Agent skill

SEO Local

by AgriciDaniel in AgriciDaniel/codex-seo

Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and…

MITAuto-check passedMarketing & SEO

Install SEO Local

skills CLI
$ npx skills add AgriciDaniel/codex-seo --skill seo-local -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install AgriciDaniel/codex-seo seo-local --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/AgriciDaniel/codex-seo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/seo-local .claude/skills/seo-local && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-local
GitHub stars
799
Used in
2 other repos
Token cost
~4.5k tokens
SKILL.md length
2,202 words
Files
2
Skills in repo
18
Repo updated
First seen
Licence
MIT

At a glance

Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and…

  • Works in 6 steps: GBP Signals (25%) → Reviews & Reputation (20%) → Local On-Page SEO (20%) → …
  • User says local SEO
  • SKILL.md covers Shared Data Cache, Key Statistics, Business Type Detection and Industry Vertical Detection, plus 11 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

SEO Local is an agent skill from AgriciDaniel/codex-seo. 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…

Its SKILL.md is about 4.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.

It sits in Marketing & SEO, covering Local SEO. The repository describes itself as: Codex-first SEO skill suite. 26 workflows, 24 TOML agents, DataForSEO/Gemini/Google/Firecrawl integrations, GEO/AEO, CWV, schema, backlinks, local/maps, and deterministic reports. The licence is MIT.

When your agent uses it

  • User says local SEO
  • Google Business Profile
  • NAP consistency

Example prompts

  • “local SEO”
  • “Google Business Profile”
  • “map pack”
  • “/seo-local”

Workflow steps

6 steps, taken from the step headings in SKILL.md.

  1. GBP Signals (25%)
  2. Reviews & Reputation (20%)
  3. Local On-Page SEO (20%)
  4. NAP Consistency & Citations (15%)
  5. Local Schema Markup (10%)
  6. Local Link & Authority Signals (10%)

What it can do on your machine

Read from SKILL.md and the folder at commit 9a644f6. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO Local loads about 4.5k tokens when it runs. Until then it costs about 143 tokens; SKILL.md has 2,202 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~143
When it runs · the whole SKILL.md, loaded when a task matches
~4.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AgriciDaniel/codex-seo at commit 9a644f6, republished under its MIT licence (© AgriciDaniel). 2,202 words, ~4,541 tokens.

Download SKILL.mdSave it as .claude/skills/seo-local/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
seo-local
description
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".
user-invokable
true
argument-hint
[url]
license
MIT
metadata.author
AgriciDaniel
metadata.version
1.9.6
metadata.category
seo

Local SEO Analysis (March 2026)

Shared Data Cache

Step 0 -- Check shared data cache:

Before gathering, check .seo-cache/ for reusable context from related SEO skills. Reference: ../seo/references/shared-data-cache.md for schemas and dependency map.

Check these cache files when present:

  • .seo-cache/site-meta.json for domain, business type, industry, and crawl context

  • .seo-cache/audit-scores.json for prior full-audit priorities

  • .seo-cache/pages/{url-slug}/page-analysis.json for page-level context when a URL is provided

  • If found: parse and use clearly valid fields (note "Using cached [X] from [date]")

  • If missing, corrupt, or irrelevant: continue with fresh evidence

  • If the user says "refresh" or "re-run": ignore cache reads and overwrite on write

Key Statistics

MetricValueSource
GBP signals share of local pack weight32%Whitespark 2026
Proximity share of ranking variance55.2%Search Atlas ML study
Review signals share (up from 16%)~20%Whitespark 2026
Google searches seeking local info46%Industry data
Mobile "near me" searches leading to visit in 24h76%Google confirmed
ChatGPT/AI usage for local recommendations45% (up from 6%)BrightLocal LCRS 2026
ChatGPT local conversion rate15.9%Seer Interactive
Google organic local conversion rate1.76%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"
  • "We come to you", "On-site service", "Mobile [service]"
  • areaServed in schema without address.streetAddress
Hybrid
  • Both physical address AND service area language present
  • "Visit our showroom" combined with "We also serve [areas]"

Impact on checks: SABs skip embedded map verification and physical address consistency. Brick-and-mortar gets full NAP + map checks.


Industry Vertical Detection

Detect from page signals and GBP category patterns. Routes to industry-specific checks from references/local-schema-types.md.

