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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive, but the description adds meaningful behavioral context: it fetches the page, extracts title/description/key links, and emits standard llms.txt markdown. This goes beyond the annotations without contradicting them, though it doesn't address potential errors or rate limits.

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 is concise and well-structured: it starts with the primary action, then explains the process and output format, and ends with practical use cases. Every sentence earns its place with no redundancy or filler.

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 simple two-parameter read-only tool without an output schema, the description sufficiently covers the return value ('a single text blob ready to drop at site-root/llms.txt') and typical use. It doesn't describe edge cases or limitations, but these aren't necessary for such a straightforward tool.

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 description coverage is 100% and both parameters (url, max_links) are self-explanatory in the schema. The description adds no additional parameter-level detail, so the baseline of 3 is appropriate.

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 uses a specific verb ('Generate') and resource ('llms.txt file'), and clarifies scope ('for any URL'). It explains the process (fetches, extracts, emits) and differentiates from siblings by focusing on a distinct output artifact, making it clear what the tool does.

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 description lists concrete use cases ('getting a client's site indexed by AI', 'drafting llms.txt', 'auditing how an AI crawler would see a competitor'), providing clear context for when to use it. However, it doesn't explicitly name alternative tools or state when not to use it, stopping short of full exclusion guidance.

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