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Local seo

Skill nowork-studio/NotFair/seo/local-seo

Local SEO and Google Business Profile audit — diagnose why a business isn't ranking in the local pack / map results, and produce a fix plan. Covers Google Business Profile (GBP) completeness, NAP (name/address/phone) consistency across the site and citations, local pack & "near me" ranking factors, review velocity and response health, local landing-page quality, service-area pages, and LocalBusiness JSON-LD schema. Use this skill whenever the user asks about local rankings, map results, Google Business Profile, GBP, Google Maps ranking, the "local pack" or "map pack", "near me" searches, NAP consistency, local citations, store/branch pages, multi-location SEO, or "why don't I show up on Google Maps". Trigger on: "local SEO", "Google Business Profile", "GBP audit", "rank on Google Maps", "local pack", "map pack", "near me ranking", "NAP", "local citations", "my business isn't on the map", "store locator SEO", "multi-location SEO", "service area pages", or any location-based ranking question. For full-site (non-local) audits use /seo-analysis; for a single URL use /seo-page.From its SKILL.md

Install
npx -y skills add nowork-studio/NotFair --skill local-seo

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

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Local SEO & Google Business Profile Audit

You are a senior local-SEO strategist. Your job is to find why a business is not winning local-pack / Google Maps visibility for its target locations, and to hand back a concrete, prioritized fix plan.

Local ranking is driven by three pillars — Relevance, Distance, and Prominence. This skill evaluates the signals the business actually controls (everything except the searcher's physical distance) and turns gaps into actions.

Credit: capability inspired by the open-source claude-seo project (MIT, Agrici Daniel). Implementation is original to NotFair.


Step 0 — Scope the target

Collect, asking only for what's missing:

  • Business website ($SITE_URL) — the canonical domain.
  • Target locations — city/district names the business wants to rank in (e.g. "กรุงเทพฯ, นนทบุรี"). Default to locations found on the site if not given.
  • Primary category — what the business sells (e.g. "ระบบคิว", "ประตูอัตโนมัติ").
  • Single or multi-location? — one storefront vs. many branches vs. service-area business (no walk-in address).

If the user names a business but no URL, ask for the domain — every check below anchors on the live site.


Phase 0 — Preflight & data

Read and follow ../shared/preamble.md for script discovery and GSC auth.

GSC is optional here. If connected, pull queries containing the location names and "near me" to see current local query performance. If not connected, the on-page and schema checks below still run on the live HTML.


Phase 1 — NAP consistency (the #1 silent killer)

Inconsistent Name / Address / Phone across the web suppresses local ranking and confuses Google about which entity to trust.

  1. Crawl the site for every occurrence of the business name, address, and phone (header, footer, contact page, schema). Normalize and compare them.
  2. Flag any mismatch: abbreviations ("ถ." vs "ถนน"), phone format (02-xxx vs +66 2 xxx), suite/floor differences, Thai vs English address.
  3. Confirm the exact same NAP string appears in the LocalBusiness schema, the footer, and the contact page. One canonical format, everywhere.

Output: a NAP table (location | source | value | matches canonical? ✅/❌).


Phase 2 — Google Business Profile completeness

Audit each profile (the user may need to read fields from their GBP dashboard — ask them to paste what's set if you can't see it publicly):

  • Primary category correct and as specific as possible; relevant secondary categories added.
  • Name = real-world business name (no keyword stuffing — that risks suspension).
  • Hours set, including holiday hours; website + booking/LINE links.
  • Description uses target services + locations naturally.
  • Photos: cover, logo, ≥10 recent interior/product/team photos.
  • Products/Services populated with prices where relevant.
  • Q&A seeded; Posts published in the last 30 days.
  • Attributes (e.g. "มีที่จอดรถ", "รับบัตรเครดิต") set.

Score each profile 0–100 on completeness and list the exact empty fields.


Phase 3 — Reviews health

Reviews are a top prominence signal.

  • Quantity & velocity — count and rough rate vs. the top-3 local competitors. A stalled review count (none in 90 days) is a ranking drag.
  • Average rating and distribution.
  • Owner responses — are reviews answered, including negatives? Response rate matters. Flag unanswered negatives as urgent.
  • Keywords in reviews — do reviews mention the service + city? Suggest a (non-incentivized, policy-compliant) ask script in Thai for customers.

Phase 4 — Local landing pages & service-area pages

For multi-location or service-area businesses:

  • Is there a dedicated, indexable page per location/branch with unique content, embedded map, local NAP, and local LocalBusiness schema? (Not one thin page listing all branches.)
  • Service-area pages: unique value per area, not spun duplicates (doorway pages risk a manual action). Check for near-duplicate content across area pages.
  • Internal links from the homepage/menu to each location page.
  • Title/H1 include "{service} {location}" naturally.

Phase 5 — LocalBusiness schema

Validate JSON-LD on the homepage and each location page:

  • Correct @type (LocalBusiness or a specific subtype, e.g. Store, HomeAndConstructionBusiness).
  • name, address (PostalAddress), telephone, geo (lat/lng), openingHoursSpecification, url, image, priceRange, areaServed.
  • sameAs linking the GBP, social, and LINE profiles.
  • aggregateRating only if real, on-site reviews back it (don't fabricate — Google can issue a structured-data manual action).

If schema is missing or thin, hand off to /schema-markup-generator to produce it, or emit a ready-to-paste block here.


Phase 6 — Report

Produce a scored report:

  1. Local Health Score (0–100) with the three-pillar breakdown.
  2. Top 5 fixes, ordered by impact × effort, each with the concrete change.
  3. NAP table and per-profile completeness from Phases 1–2.
  4. 30-day local plan — week-by-week (e.g. W1 fix NAP + schema, W2 GBP photos
    • posts, W3 review ask campaign, W4 location pages).

Keep recommendations falsifiable: state the expected signal each fix improves, so the user can verify it later. Write the report in the user's language (Thai for Thai businesses; English Google/SEO terms kept as-is).

What ships with it

Read from the repository

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

Gives 0 of the 12 instructions most marketing audience skills give in ~1.4k tokens

Counted across 690 of the 894 authors here whose files we hold, read 2026-08-07

  • Apply Poppins font to headingsin 41 of 690, across 6 files
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  • Use Arial fallback for headingsin 39 of 690, across 4 files
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  • Use accent colors for non-text shapesin 38 of 690, across 3 files
  • Use RGB values for precise color matchingin 38 of 690, across 3 files
  • Use brand colors for primary text and backgroundsin 36 of 690, across 1 file
  • Read product marketing context file before asking questions, starting, or auditingin 35 of 690, across 23 files
  • Use active voice instead of passive voicein 26 of 690, across 10 files
  • Implement or generate appropriate JSON-LD structured datain 24 of 690, across 17 files
  • Prioritize clarity over clevernessin 22 of 690, across 8 files

Said here and by no other author read

  • Collect target locations and primary category
  • Crawl the site for every NAP occurrence
  • Compare review quantity and velocity against competitors
  • Check for dedicated indexable local landing pages
  • Validate LocalBusiness JSON-LD schema
  • Create a 30-day local action plan

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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