VerticalDetection Signals
Restaurant/menu, menu items, reservations, cuisine types, food ordering, "dine-in", "takeout"
Healthcareinsurance accepted, patients, appointments, NPI, medical terms, "Dr.", HIPAA notice
Legalattorney, lawyer, practice areas, bar admission, case results, "free consultation"
Home Servicesservice area, emergency service, "free estimate", licensed/insured/bonded, "24/7"
Real Estatelistings, MLS, properties for sale/rent, agent bio, brokerage, "open house"
Automotiveinventory, VIN, test drive, dealership, service department, "new/used/certified"

If no vertical detected, use generic LocalBusiness analysis path.


Analysis Dimensions

1. GBP Signals (25%)

Primary category is the single most important local pack factor (Whitespark #1, score: 193). Incorrect primary category is the #1 negative factor (score: 176).

Check for:

  • GBP embed or reference detectable on page (Maps iframe, place ID, reviews widget)
  • Primary category appropriateness (infer from page content vs visible GBP data)
  • Evidence of secondary categories (optimal: 4 additional per BrightLocal)
  • GBP posts presence (no direct ranking impact per WebFX, but triggers Post Justifications)
  • Photos/video evidence (45% more direction requests with photos, Agency Jet)
  • Q&A content (deprecated Dec 2025, replaced by Ask Maps Gemini AI -- recommend recreating Q&A content as FAQ sections on website; GBP removed existing Q&A with no export available)
  • Google Verified badge eligibility (replaced Guaranteed/Screened in Oct 2025)
  • GBP link URL strategy: do NOT link to strongest website page (Sterling Sky Diversity Update -- risks suppressing organic rankings)
  • Business hours visibility on page (businesses open at search time rank higher, factor #5)

Scoring guide:

  • Full: GBP embed present, category signals align, posts active, photos present
  • Partial: Some GBP signals present but incomplete
  • Low: No visible GBP integration on website
2. Reviews & Reputation (20%)

Review velocity matters more than total count. The 18-day rule (Sterling Sky): rankings cliff if no new reviews for 3 weeks.

Check for:

  • Total Google review count visible on page or schema (magic threshold: 10, Sterling Sky)
  • Star rating (31% of consumers only use 4.5+, 68% only use 4+, BrightLocal 2026)
  • Review recency indicators (74% only care about reviews in last 3 months)
  • aggregateRating in schema (ratingValue, reviewCount, bestRating)
  • Third-party review presence (consumers use average of 6 review sites, BrightLocal 2026)
  • Owner response patterns (88% would use business that responds, BrightLocal)
  • Review gating detection: any pre-screening of satisfaction before directing to review platform is prohibited by Google (fake engagement policy) and FTC ($53,088/violation)

Industry-specific:

  • Healthcare: HIPAA prohibits confirming/denying reviewer is a patient in responses
  • Legal: attorney-client privilege considerations in review responses

Scoring guide:

  • Full: 10+ reviews, 4.5+ stars, recent activity, owner responses, multi-platform presence
  • Partial: Some reviews but gaps in recency, rating, or response rate
  • Low: <10 reviews, no recent activity, no responses, single platform only
3. Local On-Page SEO (20%)

Dedicated service pages = #1 local organic factor AND #2 AI visibility factor (Whitespark 2026).

Check for:

  • Title tag contains city/service keywords
  • H1 tag with local intent (city + service)
  • NAP (Name, Address, Phone) visible in page HTML (footer, contact section, header)
  • Dedicated service pages (one page per core service)
  • Location page quality for multi-location sites:
    • >60-70% unique content minimum (industry consensus, no Google-confirmed threshold)
    • Swap test: if you can swap the city name and content still makes sense, it's a doorway page (RicketyRoo method). HVAC company lost 80% rankings + 63% traffic after March 2024 Core Update for this pattern
    • Local photos, area-specific testimonials, local FAQs
  • Embedded Google Map (geographic signal reinforcement, not direct ranking factor -- lazy-load to mitigate speed impact)
  • Click-to-call button (tel: link) and contact form above the fold
  • Internal linking architecture: hub-and-spoke, every critical page within 3 clicks of homepage
  • 2-5 contextual internal links per 1,000 words with descriptive anchor text

