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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds behavioral detail by stating it 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format' and that output is 'a single text blob ready to drop at site-root/llms.txt.' This provides process and output context beyond the annotations, without contradicting them.

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 three sentences, each earning its place: the first states the main purpose, the second explains the process, and the third lists use cases. It is front-loaded with the most critical information and contains no unnecessary detail.

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?

Given the tool's simplicity (two parameters, one required), comprehensive annotations, and no output schema, the description is complete. It explains the what, how, and when, and describes the output format ('single text blob') which is important in the absence of an output schema.

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?

The input schema provides full descriptions for both parameters (url and max_links), covering 100% of the parameter semantics. The description does not add additional meaning for these parameters, so a baseline score 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 clearly states the tool's function: 'Generate a production-ready llms.txt file for any URL' and explains the process of fetching, extracting, and emitting markdown. The verb 'generate' and resource 'llms.txt' are specific. However, it does not explicitly distinguish this tool from sibling tools like scan_competitor_ai_presence, even though it mentions a similar use case (auditing a competitor).

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 clear 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.' This gives strong context for when to use the tool. However, it does not mention alternatives or explicitly state when not to use it, so it falls short of full guideline coverage.

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