geo-artifacts

geo-artifacts is a skill for Claude Code, Codex from bemoshiur/OmniRank. It costs 54 tokens per session (1,080 once invoked), scanned C, original, MIT.

A tool for generating three machine-readable files—llms.txt, llms-full.txt, and facts.json—that describe a website for AI systems. These files provide an index, fuller content, and structured facts.

In plain words
What is it for?
Use it when preparing a website to be understood as a reliable source by AI crawlers. It can generate the files from site content in Node.js or Python.
Why use it?
It gives AI services such as ChatGPT, Claude, Perplexity, and Gemini a prepared source of information they can read and cite. It does not check whether the files are actually published on the live site.

Skill for Claude CodeCodex

Part of the omnirank plugin — 3 skills shipped together

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/bemoshiur/omnirank/geo-artifacts
Any agent
npx skills add bemoshiur/OmniRank --skill geo-artifacts
Clone the repo
git clone --depth 1 https://github.com/bemoshiur/OmniRank

Made for: Claude Code, Codex.

Or install omnirank, the plugin that ships this one along with the rest of its 3 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-artifacts

README.md
[![agentmods](https://agentmods.dev/badge/skills/bemoshiur/omnirank/geo-artifacts.svg)](https://agentmods.dev/skills/bemoshiur/omnirank/geo-artifacts)
Your own site
<a href="https://agentmods.dev/skills/bemoshiur/omnirank/geo-artifacts"><img src="https://agentmods.dev/badge/skills/bemoshiur/omnirank/geo-artifacts.svg" alt="Measured on agentmods" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,080 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 2 findings. Scan, not verified.
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 $0.00054 $0.01080
Opus 5 $0.00027 $0.00540
Sonnet 5 $0.00011 $0.00216
Haiku 4.5 $0.00005 $0.00108

Measured 3d ago against content hash 53ccc0801e2e, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

geo-artifacts scanned grade C with 2 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 3d 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.

Tells the agent never to refusehighAnti-refusal

Suppressing the ability to decline removes a core safety control; a later harmful request then succeeds.

5. **Never infer a content licence — but never refuse to generate either.** `geo.license`

Makes network callslowCapability

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

curl -sI https://<site>/llms.txt | head -1
skills/geo-artifacts/SKILL.md · 86 lines

How it starts

The opening of the file, as written. The whole thing — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GEO artifacts

Generate the three files that let generative engines ingest a site as ground truth: llms.txt (curated index), llms-full.txt (full corpus), and facts.json (structured facts). Each carries an explicit citation licence.

When to use

"Make us citable by AI", "generate llms.txt", "why doesn't Perplexity know about us", "update facts.json after publishing".

When NOT to use

  • Diagnosing whether the files are already served correctly — that is audit.
  • Page-level JSON-LD or AnswerBlocks — that is aeo-onpage (planned, not in v0.1.0).
  • Submitting URLs to search engines — that is indexing (planned, not in v0.1.0).

Generation only writes the three artifacts. It never verifies they are actually served in production — that is audit, and the "After generating" section below.

Which path to take

Node, when the site's content lives in this repo. It consumes an already-materialized Page[] ({ url, title, description, answer }) that your own prebuild script gathers — e.g. from getPages(): Promise<Page[]> reading your CMS or database directly — so it sees draft flags, DB rows, and unpublished states a crawler cannot.

Python, for any other stack or an external site. It reconstructs the corpus itself by crawling the sitemap and the rendered HTML.

# Python / crawl path
python3 -m omnirank.cli geo --config omnirank.config.json --out public
# flags: url (optional, omit when using --config), --config PATH, --out DIR (default: public)

# Node / in-repo path — call generate(config, pages, outDir) from the site's own
# prebuild script, after gathering pages with your own getPages()

Both paths share the same field logic (licence block, sameAs null-dropping, the published gate on statistics) and were verified to emit byte-identical output for identical input, aside from generatedAt timestamp precision (Python emits microseconds, Node emits milliseconds — both valid RFC 3339 UTC).

Rules

  1. These are physical files. Write them into publicDir at build time. Never serve them from a dynamic route — see references/serving-gotchas.md for the 403 this causes.
  2. Wire generation into prebuild AND the deploy script. OpenNext runs next build, not npm run build, so a prebuild hook alone silently does nothing in production.
  3. Never invent a statistic. facts.statistics carries only entries explicitly marked published: true. No published entries means the key is omitted entirely, not emitted empty.
  4. Null sameAs values are dropped, not emitted as null. A null is an entity gap to fill, and offsite-entity (planned, not in v0.1.0) reports on it.
  5. Never infer a content licence — but never refuse to generate either. geo.license has no default. These files are written into publicDir and published on the open web, so the licence text inside them is a real, standing grant of reuse rights over the site owner's content — not a suggestion OmniRank can guess. If geo.license is unset, generation treats it exactly like the explicit "none" opt-out: it proceeds and grants nothing, and (Python CLI only) omnirank geo prints a one-line notice to stderr naming the config key, so the "no rights" default isn't chosen silently. Set geo.license to a licence you have actually chosen (e.g. "CC-BY-4.0") to grant reuse rights, or to the explicit opt-out "none" (or JSON null) for sites that grant no reuse rights at all and to silence the notice — the citation block states plainly that no licence is granted instead of inventing one.

Read the full file on GitHub · 86 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 3d ago First seen · 86 lines · 54 tokens per session scan C 53ccc0801e2e

Subscribe to this mod's changes

geo-artifacts is a skill published in the GitHub repository bemoshiur/OmniRank (6 stars, last pushed 4d ago), licensed MIT. It adds 54 tokens to every session and 1,080 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 2 findings (tells the agent never to refuse, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.