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Generate llms.txt

generate_llms_txt
Read-only

Generate an llms.txt file (llmstxt.org format) for a public website. Uses the site name, summary and pages you pass; anything missing is filled from the homepage and sitemap.xml. Returns the file text plus notes on how to improve it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pagesNoOptional list of the most important page URLs. If omitted, sitemap.xml is used.
summaryNoOne paragraph: what the site is, who it is for, what is most useful.
site_urlYesSite root, e.g. "https://example.com".
max_pagesNo
site_nameNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety/network profile is covered. The description adds genuinely new behavior: the fallback that missing inputs are filled from the homepage and sitemap.xml, and a return-value summary ('file text plus notes'). No contradiction with the annotations.

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?

Three tight sentences, front-loaded with the verb and artifact, then behavior, then return. Nothing redundant, though it could be marginally leaner.

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?

No output schema exists, and the description compensates by describing the return (file text plus improvement notes). The main residual gap is the undocumented max_pages/site_name parameters, but overall an agent has enough to invoke it correctly.

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

Parameters4/5

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

With 60% schema coverage, three of five parameters are already documented. The description adds meaning beyond the schema by explaining how site_name, summary and pages are consumed together and how omissions fall back to sitemap.xml. It leaves max_pages and site_name unaddressed, keeping it short of a 5.

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

Purpose4/5

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

States a specific verb and artifact: 'Generate an llms.txt file (llmstxt.org format) for a public website.' That is concrete and distinguishable from the robots.txt sibling by the named output format. It stops short of explicitly contrasting itself with generate_ai_robots_txt, so it is clear but not sibling-differentiating.

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?

The 'for a public website' scoping implies when it applies, but there is no explicit when-to-use, when-not-to-use, or pointer to alternatives among the siblings (check_ai_crawler_access, generate_ai_robots_txt). Usage is inferable rather than stated.

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

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