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

Annotations already mark this as read-only, idempotent, and non-destructive. The description adds meaningful behavioral detail: it produces 'Errors and warnings with line numbers and fixes, plus the parsed links,' and explicitly states 'nothing fetched.' No contradiction with annotations.

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?

The description packs useful information, and the key behavior is front-loaded, but the embedded JSON-RPC literal for a different tool is noisy and distracts from the definition of validate_llms_txt. It could be trimmed to improve readability without losing meaning.

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?

For a one-parameter, read-only, idempotent validator with no output schema, the description covers input constraints, validation rules, output components, side-effect-free behavior, and provides an illustrative example. Nothing essential is missing.

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?

The input schema already fully describes the text parameter at 100% coverage, including 'The llms.txt content itself, not a URL.' The description reinforces this by noting 'pasted' input and 'Text in, nothing fetched,' adding practical nuance beyond the schema.

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?

The description states a specific verb and resource: "Checks pasted llms.txt against the format: one H1, a blockquote summary, H2 sections of `- [name](url): notes`." This clearly distinguishes it from siblings like validate_agent_card, and the validation rules are concrete.

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?

The opening 'FIRST CALL, needs nothing' plus the JSON-RPC example for no_arguments_check_this_hosts_own_discovery_documents explicitly guides the agent to call that tool first. Saying 'Text in, nothing fetched' also clarifies the intended input style, indirectly distinguishing this from fetching/sitemap tools. It does not explicitly name alternative siblings, but the context is sufficient.

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