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

Annotations already convey read-only, idempotent, and non-destructive behavior. The description adds meaningful process details: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format,' plus notes the output is a 'single text blob.' This goes beyond the annotation hints, although it omits error handling or rate-limit specifics.

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 yet comprehensive, leading with the core function, then the method, output, and use cases. Every sentence contributes value with no redundancy or filler, making it easy to parse quickly.

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 two-parameter tool with strong annotations, the description is complete. It explains the input (any URL), the process (fetch and extract), the output format (standard llms.txt markdown), and realistic use cases. Given no output schema, the explicit note that the output is a 'single text blob' fully suffices for invocation.

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% with both `url` and `max_links` having descriptive text. The description mentions extracting 'key links' but does not add meaning beyond the schema's explanation of `max_links`. Since the schema already documents the parameters clearly, 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') with a clear scope ('for any URL'). It details the output format and use cases, making the tool's purpose unmistakable. Although it doesn't explicitly reference siblings, the unique deliverable (standard llms.txt markdown) inherently distinguishes it from the other listed tools.

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'), offering clear context for when to invoke the tool. However, it does not mention when not to use it or explicitly contrast with alternative tools, so it stops short of full exclusions.

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