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Wf seo geo audit

Skill multiplex-ai/muggle-ai-teams/skills/wf-seo-geo-audit

Combined SEO + GEO audit and optimization workflow. Runs traditional SEO audit and AI search optimization in parallel, then produces a unified action plan covering both Google rankings and AI citations. Use when user says "full SEO and GEO audit", "audit my site for SEO and AI", "SEO + AI visibility", "comprehensive site audit", "optimize for Google and AI", "audit for search and AI engines", or "complete search audit". Chains 15+ SEO and GEO skills.From its SKILL.md

Install
npx -y skills add multiplex-ai/muggle-ai-teams --skill wf-seo-geo-audit

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SKILL.md

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SEO + GEO Combined Audit Workflow

Run a comprehensive search audit covering traditional SEO and AI engine optimization.

Phase 1: Parallel Audits

Dispatch these two audits concurrently:

Track A — Traditional SEO Audit

Invoke seo-audit which orchestrates:

  • seo-technical — crawlability, indexability, security, Core Web Vitals
  • seo-content — E-E-A-T, readability, thin content
  • seo-schema — structured data detection and validation
  • seo-sitemap — XML sitemap analysis
  • seo-images — alt text, file sizes, formats, lazy loading
  • seo-page — deep dive on key pages
  • seo-hreflang — international SEO (if multi-language detected)

Track B — GEO Audit

Invoke geo-audit which orchestrates:

  • geo-citability — passage-level AI citation scoring
  • geo-crawlers — AI crawler access map (GPTBot, ClaudeBot, etc.)
  • geo-llmstxt — llms.txt analysis/generation
  • geo-brand-mentions — brand authority across AI training sources
  • geo-content — E-E-A-T for AI citability
  • geo-schema — structured data for AI discoverability
  • geo-technical — technical audit with GEO-specific checks
  • geo-platform-optimizer — per-platform optimization (ChatGPT, Perplexity, Gemini, etc.)

Output: Two parallel reports — SEO Health Score + GEO Score (both 0-100).


Phase 2: Gap Analysis (after both audits complete)

Step 2A — Cross-Reference Findings

Compare overlapping areas:

  • Schema: seo-schema vs geo-schema — unified recommendation
  • Content: seo-content vs geo-content — E-E-A-T alignment
  • Technical: seo-technical vs geo-technical — merge issues lists

Step 2B — AI SEO Deep Dive

Invoke ai-seo with findings from both tracks:

  • Three-pillar optimization (Structure, Authority, Presence)
  • Platform-specific recommendations

Step 2C — Site Architecture Review

Invoke site-architecture if structural issues found:

  • Internal linking optimization for both crawlers and AI
  • Topic cluster architecture

Phase 3: Action Plan

Step 3A — Content Strategy

Invoke content-strategy informed by both audits:

  • Topics that serve both Google rankings AND AI citations
  • Content gap priorities

Step 3B — Schema Implementation

Invoke schema-markup for:

  • Unified JSON-LD implementation covering both SEO rich results and AI discoverability

Step 3C — Programmatic SEO (if applicable)

Invoke programmatic-seo if scale opportunities identified:

  • Template pages, data sources, thin content safeguards

Phase 4: Reporting

Step 4A — Client Report

Invoke geo-report to generate combined report, then Invoke geo-report-pdf for PDF deliverable

Step 4B — Competitor Comparison Pages (if relevant)

Invoke competitor-alternatives or seo-competitor-pages for:

  • "vs" and "alternatives" pages targeting competitor keywords

Skill Chain Summary

Phase 1 (parallel): seo-audit ║ geo-audit
Phase 2 (sequential): cross-reference → ai-seo → site-architecture
Phase 3 (parallel): content-strategy + schema-markup + programmatic-seo
Phase 4: geo-report → geo-report-pdf

Rules

  • Phase 1 tracks MUST run in parallel for efficiency.
  • If user only wants SEO or only GEO, run just that track — but recommend the other.
  • De-duplicate overlapping recommendations between SEO and GEO.
  • Phase 4 reporting is optional — ask user if they need a client-facing deliverable.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most audit compliance skills give in 829 tokens

Counted across 960 of the 1,589 authors here whose files we hold, read 2026-09-06

  • Read product marketing context before asking questionsin 29 of 960, across 11 files
  • Rank findings by severityin 29 of 960, across 22 files
  • Generate audit reportin 22 of 960
  • Run the audit scriptin 20 of 960, across 19 files
  • Generate a prioritized action plan reportin 19 of 960, across 11 files
  • Ensure one H1 per pagein 15 of 960, across 5 files
  • Ensure sitemap exists and is accessiblein 14 of 960, across 4 files
  • Verify alt text on all imagesin 12 of 960, across 3 files
  • Determine the audit scope before startingin 12 of 960, across 4 files
  • Verify important pages allowed in robots.txtin 11 of 960, across 2 files
  • Detect business type from homepage signalsin 11 of 960, across 7 files
  • Delegate specialized tasks to subagentsin 11 of 960, across 7 files

Said here and by no other author read

  • Run traditional SEO and AI audits concurrently
  • Compare overlapping areas between audits
  • De-duplicate overlapping recommendations

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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