seo-geo-factdensity

seo-geo-factdensity is a skill for Claude Code from Hainrixz/claude-seo-ai. It costs 69 tokens per session (1,635 once invoked), scanned A, original, MIT.

A page audit that checks how often writing includes numbers, original data, and links to trustworthy outside sources. It is designed to show how easily search and answer systems can verify and cite the page.

In plain words
What is it for?
Use it to review articles, landing pages, or other main-content pages for unsupported claims, weak sourcing, and missing evidence. It also checks whether first-party research claims explain their method or sample.
Why use it?
It finds long claims that have no figures or supporting sources. This helps reveal where a page may seem vague or difficult to verify.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Runs only inside its plugin — its command needs a path that Claude Code sets for a plugin’s own hooks and for nothing else. Install the plugin, not this.

Part of the claude-seo-ai plugin — 34 skills, 5 agents, 1 hook shipped together

Good fit Use it to review articles, landing pages, or other main-content pages for unsupported claims, weak sourcing, and missing evidence. It also checks whether first-party research claims explain their method or sample.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.

Claude Code
/plugin marketplace add Hainrixz/claude-seo-ai
Claude Code
/plugin install claude-seo-ai

Made for: Claude Code.

Or install claude-seo-ai, the plugin that ships this one along with the rest of its 34 skills, 5 agents, 1 hook.

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-geo-factdensity

README.md
[![agentmods](https://agentmods.dev/badge/skills/hainrixz/claude-seo-ai/seo-geo-factdensity/github.svg)](https://agentmods.dev/skills/hainrixz/claude-seo-ai/seo-geo-factdensity)
Your own site
<a href="https://agentmods.dev/skills/hainrixz/claude-seo-ai/seo-geo-factdensity"><img src="https://agentmods.dev/badge/skills/hainrixz/claude-seo-ai/seo-geo-factdensity/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 seo-geo-factdensity

Your own site · 80×15
<a href="https://agentmods.dev/skills/hainrixz/claude-seo-ai/seo-geo-factdensity"><img src="https://agentmods.dev/badge/skills/hainrixz/claude-seo-ai/seo-geo-factdensity.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,635 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00069 $0.01635
Opus 5 $0.00034 $0.00817
Sonnet 5 $0.00014 $0.00327
Haiku 4.5 $0.00007 $0.00163

Measured 5d ago against content hash 6c87c22441c7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

seo-geo-factdensity 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 5d 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.

skills/seo-geo-factdensity/SKILL.md · 46 lines

How it starts

The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.

seo-geo-factdensity (M12)

Generative engines preferentially cite passages that are concrete, quantified, and attributable. This module measures how "citable" the page's prose is — facts, numbers, original data, and authoritative outbound links — not vocabulary. AI retrieval/citation context: references/ai-crawlers.md.

Inputs

Work from the PageSnapshot named in your dispatch envelope: read parsed from <run_dir>/pages/<slug>.json (anchors[] for outbound links, text_sample) and the HTML file for passage-level counts; Grep pages/<slug>.html for verbatim evidence; site artifacts live in <run_dir>/site/{robots.json,sitemaps.json,discovery.json}. Deterministic findings already emitted by audit.mjs are listed in <run_dir>/findings.deterministic.json — do not re-emit those ids; add model-judged findings only. If invoked directly with a URL/path and no snapshot exists, first run node "${CLAUDE_PLUGIN_ROOT}/scripts/snapshot.mjs" <target> --out "${CLAUDE_PLUGIN_DATA}/runs" and use the printed snapshot path.

Audits

Working from the PageSnapshot (parsed_rendered when render.used is not none, else parsed):

  1. Statistic/number density per passage: tokenize the main content into passages (paragraph / <li> / heading-bounded block) and count numeric tokens — figures, percentages, dates, quantities, ranges. Flag long passages of pure assertion with zero numeric support.
  2. Proprietary/original data: detect first-party-data signals — patterns like "our study", "our survey", "our data", "we analyzed", "we surveyed", "in our test", "internal data" — and note whether such claims are backed by a method/sample, a table, or a chart.
  3. Outbound citations: count outbound links from the main content to authoritative sources (standards bodies, primary research, official docs, .gov/.edu, named publications); distinguish them from internal/nav/affiliate links.
  4. Claim-without-source flags: detect strong factual or comparative claims ("the most", "fastest", "studies show", superlatives, hard numbers) that carry no inline citation or data reference, and mark each as a candidate for sourcing.

Read the full file on GitHub · 46 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. 5d ago Changed · +6 lines 6c87c22441c7
  2. 6d ago Changed · +3 lines a27599c06350
  3. 12d ago First seen · 37 lines · 69 tokens per session scan A af8bb485b2b3

Subscribe to this mod's changes

seo-geo-factdensity is a skill published in the GitHub repository Hainrixz/claude-seo-ai (59 stars, last pushed 5d ago), licensed MIT. It adds 69 tokens to every session and 1,635 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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