geo-llmstxt

geo-llmstxt is a skill for Claude Code from KSfak/Zubair-Trabzada-YouTube. It costs 46 tokens per session (3,695 once invoked), scanned A, a copy of geo-llmstxt, MIT.

A tool for checking and creating an llms.txt file, an emerging website file that gives AI systems a structured summary of the site's purpose, important pages, and organization.

In plain words
What is it for?
Use it to validate an existing llms.txt file or generate one by crawling a website.
Why use it?
It helps you assess whether a site gives AI systems clear guidance about which content matters, instead of relying only on the systems' own crawling and interpretation.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to validate an existing llms.txt file or generate one by crawling a website.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ksfak/zubair-trabzada-youtube/geo-llmstxt
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 KSfak/Zubair-Trabzada-YouTube --skill geo-llmstxt
Clone the repo
git clone --depth 1 https://github.com/KSfak/Zubair-Trabzada-YouTube

Made for: Claude Code.

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-llmstxt

README.md
[![agentmods](https://agentmods.dev/badge/skills/ksfak/zubair-trabzada-youtube/geo-llmstxt/github.svg)](https://agentmods.dev/skills/ksfak/zubair-trabzada-youtube/geo-llmstxt)
Your own site
<a href="https://agentmods.dev/skills/ksfak/zubair-trabzada-youtube/geo-llmstxt"><img src="https://agentmods.dev/badge/skills/ksfak/zubair-trabzada-youtube/geo-llmstxt/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-llmstxt

Your own site · 80×15
<a href="https://agentmods.dev/skills/ksfak/zubair-trabzada-youtube/geo-llmstxt"><img src="https://agentmods.dev/badge/skills/ksfak/zubair-trabzada-youtube/geo-llmstxt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,695 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 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 $0.00046 $0.03695
Opus 5 $0.00023 $0.01847
Sonnet 5 $0.00009 $0.00739
Haiku 4.5 $0.00005 $0.00369

Measured 12d ago against content hash de12c9cc28b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

geo-llmstxt 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 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.

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-llmstxt — 0 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-llmstxt/SKILL.md · 433 lines

How it starts

The opening of the file, as written. The whole thing — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.

llms.txt Standard Analysis and Generation Skill

Purpose

This skill handles everything related to the llms.txt standard -- an emerging convention (proposed by Jeremy Howard in September 2024, gaining adoption through 2025-2026) that allows websites to provide structured guidance to AI systems about their content, structure, and key information. It is analogous to robots.txt (which tells crawlers what NOT to access) but instead tells AI systems what IS most useful to understand about the site.

Why llms.txt Matters

AI language models face a fundamental challenge when processing websites: they must determine which pages are most important, what the site is about, and how content is organized -- typically by crawling many pages and inferring structure. llms.txt solves this by providing an explicit, machine-readable (and human-readable) summary.

Benefits of having a well-crafted llms.txt:

  1. Faster AI comprehension: AI systems can understand your site's purpose and structure from a single file rather than crawling dozens of pages.
  2. Controlled narrative: You choose which pages and facts AI systems see first, shaping how they represent your brand.
  3. Higher citation accuracy: AI systems that consult llms.txt can cite the correct, authoritative page for each topic.
  4. Reduced misrepresentation: Key facts (pricing, features, locations) are stated explicitly, reducing AI hallucination about your business.
  5. Early adopter advantage: As of early 2026, fewer than 5% of websites have an llms.txt file, making it a differentiator.

The llms.txt Specification

File Location

The file MUST be located at the root of the domain:

https://example.com/llms.txt

Format Specification

The file uses Markdown formatting with specific conventions:

# [Site Name]

> [One-sentence description of what the site/business does. Keep under 200 characters.]

## Docs

- [Page Title](https://example.com/page-url): Concise description of what this page covers and why it matters.
- [Another Page](https://example.com/another-page): Description of content.

## Optional

- [Less Critical Page](https://example.com/optional-page): Description.

Read the full file on GitHub · 433 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 · 433 lines · 46 tokens per session scan A de12c9cc28b0

Subscribe to this mod's changes

geo-llmstxt is a skill published in the GitHub repository KSfak/Zubair-Trabzada-YouTube (22 stars, last pushed 6mo ago), licensed MIT. It adds 46 tokens to every session and 3,695 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-llmstxt, differing in 0 lines, and is treated as a copy.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens