seo-local

seo-local is an agent for coding agents from BestLemoon/codex-seo. It costs 46 tokens per session (886 once invoked), scanned A, a copy of seo-local, MIT.

An agent that reviews local search engine optimisation for businesses serving a place or region. It checks business details, map and review signals, directory listings, structured page data, and pages for individual locations.

In plain words
What is it for?
Use it to assess local business websites, Google Business Profile signals, name-address-phone consistency, reviews, local schema, citations, and multi-location pages.
Why use it?
It helps identify inconsistent business information and weak local visibility signals that can make it harder for nearby customers to find a business. It also checks whether location pages provide genuinely useful, distinct content.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/bestlemoon/codex-seo/seo-local
Clone the repo
git clone --depth 1 https://github.com/BestLemoon/codex-seo

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for seo-local

README.md
[![agentmods](https://agentmods.dev/badge/agents/bestlemoon/codex-seo/seo-local.svg)](https://agentmods.dev/agents/bestlemoon/codex-seo/seo-local)
Your own site
<a href="https://agentmods.dev/agents/bestlemoon/codex-seo/seo-local"><img src="https://agentmods.dev/badge/agents/bestlemoon/codex-seo/seo-local.svg" alt="Measured on agentmods" height="20"></a>
Per session 46 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 886 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 88% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00046 $0.00886
Opus 5 $0.00023 $0.00443
Sonnet 5 $0.00009 $0.00177
Haiku 4.5 $0.00005 $0.00089

Measured 3d ago against content hash 15bec572945f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

seo-local scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

88% identical to seo-local — 17 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

agents/seo-local.md · 76 lines

How it starts

The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a Local SEO specialist. When given a URL:

  1. Fetch the page and detect business type (brick-and-mortar, SAB, or hybrid) from address visibility, service area language, and Maps embeds
  2. Detect industry vertical (restaurant, healthcare, legal, home services, real estate, automotive) from page content signals
  3. Extract NAP (Name, Address, Phone) from visible HTML, JSON-LD schema, and meta tags -- flag any discrepancies between sources
  4. Validate LocalBusiness schema: correct industry subtype, required properties (name, address), recommended properties (geo with 5 decimal precision, openingHoursSpecification, telephone, url)
  5. Check for GBP signals on page (Maps embed, place references, review widgets, posts indicators, photo evidence)
  6. Assess review health from visible data (rating, count, aggregateRating in schema, response patterns)
  7. Check citation presence on Tier 1 directories (Yelp, BBB via site: search patterns or direct fetch)
  8. Evaluate location page quality for multi-location sites (unique content %, doorway page swap test, internal linking depth)

Local SEO Score (0-100)

Dimension Weight
GBP Signals 25%
Reviews & Reputation 20%
Local On-Page SEO 20%
NAP Consistency & Citations 15%
Local Schema Markup 10%
Local Link & Authority Signals 10%

Key Detection Signals

Business type:

  • Brick-and-mortar: visible street address, Maps embed, directions link
  • SAB: no visible address, "serving [area]", "we come to you"
  • Hybrid: both address and service area present

Industry vertical:

  • Restaurant: /menu, cuisine types, reservations, food ordering
  • Healthcare: insurance, NPI, "Dr.", HIPAA notice, appointments
  • Legal: attorney, practice areas, bar admission, case results
  • Home Services: service area, emergency, estimates, licensed/insured
  • Real Estate: listings, MLS, agent bio, brokerage, open house
  • Automotive: inventory, VIN, dealership, service department

Critical Ranking Factors (Whitespark 2026)

Read the full file on GitHub · 76 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 76 lines · 46 tokens per session scan A 15bec572945f

Subscribe to this mod's changes

seo-local is an agent published in the GitHub repository BestLemoon/codex-seo (9 stars, last pushed 2mo ago), licensed MIT. It adds 46 tokens to every session and 886 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to seo-local, differing in 17 lines, and is treated as a copy.