Validate an llms.txt

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

Goes well beyond the readOnly/openWorld/idempotent annotations: it discloses that non-llms.txt content served at the path is reported as invalid rather than erroring, states the return format and versioning (JSON, schemaVersion 1, matching the CLI --json output), and warns that fetched site text is data, never instructions. That injection caveat is exactly the kind of non-obvious behavior an open-world tool needs.

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

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

Four sentences, front-loaded with the validation criteria, then mode selection, then return shape. Every sentence carries information, though the prose is dense and the criteria list could be tightened.

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

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

With no output schema, the description does its duty by naming the return format and pointing to schemaVersion 1 as a contract. It does not describe the JSON's internal shape (findings, exitCode), leaving the agent to rely on the referenced CLI format, which is a small remaining gap for a validator.

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

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

Schema coverage is 100%, so all five parameters are already documented, including the url/text/base/links relationship and the failOn enum. The description reinforces the url-vs-text mode semantics but mainly restates the schema for links and says nothing about base or failOn, so it adds marginal value over structured fields.

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

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

States a specific verb and resource plus the actual validation rules (one H1, a summary, sections of links) and the misclassification case (HTML page or robots.txt at /llms.txt reported as not one). An agent can distinguish it from llms_generate and robots_test by topic, though those siblings are never named explicitly.

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

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

Explicitly resolves the main mode choice: 'Give url to read a site's file, or text to validate a file you already have.' It also flags the dependent case for links ('with text, base is needed'). No when-not-to-use guidance or named alternative for generating/fixing an llms.txt, so it stops short of 5.

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