geo-citability

geo-citability is a skill for Claude Code from techhorizonlabs/thl-open. It costs 61 tokens per session (3,750 once invoked), scanned A, a copy of geo-citability, MIT.

A checker that rates how likely website content is to be quoted or cited by AI systems such as ChatGPT, Claude, Perplexity, and Gemini.

In plain words
What is it for?
It is for scoring web pages, identifying weak or incomplete answers, and rewriting passages so their meaning is self-contained and easier for AI systems to use.
Why use it?
It points out why a passage may be hard for an AI system to extract and suggests clearer ways to write it.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is **Provenance (THL):** tag the score `[scan]` (data fetched this run), `[partial-scan]`, `[heuristic]` (judgement, no data), or `[unmeasured]` — and emit `—` ins.

Part of the thl-open plugin — 17 skills shipped together

Good fit It is for scoring web pages, identifying weak or incomplete answers, and rewriting passages so their meaning is self-contained and easier for AI systems to use.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/techhorizonlabs/thl-open
agentmods
npx agentmods add skills/techhorizonlabs/thl-open/geo-citability

Made for: Claude Code.

Or install thl-open, the plugin that ships this one along with the rest of its 17 skills.

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-citability

README.md
[![agentmods](https://agentmods.dev/badge/skills/techhorizonlabs/thl-open/geo-citability/github.svg)](https://agentmods.dev/skills/techhorizonlabs/thl-open/geo-citability)
Your own site
<a href="https://agentmods.dev/skills/techhorizonlabs/thl-open/geo-citability"><img src="https://agentmods.dev/badge/skills/techhorizonlabs/thl-open/geo-citability/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-citability

Your own site · 80×15
<a href="https://agentmods.dev/skills/techhorizonlabs/thl-open/geo-citability"><img src="https://agentmods.dev/badge/skills/techhorizonlabs/thl-open/geo-citability.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,750 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 86% 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 $0.00061 $0.03750
Opus 5 $0.00030 $0.01875
Sonnet 5 $0.00012 $0.00750
Haiku 4.5 $0.00006 $0.00375

Measured 9d ago against content hash ace8626ceda4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

geo-citability 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 9d 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

86% identical to geo-citability — 15 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-citability/SKILL.md · 323 lines

How it starts

The opening of the file, as written. The whole thing — 323 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AI Citability Scoring Skill

Core Insight

AI language models cite passages that meet specific structural criteria. Research on Generative Engine Optimization (Aggarwal et al., KDD 2024) found GEO tactics can lift visibility in AI answers by roughly 30–115% depending on the tactic and query set (see docs/SOURCES.md for provenance on this and the length figure). The pattern: AI systems preferentially extract passages that are ~134–167 words long, self-contained (understandable without surrounding context), fact-rich (specific statistics, dates, named entities), and directly answer a question in the first 1-2 sentences.

This score is a proxy, not a measurement. It scores how extractable your passages are against these research-derived criteria — it does not ask an AI engine whether it actually quoted you. Any "expected lift" is a research-informed estimate, never a promise. For the live check of whether the engines name you, run the free scan at areyoufoundbyai.com (two buyer questions on ChatGPT and Gemini; the trial and paid tiers cover all seven engines).

This is fundamentally different from traditional SEO copywriting, which optimizes for keyword density and user engagement metrics. GEO citability optimizes for extractability -- the ease with which an AI system can pull a passage from your content and present it as a direct answer.


Citability Scoring Rubric (0-100)

Category 1: Answer Block Quality (30% of total score)

This measures whether content contains clear, quotable answer passages that AI systems can extract verbatim.

Scoring Criteria:

Score Criteria
90-100 Every major section opens with a 1-2 sentence direct answer. Uses "X is..." or "X refers to..." patterns. First 40-60 words of each section can stand alone as a complete answer.
70-89 Most sections have clear answer openings. Some definition patterns present. Answers are identifiable but may need minor context.
50-69 Some sections have answer-like openings but many bury the answer in the middle or end of paragraphs. Few explicit definition patterns.
30-49 Answers are generally buried in long paragraphs. No consistent definition patterns. Content is narrative-driven rather than answer-driven.
0-29 No identifiable answer blocks. Content is entirely narrative, conversational, or fragmented. AI would struggle to extract any quotable passage.

Read the full file on GitHub · 323 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. 9d ago First seen · 323 lines · 61 tokens per session scan A ace8626ceda4

Subscribe to this mod's changes

geo-citability is a skill published in the GitHub repository techhorizonlabs/thl-open (15 stars, last pushed yesterday), licensed MIT. It adds 61 tokens to every session and 3,750 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to geo-citability, differing in 15 lines, and is treated as a copy.

Related

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