geo-platform-optimizer

geo-platform-optimizer is a skill for Claude Code, Codex from bytefer/geo-seo-codex. It costs 34 tokens per session (4,455 once invoked), scanned A, a copy of geo-platform-optimizer, MIT.

A review guide for improving how a website appears in answers from AI search services such as Google AI Overviews, ChatGPT, Perplexity, Gemini, and Bing Copilot.

In plain words
What is it for?
Use it to check a website separately for each listed service and produce scores, gaps, and recommended actions.
Why use it?
Different AI search services may use different sources and ranking methods, so one service may find or cite a page that another misses.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

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 skills/bytefer/geo-seo-codex/geo-platform-optimizer
Any agent
npx skills add bytefer/geo-seo-codex --skill geo-platform-optimizer
Clone the repo
git clone --depth 1 https://github.com/bytefer/geo-seo-codex

Made for: Claude Code, Codex.

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 geo-platform-optimizer

README.md
[![agentmods](https://agentmods.dev/badge/skills/bytefer/geo-seo-codex/geo-platform-optimizer.svg)](https://agentmods.dev/skills/bytefer/geo-seo-codex/geo-platform-optimizer)
Your own site
<a href="https://agentmods.dev/skills/bytefer/geo-seo-codex/geo-platform-optimizer"><img src="https://agentmods.dev/badge/skills/bytefer/geo-seo-codex/geo-platform-optimizer.svg" alt="Measured on agentmods" height="20"></a>
Per session 34 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,455 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% 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 5.1 $0.00034 $0.04455
Opus 5 $0.00017 $0.02227
Sonnet 5 $0.00007 $0.00891
Haiku 4.5 $0.00003 $0.00445

Measured 6d ago against content hash 766750180009, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

geo-platform-optimizer 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 6d 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

100% identical to geo-platform-optimizer — 6 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.

skills/geo-platform-optimizer/SKILL.md · 272 lines

How it starts

The opening of the file, as written. The whole thing — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GEO Platform Optimizer

Core Insight

Only 11% of domains are cited by BOTH ChatGPT and Google AI Overviews for the same query. Each AI search platform uses different indexes, ranking logic, and source preferences. A page optimized for Google AI Overviews may be invisible to ChatGPT, and vice versa. Platform-specific optimization is not optional — it is the foundation of any serious GEO strategy.

How to Use This Skill

  1. Collect the target URL and the site's primary topic/industry
  2. Run each platform checklist below against the site
  3. Score each platform on the 0-100 rubric
  4. Generate GEO-PLATFORM-OPTIMIZATION.md with per-platform scores, gaps, and action items

Platform 1: Google AI Overviews (AIO)

How AIO Selects Sources

  • 92% of AIO citations come from pages already ranking in the top 10 organic results — traditional SEO is the gateway
  • However, 47% of citations come from pages ranking below position 5 — AIO has its own selection logic favoring clarity and directness over raw rank
  • AIO strongly favors pages with clean structure, direct answers, and scannable formatting
  • Featured snippet optimization has ~70% overlap with AIO optimization
  • AIO prefers concise, factual, unambiguous answers — hedging and filler reduce citation probability

Optimization Checklist

  1. Question-Based Headings: Use H2/H3 headings phrased as questions matching real user queries. Check Google's "People Also Ask" for the target topic and mirror those exact phrasings.
  2. Direct Answer in First Paragraph: After each question heading, provide a clear 1-2 sentence answer immediately. Then expand with supporting detail. The first sentence should be a standalone citation candidate.
  3. Tables and Structured Comparisons: AIO heavily cites tables. Convert any comparison, pricing, specification, or feature data into HTML tables. Use clear column headers.
  4. Ordered and Unordered Lists: Step-by-step processes should use ordered lists. Feature lists should use unordered lists. AIO extracts these directly.
  5. FAQ Sections: Add a dedicated FAQ section with 5-10 real questions. Use proper H3 headings for each question. While FAQPage schema rich results are restricted to govt/health sites since Aug 2023, the content pattern still helps AIO extraction.
  6. Definitions and Glossary Boxes: For any industry-specific term, provide a clear definition. Format: "[Term] is [concise definition]." AIO frequently cites definitions.
  7. Statistics with Sources: Include specific numbers with attribution. "According to [Source], [statistic]." AIO prefers citeable, specific claims over vague assertions.
  8. Publication Date: Include a visible publication date and last-updated date. AIO deprioritizes undated content for time-sensitive queries.
  9. Author Byline: Display author name with credentials. Link to an author page with bio, credentials, and sameAs links.
  10. Page Depth: Keep target pages within 3 clicks of homepage. AIO rarely cites deep, orphaned content.

Read the full file on GitHub · 272 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. 6d ago First seen · 272 lines · 34 tokens per session scan A 766750180009

Subscribe to this mod's changes

geo-platform-optimizer is a skill published in the GitHub repository bytefer/geo-seo-codex (11 stars, last pushed 2mo ago), licensed MIT. It adds 34 tokens to every session and 4,455 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to geo-platform-optimizer, differing in 6 lines, and is treated as a copy.

Related

Other skills, from other repositories

building-edgespark-apps

Build and modify EdgeSpark apps. Use when a project has edgespark.toml, the user mentions EdgeSpark, or work involves the edgespark CLI, server SDK types, storage/auth/database workflows, deployment, or @edgespark/web.

edgesparkhq/codex-plugins · 55 tokens

edgespark-frontend-design

Design and redesign EdgeSpark frontends with distinctive, production-grade visual direction instead of generic AI-looking UI. Use when building or polishing landing pages, marketing sites, dashboards, auth flows, portfolios, product surfaces, or reusable frontend sections in EdgeSpark, especially when the task…

edgesparkhq/codex-plugins · 87 tokens

ppt-design-skill

Design, generate, review, and revise editable PowerPoint presentations through a rigorous brief-to-PNG workflow using the public pptx-designer Python library.

sunchaokun/PPT-Design-Skill · 35 tokens

database-migrations

Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Kysely, Django, TypeORM, golang-migrate).

datit309/supergraph · 56 tokens

execute

Dispatch and execute implementation plans with TDD and checkpoints. Use when plan is ready. Parallel by default for independent tasks.

datit309/supergraph · 26 tokens

flutter-ui

Build Flutter UI from Figma MCP or image input. Scans src for design tokens (colors, sizes, text styles), existing components, and naming conventions before writing a single line of code. Never hard-codes values.

datit309/supergraph · 48 tokens