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

Annotations already declare the tool as read-only, idempotent, and non-destructive, and the description adds behavioral detail by explaining it 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format.' This goes beyond the annotations without contradicting them, though it omits potential edge cases like rate limits or failure behavior, so a 4 is appropriate.

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 structured with a clear opening sentence stating the core function, followed by a brief explanation of process and output, and a concise list of use cases. Every sentence contributes value, though the use-case list could be seen as slightly redundant with the opening. It is appropriately sized and front-loaded.

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 tool with two parameters and no output schema, the description covers the key context: it explains the input (URL), the process (fetch/extract), the output format (standard llms.txt markdown), and the deployment location ('drop at site-root/llms.txt'). It does not discuss error handling or rate limits, but given the tool's simplicity and annotation coverage, this is reasonably 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 description coverage is 100%, so the baseline is 3. The description adds minimal value beyond the schema: it mentions 'any URL' for the url parameter but does not elaborate on max_links beyond what the schema already provides. Since the schema fully documents both parameters, the description does not need to compensate.

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 the verb ('Generate') and resource ('a production-ready llms.txt file for any URL'), and explains the purpose of enabling AI crawlers to index a site. It also lists use cases that implicitly differentiate it from sibling tools like ai_visibility_check or scan_competitor_ai_presence, but does not explicitly name alternatives, so it misses the top score.

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 provides explicit use cases ('Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor'), giving clear context for when to use the tool. However, it lacks any 'when not to use' guidance or explicit comparison to alternative tools, so it falls short of a 5.

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