geo-schema

geo-schema is a skill for Claude Code, Codex from TheSmokeDev/geo-skills. It costs 59 tokens per session (3,878 once invoked), scanned A, original, MIT.

A tool for checking and creating Schema.org structured data, which is machine-readable information embedded in web pages. It produces JSON-LD, a common format for describing page facts to search engines.

In plain words
What is it for?
Use it to audit, validate, or generate JSON-LD for organizations, offers, dates, locations, specifications, and related entities. It is useful when making visible page facts easier for search systems to interpret.
Why use it?
It helps search engines understand entities, facts, and page content consistently, and can support enhanced search-result displays called rich results. It does not claim that markup alone improves citations in AI answers.

Skill for Claude CodeCodex

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

Good fit Use it to audit, validate, or generate JSON-LD for organizations, offers, dates, locations, specifications, and related entities. It is useful when making visible page facts easier for search systems to interpret.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/thesmokedev/geo-skills/geo-schema
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.

Any agent
npx skills add TheSmokeDev/geo-skills --skill geo-schema
Clone the repo
git clone --depth 1 https://github.com/TheSmokeDev/geo-skills

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-schema

README.md
[![agentmods](https://agentmods.dev/badge/skills/thesmokedev/geo-skills/geo-schema/github.svg)](https://agentmods.dev/skills/thesmokedev/geo-skills/geo-schema)
Your own site
<a href="https://agentmods.dev/skills/thesmokedev/geo-skills/geo-schema"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/geo-schema/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for geo-schema

Your own site · 80×15
<a href="https://agentmods.dev/skills/thesmokedev/geo-skills/geo-schema"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/geo-schema.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 59 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,878 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found 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 $0.00059 $0.03878
Opus 5 $0.00030 $0.01939
Sonnet 5 $0.00012 $0.00776
Haiku 4.5 $0.00006 $0.00388

Measured 12d ago against content hash 9eb564098023, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

geo-schema scanned grade A with 1 finding 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 12d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

1. Fetch the target page HTML using curl or WebFetch
skills/geo-schema/SKILL.md · 371 lines

How it starts

The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GEO Schema & Structured Data

Purpose

Structured data does two jobs well: earning Google rich results and keeping entity data unambiguous (who the organization is, what it offers, which profiles belong to it). That is the scope of this skill.

What schema does NOT do: lift AI citations. In the Ahrefs controlled study (1,885 pages that added JSON-LD, reported May 2026 via Search Engine Journal), citation rates moved ChatGPT +2.2%, AI Mode +2.4%, AIO -4.6% — all within noise. Adding markup alone produced no citation lift on any platform. Do not sell schema as a GEO tactic.

The nuance worth keeping (SSRN, Feb 2026): schema that carries concrete, extractable facts (dates, prices, locations, specs) can still correlate with citation — but the lift comes from the quotable data, not the markup itself. Put the facts in visible, well-structured page content first; schema is the machine-readable echo, not the signal.

With that framing, complete and accurate structured data remains worthwhile: rich results still win SERP real estate, and clean entity data (Organization, sameAs, contactPoint) removes ambiguity for every system — search engines, knowledge graphs, and AI platforms alike.

How to Use This Skill

  1. Fetch the target page HTML using curl or WebFetch
  2. Detect all existing structured data (JSON-LD, Microdata, RDFa)
  3. Validate detected schemas against Schema.org specifications
  4. Identify missing recommended schemas based on business type
  5. Generate ready-to-use JSON-LD code blocks
  6. Output GEO-SCHEMA-REPORT.md

Step 1: Detection

Scan for JSON-LD

Look for <script type="application/ld+json"> blocks in the HTML. Parse each block as JSON. A page may contain multiple JSON-LD blocks — collect all of them.

Scan for Microdata

Look for elements with itemscope, itemtype, and itemprop attributes. Map the hierarchy of nested items. Note: Microdata is harder for AI crawlers to parse than JSON-LD. Flag a recommendation to migrate to JSON-LD if Microdata is the only format found.

Read the full file on GitHub · 371 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. 12d ago First seen · 371 lines · 59 tokens per session scan A 9eb564098023

Subscribe to this mod's changes

geo-schema is a skill published in the GitHub repository TheSmokeDev/geo-skills (22 stars, last pushed 8d ago), licensed MIT. It adds 59 tokens to every session and 3,878 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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