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JavaScript
Remote

generate_llms_txt

Read-onlyIdempotent

Generate an llms.txt file for a website so AI models know how to interact with its content. Helps site owners prepare their sites 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
max_inline_charsNoLargest result to return inline, in characters of its JSON. Over it, the call returns a preview plus a result_handle for read_result instead of the whole result (default 40,000; env CRAWLFORGE_MAX_INLINE_CHARS)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv6.19.2
    • addedInput schema / properties / max_inline_chars
      Added value: +{
+  "description": "Largest result to return inline, in characters of its JSON. Over it, the call returns a preview plus a result_handle for read_result instead of the whole result (default 40,000; env CRAWLFORGE_MAX_INLINE_CHARS)",
+  "maximum": 10000000,
+  "minimum": 1000,
+  "type": "integer"
+}
  2. 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,}$"New value: +"^(?:[A-Za-z0-9_'+\\-]+\\.)*[A-Za-z0-9_'+\\-]*[A-Za-z0-9_+-]@(?:[A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"
  3. 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,}$"
  4. 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"
+}
  5. First observedv4.10.0

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive). The description adds non-annotation context: the 5-credit cost and a usage example. It stops short of describing output shape or how the 100-500 page analysis behaves, so 4 rather than 5.

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?

Front-loaded with the core purpose, then the exclusion, cost, and example in tight order. Dense but no wasted sentences; the parenthetical gloss on llms.txt is slightly verbose.

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 six parameters including two nested option objects and no output schema, the description gives purpose, routing, cost, and an example. It does not explain the returned file/handle behavior, but the safety annotations and full schema coverage make it adequate.

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 url, format, and the nested options. The description only adds an example call, not new semantics for the many nested analysis/output parameters. Baseline 3 is appropriate.

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 (generate) and resource (llms.txt file for a website) and explains what llms.txt is. It is clearly distinguishable from fetch_url and other scraping siblings because it is about producing a file, not reading content.

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?

Explicitly scopes usage to site owners preparing for AI discoverability and names the exclusion: 'Not for reading a site's existing llms.txt (fetch_url on /llms.txt).' It also supplies cost (5 credits) and a concrete invocation example, leaving nothing to inference.

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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