Agent skill · Code Review & Quality

seo-local

Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and industry-specific recommendations. Detects business type (brick-and-mortar, SAB, hybrid) and industry vertical (restaurant, healthcare, legal, home services, real estate, automotive). Use when user says "local SEO", "Google Business Profile", "GBP", "map pack", "local pack", "citations", "NAP consistency", "local rankings", "service area", "multi-location", or "local search".

Infrasity-Labsgithub.com/Infrasity-LabsGitHub ↗
claude-codeMIT
Install
npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill seo-local --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 17 KB
Bundled scripts: none
Path: .claude/skills/seo-local/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 97
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Local SEO Analysis (March 2026) ## Key Statistics | Metric | Value | Source | |--------|-------|--------| | GBP signals share of local pack weight | 32% | Whitespark 2026 | | Proximity share of ranking variance | 55.2% | Search Atlas ML study | | Review signals share (up from 16%) | ~20% | Whitespark 2026 | | Google searches seeking local info | 46% | Industry data | | Mobile "near me" searches leading to visit in 24h | 76% | Google confirmed | | ChatGPT/AI usage for local recommendations | 45% (up from 6%) | BrightLocal LCRS 2026 | | ChatGPT local conversion rate | 15.9% | Seer Interactive | | Google organic local conversion rate | 1.76% | Seer Interactive | | Local pack ads growth (Jan 2025 to Jan 2026) | 1% to 22% | Sterling Sky | --- ## Business Type Detection Detect from page signals before analysis. This determines which checks apply. ### Brick-and-Mortar - Physical street address visible in page content or footer - Google Maps embed with pin/directions - "Visit us at", "Located at", "Come see us" - Structured address in LocalBusiness schema ### Service Area Business (SAB) - No visible physical address - Service area mentions: "serving [city/region]", "service area includes

What's inside
Steps it walks through
  1. Key Statistics
  2. Business Type Detection
  3. Brick-and-Mortar
  4. Service Area Business (SAB)
  5. Hybrid
  6. Industry Vertical Detection
  7. Analysis Dimensions
  8. 1. GBP Signals (25%)
  9. 2. Reviews & Reputation (20%)
  10. 3. Local On-Page SEO (20%)
  11. 4. NAP Consistency & Citations (15%)
  12. 5. Local Schema Markup (10%)
  13. 6. Local Link & Authority Signals (10%)
  14. AI Search Impact on Local
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About this skill
What does the seo-local skill do?

Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and industry-specific recommendations. Detects business type (brick-and-mortar, SAB, hybrid) and industry vertical (restaurant, healthcare, legal, home services, real estate, automotive). Use when user says "local SEO", "Google Business Profile", "GBP", "map pack", "local pack", "citations", "NAP consistency", "local rankings", "service area", "multi-location", or "local search".

How do I install it?

Run `npx skills add Infrasity-Labs/dev-gtm-claude-skills --skill seo-local --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From Infrasity-Labs/dev-gtm-claude-skills, a repository with 97 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going