GEO Audit Multi-Skill Runner
Run /geo-audit on any URL and Claude Code spins up parallel sub-agents to score how well the site shows up in ChatGPT, Perplexity, Gemini, and Bing.
Before & after
Same prompt, same agent — the only difference is the skill.
That's a good question. Your website visibility in AI search depends on things like structured data, whether your content is cited by AI models, how Perplexity and ChatGPT index you. It's a relatively new area, so there aren't a lot of established benchmarks yet. I'd suggest checking if your site appears in ChatGPT web search results, making sure you have proper metadata and schema markup, and looking at your traffic sources. It's hard to measure precisely right now, but there are some signals to look at.
GEO AUDIT REPORT - AI Search Visibility SITE AUDITED: calendly.com DATE: 2026-07-31 EXECUTIVE SUMMARY: Overall citability score: 72/100. Strong on Wikipedia and structured data; weak on Perplexity discoverability. Estimated monthly AI search traffic potential: 1.2K-1.8K visits (currently unmeasured). PLATFORM-BY-PLATFORM SCORES: CHATGPT (85/100) ✓ Appears in web search results ✓ Cited in knowledge synthesis tasks ✗ No Wikipedia article (missed citability boost) ✓ Clear entity extraction via schema.org PERPLEXITY (68/100) ✓ Content indexed ✗ Low frequency of citations vs. competitors (Zoom, HubSpot) ✗ Missing rich snippets for key comparison queries GEMINI (79/100) ✓ Schema markup detected ✓ Knowledge panel eligible ✗ Competitor reviews rank higher for "scheduling tools" BING (82/100) ✓ Sitelinks appearing ✓ Knowledge card presence ✗ Enterprise content gap (no "security for enterprise" guide) KEY FINDINGS: 1. Wikipedia gap: No Wikipedia article. This is costing 12-15 points across all platforms. (Estimated blocker: 400+ monthly AI citations) 2. Structured data: Schema exists but missing BreadcrumbList. Add it. 3. Content gaps: Blog has zero posts on "scheduling compliance" or "analytics for distributed teams." Competitors rank here in AI search. WEEKLY ACTION PLAN (Priority Order): Week 1: Add schema.org BreadcrumbList to all product pages (1 day). Audit competitor content gaps; draft one blog post on "Scheduling Security Compliance" (2 days). Week 2: Submit Wikipedia article candidate (requires external Wikipedia expert; 3-4 days). Week 3-4: Build enterprise feature deep-dive guides for AI search indexing. Expected impact after 90 days: +180-240 monthly AI search visits.
About this skill
name: geo-audit-multi-skill-runner description: Run /geo-audit on any URL and Claude Code spins up parallel sub-agents to score how well the site shows up in ChatGPT, Perplexity, Gemini, and Bing.
GEO Audit Multi-Skill Runner
What This Does
The creator ships a 12-skill GEO folder with a top-level geo-audit skill that runs discovery on the homepage, then delegates to five sub-agents doing citability, structured data, competitive gap, and platform-specific checks in parallel. The final HTML report includes scores per AI platform, key findings, and a weekly prioritized action plan.
What You Get
- 12-skill GEO folder installable via GitHub
- five parallel sub-agents for scoring
- per-platform score for ChatGPT, Perplexity, Gemini, Bing
- executive summary and key findings
- weekly prioritized action plan
Customize
- target_url: site to audit
- platforms: which AI engines to score against
- competitor_urls: optional comparison sites
- sub_skill_toggle: enable or disable citability, structured data, etc
- report_output: HTML, MD, or PDF
Sample Output
Audit of calendly.com flags no Wikipedia article as a critical finding and returns per-platform scores plus a weekly action plan.
Target Audience
SEO and content agencies pitching AI-search optimization
SKILL.md preview
---
name: geo-audit-multi-skill-runner
description: Use this skill to run a multi-agent GEO audit on a URL, scoring how well the site shows up in ChatGPT, Perplexity, Gemini, and Bing.
version: 1.0.0
category: Marketing
author: AgentVolt
license: proprietary
tags:
- marketing
- standard
---
# GEO Audit Multi-Skill Runner
Runs a generative-engine-optimization audit on a URL by delegating discovery, citability, structured data, and competitive checks to parallel sub-agents, then compiles a scored report.
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