Multi-location specific:

  • Store locator with individual crawlable URLs (SSR/SSG preferred over CSR)
  • Subdirectory structure: domain.com/locations/city-name/ (subdirectories consolidate link equity better, Bruce Clay: 50%+ traffic lift)
  • Each location page has unique LocalBusiness schema with @id

Scoring guide:

  • Full: City in title + H1, NAP visible, dedicated service pages, no doorway patterns, good internal linking
  • Partial: Some local signals but missing service pages or doorway page risk
  • Low: Generic title/H1, NAP not visible, thin location pages
4. NAP Consistency & Citations (15%)

Citations declining for traditional pack rankings but 3 of top 5 AI visibility factors are citation-related (Whitespark 2026). Google's July 2025 documentation update removed "directories" from prominence definition.

Check for:

  • NAP extraction: compare Name, Address, Phone from:
    1. Visible page HTML (footer, contact page)
    2. LocalBusiness JSON-LD schema
    3. Any visible GBP data
    • Flag any discrepancies between these three sources
  • Citation presence on Tier 1 directories (check via WebFetch or site: search patterns):
    • Google Business Profile signals on page
    • Yelp: site:yelp.com "Business Name"
    • BBB: site:bbb.org "Business Name"
    • Facebook business page references
  • Apple Business Connect awareness (usage doubled to 27%, BrightLocal 2026 -- recommend claiming)
  • Bing Places awareness (powers ChatGPT, Copilot, Alexa -- recommend claiming and optimizing)
  • Industry-specific directory recommendations: load references/local-schema-types.md for per-vertical citation sources
  • Data aggregator awareness: Data Axle, Foursquare, Neustar/TransUnion (recommend submission for downstream distribution)

Scoring guide:

  • Full: Consistent NAP across page/schema, Tier 1 citations detected, industry directories present
  • Partial: NAP present but inconsistencies, some citations missing
  • Low: NAP discrepancies, no detectable citations, no schema address
5. Local Schema Markup (10%)

Schema is NOT a direct ranking factor (John Mueller confirmed). But enables rich results (43% CTR increase, Webstix case study) and helps AI systems parse business information.

Check for:

  • LocalBusiness schema presence (extract JSON-LD blocks)
  • Required properties: name, address with PostalAddress sub-properties
  • Recommended properties: geo (minimum 5 decimal places, Confirmed), openingHoursSpecification, telephone, url, priceRange (<100 chars), image, aggregateRating
  • Correct subtype for industry -- load references/local-schema-types.md:
    • Restaurant using Restaurant not generic LocalBusiness
    • Legal using LegalService not deprecated Attorney
    • Auto dealer using AutoDealer not deprecated VehicleListing
    • Healthcare using MedicalClinic/Hospital/Dentist not generic MedicalBusiness
  • SAB-specific: areaServed with named cities (recommended, not in Google's official list but Schema.org supported)
  • Multi-location: each location page has own LocalBusiness with unique @id, linked via branchOf to Organization on homepage
  • Industry-specific schema patterns (per references/local-schema-types.md):
    • Restaurant: Menu + MenuSection + MenuItem + ReserveAction
    • Healthcare: Physician (Person) + MedicalSpecialty + sameAs to NPI
    • Legal: LegalService + Person + Service (practice areas)
    • Home Services: Subtype + areaServed + Service
    • Real Estate: RealEstateAgent + Person + RealEstateListing
    • Automotive: AutoDealer + Car + Offer (separate dept schemas)

Scoring guide:

  • Full: Correct subtype, all recommended properties, industry-specific patterns, valid JSON-LD
  • Partial: LocalBusiness present but generic type or missing recommended properties
  • Low: No local schema, or schema with errors/placeholder content
Show full SKILL.md (857 more words)Show less

Links declining for local pack but remain ~26% of local organic ranking (Whitespark 2026, #2 factor group). "Best of" list placements = #1 AI visibility citation factor.

