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generate_llms_txt

Read-onlyIdempotent

Create an llms.txt file for any website to help AI models understand and interact with its content, preparing site owners for AI discoverability.

Instructions

Use this to generate an llms.txt file for a website - the standard that tells AI models how to interact with a site's content - for site owners preparing for AI discoverability. Not for reading a site's existing llms.txt (fetch_url on /llms.txt). Cost: 5 credits. Example: generate_llms_txt({url: "https://example.com"})

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe website URL to generate llms.txt for
formatNoOutput format: llms.txt, llms-full.txt, or bothboth
outputOptionsNoOutput customization and organization details
analysisOptionsNoWebsite analysis options for depth, scope, and detection
complianceLevelNoCompliance level for generated guidelinesstandard

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv6.5.0
    • changedInput schema / properties / outputOptions / properties / contactEmail / pattern
      Previous value: -"^(?!\\.)(?!.*\\.\\.)([A-Za-z0-9_'+\\-\\.]*)[A-Za-z0-9_+-]@([A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"New value: +"^(?:[A-Za-z0-9_'+\\-]+\\.)*[A-Za-z0-9_'+\\-]*[A-Za-z0-9_+-]@(?:[A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"
  2. Changed4 schema fields changedv6.0.0
    • removedInput schema / additionalProperties
      Removed value: -false
    • removedInput schema / properties / analysisOptions / additionalProperties
      Removed value: -false
    • removedInput schema / properties / outputOptions / additionalProperties
      Removed value: -false
    • addedInput schema / properties / outputOptions / properties / contactEmail / pattern
      Added value: +"^(?!\\.)(?!.*\\.\\.)([A-Za-z0-9_'+\\-\\.]*)[A-Za-z0-9_+-]@([A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"
  3. Changed4 schema fields changedv5.0.4
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedInput schema / properties / analysisOptions / properties / checkSecurity / default
      Previous value: -trueNew value: +false
    • addedInput schema / properties / analysisOptions / properties / probeRateLimit
      Added value: +{
+  "default": false,
+  "type": "boolean"
+}
    • addedInput schema / properties / outputOptions / properties / robotsStyle
      Added value: +{
+  "default": false,
+  "type": "boolean"
+}
  4. First observedv4.10.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: the cost (5 credits) and a concrete example call. It doesn't describe side effects or rate limits, but the annotations cover the key behavioral traits. The cost disclosure is a valuable addition beyond annotations.

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

Conciseness5/5

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

Three sentences with zero waste. The core purpose is front-loaded, the exclusion is stated early, and the cost plus example are packed efficiently. Every sentence earns its place.

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 tool with 5 parameters, 100% schema coverage, and no output schema, the description covers the essential context: what it does, when to use it, cost, and an example. The only minor gap is that it doesn't describe what the return value looks like, but with no output schema and rich parameter schema, the description is largely complete for an agent to select and invoke the tool correctly.

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 description coverage is 100%, so the schema already documents all parameters. The description adds a concrete example with the url parameter, which is helpful, but doesn't add meaning beyond the schema for the other parameters. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

The description states a specific verb ('generate'), a specific resource ('llms.txt file for a website'), and the purpose ('standard that tells AI models how to interact with a site's content'). It also explicitly distinguishes itself from reading an existing llms.txt by pointing to fetch_url on /llms.txt. This is a clear, specific purpose that differentiates it from siblings.

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

Usage Guidelines5/5

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

The description explicitly says when to use this tool ('for site owners preparing for AI discoverability') and when not to use it ('Not for reading a site's existing llms.txt (fetch_url on /llms.txt)'). It names the alternative tool and the condition that selects it. This is explicit usage guidance.

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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