
The standout feature is the citability scorer — a Python engine that analyzes content blocks for AI citation readiness. Research shows optimal AI-cited passages are 134-167 words, self-contained, and fact-rich. The tool scores each content block against these criteria and flags sections that need restructuring for higher AI citation probability.
AI Crawler Analysis
Checks robots.txt for 14+ AI crawlers (GPTBot, ClaudeBot, PerplexityBot, etc.) and provides specific allow/block recommendations. Brand mention scanning covers YouTube, Reddit, Wikipedia, LinkedIn, and 7+ other platforms — important because brand mentions correlate 3x more strongly with AI visibility than backlinks.
15 Slash Commands
The command surface grew from 12 to 15 between March and June 2026 — the three additions (/geo prospect, /geo proposal, /geo compare) all target agency workflows rather than audit depth.
| Command | Purpose |
|---|---|
/geo audit | Full GEO + SEO audit with parallel subagents |
/geo quick | 60-second GEO visibility snapshot |
/geo citability | Score content for AI citation readiness |
/geo crawlers | Check AI crawler access (robots.txt) |
/geo llmstxt | Analyze or generate llms.txt |
/geo brands | Scan brand mentions across AI-cited platforms |
/geo platforms | Platform-specific optimization |
/geo schema | Structured data analysis and generation |
/geo technical | Technical SEO audit |
/geo content | Content quality and E-E-A-T assessment |
/geo report | Generate client-ready markdown report |
/geo report-pdf | Professional PDF with charts and visualizations |
/geo prospect | CRM-style prospect pipeline management |
/geo proposal | Auto-generate client proposals |
/geo compare | Month-over-month progress tracking |
Business Model
The tool itself is free and open source. The creator monetizes through a paid Skool community ("AI Workshop") that teaches how to package GEO audits as agency services. The pitch: GEO agencies charge $2K-$12K/month, this tool does the audit, the community teaches how to sell it.
This is an increasingly common pattern in the Claude Code skills ecosystem — open-source the tool, monetize the education/community layer.
Competitive Position
geo-seo-claude sits in a rapidly growing category of SEO/GEO agent skills. Its main differentiator is the GEO-first philosophy — most competitors (claude-seo, Agentic-SEO-Skill, SEO Machine) treat traditional SEO as primary with GEO bolted on. geo-seo-claude inverts this, which aligns with the market shift: AI-referred traffic grew 527% year-over-year, and Gartner projects a 50% drop in traditional search traffic by 2028.
As of June 2026, the race with claude-seo is effectively a dead heat — claude-seo holds 8,686 stars to geo-seo-claude's 8,075, with both pushed within the last three weeks. SEO Machine sits at 7,121 stars but has not been pushed since April 10, 2026. All three are dwarfed by Marketing Skills (32,921 stars), which covers the broader marketing stack beyond SEO/GEO.
Strengths
- GEO-first positioning aligns with where traffic is going, not where it was
- Parallel subagent architecture makes audits fast and comprehensive
- Citability scorer is a unique, research-backed feature
- PDF report generation makes it agency-ready out of the box
- Community contributions accepted — merged external PRs through late May 2026 (white-label config, pandoc PDF export, agent HTTP checks)
Weaknesses
- Claude Code only — no Cursor, Codex, or multi-agent support
- Python dependency adds friction vs. pure SKILL.md approaches
- Monetization via Skool may raise questions about tool quality vs. lead gen
- No MCP integration — competitors like claude-seo integrate with DataForSEO
- Young project — ~4 months old as of June 2026, and the commit stream has been quiet since May 27, 2026
What Developers Say
No verbatim, attributable developer testimonials for geo-seo-claude surfaced in public channels (Hacker News, Reddit, X) as of June 11, 2026. The repo's 8,075 stars, 1,310 forks, and merged community PRs are the strongest available adoption signals, but no named practitioner reviews exist to quote. This section will be updated if credible firsthand accounts appear.
Bottom Line
Recommended — for teams already using Claude Code who want to optimize for AI search visibility, it remains the most focused GEO-first tool in the category. geo-seo-claude is well-architected and bets correctly on the GEO-first thesis; the citability scoring engine and parallel subagent design are genuinely differentiated. The Skool monetization layer is smart business but may make some developers skeptical.
Outlook: stars more than doubled between March and June 2026 (3,320 → 8,075), and the May additions (/geo prospect, /geo proposal, /geo compare) show the roadmap tilting toward agency tooling. The two-week commit pause since May 27 is worth watching but not yet a stall — claude-seo's near-identical star count means the category lead is genuinely contested.