Skip to main content
Glama

GEO SEO Records

Draft the llms.txt of a website

draft_llms_txt
Read-onlyIdempotent

Builds an llms.txt for a website from facts read on it — the site name and description from its home page, then pages from its sitemap with their titles and meta descriptions, grouped by section — and reviews the existing llms.txt if there is one (declared name, links, claims no machine can verify). The draft is ready to edit and publish at /llms.txt. Docs: https://seorecords.com/assistants

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe website address, e.g. example.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent and open-world, and the description adds substantive context beyond that: the exact data sources it fetches (home page, sitemap, existing llms.txt), what it critiques (declared name, links, unverifiable claims), and where the output belongs. It stops short of stating rate limits, fetch scope limits, or failure behavior when no sitemap exists.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

One dense, front-loaded sentence plus a short publishing note and docs link; the most important clause (what it builds and from what) comes first. It is slightly run-on with stacked em-dash and parenthetical asides, but no sentence is filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter, no-output-schema, read-only tool, the description covers input sources, review behavior, and the resulting artifact location well enough to call it correctly. Missing only edge-case behavior (sites without sitemaps, pre-existing conflicting llms.txt) and signal on how the draft is returned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single url parameter with a format example ('example.com'), so the schema already carries the semantics. The description never mentions the url argument or adds accepted-format nuance beyond it, leaving this at the baseline for a fully documented param.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (builds/drafts) and resource (llms.txt) and enumerates exactly what it draws on — home page name/description, sitemap pages with titles and meta descriptions. It is clearly distinct from siblings like check_ai_readiness or open_robots_txt_to_ai, which an agent can tell apart without reading schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the artifact produced (a draft 'ready to edit and publish at /llms.txt'), but no when-to-use vs alternative guidance is given against the sibling tools. Nothing tells the agent whether to run this before or instead of check_ai_readiness.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources