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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false. The description adds that it fetches a page and extracts content, but does not disclose potential errors, timeouts, or limitations (e.g., only works for HTML pages).

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 well-structured sentences with no extraneous text. The first sentence states purpose, the second adds process detail, the third specifies output format, and the fourth lists usage scenarios.

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?

Annotations and schema cover safety and parameters adequately. The description adds usage context and output format. However, missing guidance on URL accessibility requirements or error handling, which would make it fully complete.

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 the description does not need to add param details. It implicitly mentions 'max_links' via 'key links' but does not clarify its behavior 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 clearly states 'Generate a production-ready llms.txt file for any URL' with a specific verb and resource, and distinguishes it by naming the output format and use cases.

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?

Provides use case examples ('getting a client's site indexed', 'drafting for your own project', 'auditing competitor') but does not explicitly differentiate from sibling tools like ai_visibility_check or scan_competitor_ai_presence, nor state when not to use it.

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