Check for:

  • Local backlink indicators detectable from page:
    • Chamber of Commerce mentions or links (high Trust Flow, ~80% more consumer visits, GlueUp)
    • BBB accreditation/badge (Google uses BBB for business verification)
    • Local news/press mentions
    • Community involvement signals (sponsorships, local events, partnerships)
  • "Best of" list presence (top AI visibility factor per Whitespark 2026)
  • Digital PR signals: 66.2% of PR practitioners now track AI citations as KPI (BuzzStream 2026)
  • Brand mentions correlate 3x more strongly with AI visibility than traditional backlinks (Ahrefs: 0.664 vs 0.218 correlation)
  • Link velocity benchmark: 5-10 quality local links/month for small businesses (consensus)

Scoring guide:

  • Full: Local authority signals visible (chamber, BBB, press), community involvement evident
  • Partial: Some authority signals but limited local link indicators
  • Low: No detectable local authority signals

AI Search Impact on Local

Do not duplicate seo-geo analysis. Provide local-specific AI context and recommend /seo geo <url> for full analysis.

Key local AI facts:

  • AI Overviews appear on up to 68% of local searches (Whitespark Q2 2025)
  • ChatGPT converts at 15.9% vs Google organic at 1.76% (Seer Interactive)
  • 3 of top 5 AI visibility factors are citation-related (Whitespark 2026)
  • ChatGPT does NOT access GBP directly -- sources from Bing index, Yelp, TripAdvisor, BBB, Reddit
  • Bing Places is critical: powers ChatGPT, Copilot, Alexa
  • AI-powered local packs (mobile US) show only 1-2 businesses, 32% fewer shown (Sterling Sky)

Recommendation: Run /seo geo <url> for comprehensive AI search visibility analysis including citability scoring, llms.txt check, and brand mention audit.


Reference Files

Load on-demand as needed:

  • references/local-seo-signals.md: Ranking factors, review benchmarks, citation tiers, GBP feature status, algorithm updates
  • references/local-schema-types.md: LocalBusiness subtypes by industry, schema patterns, citation sources per vertical

Output

Generate LOCAL-SEO-ANALYSIS-{domain}.md with:

  1. Local SEO Score: XX/100 with dimension breakdown table
  2. Business type: Brick-and-mortar / SAB / Hybrid
  3. Industry vertical detected + industry-specific findings
  4. GBP optimization checklist (detected signals vs missing)
  5. Review health snapshot (rating, count, velocity indicators, response patterns)
  6. NAP consistency audit (page vs schema discrepancies, cross-source comparison)
  7. Citation presence check (Tier 1 directory status)
  8. Local schema status (present/missing/malformed + ready-to-use fix)
  9. Location page quality (if multi-location: unique content %, doorway risk, store locator)
  10. Top 10 prioritized actions (Critical > High > Medium > Low)
  11. Limitations disclaimer: What this analysis could NOT assess (geo-grid ranking, Domain Authority, comprehensive backlinks, GBP Insights data, real-time local pack position) and which paid tools can fill those gaps

Quick Wins

  1. Claim and optimize Apple Business Connect (usage doubled to 27%)
  2. Claim and optimize Bing Places (powers ChatGPT, Copilot, Alexa)
  3. Fix any NAP discrepancies between page, schema, and GBP
  4. Add LocalBusiness schema with correct industry subtype
  5. Add geo coordinates with 5+ decimal precision
  6. Ensure phone number uses tel: link for click-to-call
  7. Add city + service keyword to title tag and H1

Medium Effort

  1. Create dedicated page for each core service (Whitespark: #1 local organic factor)
  2. Build review generation strategy maintaining 18-day minimum cadence
  3. Submit to three data aggregators (Data Axle, Foursquare, Neustar/TransUnion) for downstream distribution
  4. Claim industry-specific directory listings (per vertical recommendations)
  5. Add industry-specific schema patterns (Menu for restaurants, Physician for healthcare, etc.)
  6. Implement hub-and-spoke internal linking for service/location pages

High Impact

  1. Build local digital PR strategy targeting "best of" lists (#1 AI visibility factor)
  2. Develop unique, non-swappable content for each location page (>60% unique)
  3. Establish presence on platforms ChatGPT sources from (Yelp, TripAdvisor, BBB, Reddit)
  4. Pursue Chamber of Commerce and BBB membership (authority + verification signals)
  5. Create community involvement content (sponsorships, local events, partnerships)

DataForSEO Integration (Optional)

If DataForSEO MCP tools are available, use local_business_data for live GBP data extraction, google_local_pack_serp for real-time local pack positions, and business_listings for automated citation auditing across directories.


