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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, covering the safety and side-effect profile. The description adds valuable process details: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format' and notes the output is a 'single text blob.' This goes beyond the annotations without being exhaustive.

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 compact and front-loaded, starting with the primary purpose and then adding process, output format, and use cases in just a few sentences. Every sentence contributes meaningful information, 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 tool with two parameters, comprehensive annotations, and full schema descriptions, the description adequately covers purpose, behavior, output format, and use cases. The absence of an output schema is mitigated by the explicit statement that the output is a 'single text blob' in standard llms.txt markdown.

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 input schema fully documents both parameters (url and max_links). The description provides overall context about generating llms.txt but does not add any additional meaning to the individual parameters beyond what the schema already specifies, hence the baseline score of 3.

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 the tool's function with a specific verb ('Generate') and resource ('llms.txt file'), and clearly differentiates it from sibling tools by focusing on generating this specific file for any URL. The 'Useful for' list adds concrete context, making the purpose unmistakable.

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 ('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 does not explicitly mention when not to use it or name alternatives, 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.