Error Handling

ScenarioAction
URL unreachable (DNS failure, connection refused)Report the error clearly. Do not guess site content. Suggest the user verify the URL and try again.
No local signals detected on pageReport that no local business indicators were found. Suggest the user confirm this is a local business and provide the GBP listing URL if available.
NAP not found in page HTMLCheck schema and meta tags. If still absent, flag as Critical issue. Recommend adding visible NAP to footer and contact page.
Industry vertical unclearPresent the top two detected verticals with supporting signals. Ask the user to confirm before applying industry-specific recommendations.
Multi-location with 50+ location pagesApply the quality gates from seo orchestrator: WARNING at 30+ pages (enforce 60%+ unique), HARD STOP at 50+ pages (require user justification before continuing).

FLOW Framework Integration

For prompt-guided local optimization, use /seo flow local <url> — FLOW's 11 local-stage prompts cover GBP optimization, meta descriptions, title tags, and structured local audit workflows.

Write to shared data cache

After completing all work, write a concise JSON summary to .seo-cache/ when the workflow produced durable findings. Use the schemas and naming rules in ../seo/references/shared-data-cache.md; include at least cache_type, analyzed_at, source URL/domain, key findings, issues, recommendations, and tool limitations. Add .seo-cache/ to .gitignore if it is missing.

© AgriciDaniel, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/seo-local of AgriciDaniel/codex-seo.

  • SKILL.md
  • LICENSE.txt

Open the folder on GitHubat commit 9a644f6

Used in 3 other repositories

We found 5 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in AgriciDaniel/codex-seo, which our catalogue first saw on October 7, 2026.

Compare with similar skills

SEO Local next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

SEO Local compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
SEO Local this skillAgriciDaniel/codex-seo7992 repos~4.5kAutomated safety check: PassMIT
FLOW SEO FrameworkAgriciDaniel/claude-seo19k2 repos~1.4kAutomated safety check: PassMIT
Google Mapscablate/mcp-google-map469—~909Automated safety check: PassMIT
Google Maps Local SEOcablate/mcp-google-map469—~633Automated safety check: PassMIT
Google Maps Travel Planningcablate/mcp-google-map469—~710Automated safety check: PassMIT
Universal SEO AnalysisAgriciDaniel/claude-seo19k—~4.9kAutomated safety check: PassMIT

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Categories

Questions about SEO Local

What does SEO Local 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…. SEO Local is an agent skill from AgriciDaniel/codex-seo. 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.

When should I use SEO Local?

SEO Local fits situations like: user says local SEO; google Business Profile; NAP consistency.

How do I install SEO Local in Claude Code?

Run `npx skills add AgriciDaniel/codex-seo --skill seo-local -a claude-code`. Or copy the skill folder (skills/seo-local in AgriciDaniel/codex-seo) into .claude/skills/seo-local in your project. Claude Code loads it when a task matches its description.

How do I install SEO Local in Codex?

Run `npx skills add AgriciDaniel/codex-seo --skill seo-local -a codex`. Or copy the skill folder (skills/seo-local in AgriciDaniel/codex-seo) into .agents/skills/seo-local in your project. Codex loads it when a task matches its description.

Can I use SEO Local in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AgriciDaniel/codex-seo --skill seo-local -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-local, .gemini/skills/seo-local, .github/skills/seo-local and .opencode/skills/seo-local in your project.

What does SEO Local need to run?

SKILL.md names no scripts, command-line tools or credentials: SEO Local is instructions for the agent only.

Does SEO Local access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is SEO Local safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO Local use?

SEO Local is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO Local use?

About 4.5k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to SEO Local?

Skills that share tags, products or a category with SEO Local: FLOW SEO Framework (AgriciDaniel/claude-seo, 19k stars), Google Maps (cablate/mcp-google-map, 469 stars), Google Maps Local SEO (cablate/mcp-google-map, 469 stars) and Google Maps Travel Planning (cablate/mcp-google-map, 469 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO Local?

AgriciDaniel (a GitHub user) maintains it in AgriciDaniel/codex-seo, which has 799 GitHub stars. The repository holds 18 skills in this directory. The repository was last updated on September 11, 2026.

Source: AgriciDaniel/codex-seo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.