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

Annotations already declare readOnly, openWorld, and idempotent hints, and the description complements them by detailing the process: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format.' This adds behavioral context (network fetch, extraction logic) without contradicting any annotations, though it doesn't disclose rate limits or failure modes.

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 tightly structured: a direct opening sentence, a process sentence, an output sentence, and a concise 'Useful for' list. Every sentence contributes meaning, and the text is front-loaded with the primary action. No redundant or filler content.

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 (2 params, no output schema) and rich annotations, the description adequately explains what it does, the output format, and use cases. It is nearly complete, though it could mention that it only produces the standard format and not customized variants, but that is a minor gap.

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 marginal context by mentioning 'key links' which relates to max_links, but it does not elaborate on parameter syntax or defaults beyond what the schema already provides. Thus, it meets the baseline without significant extra value.

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 with a specific verb+resource: 'Generate a production-ready llms.txt file for any URL.' It also differentiates from siblings by focusing on file generation rather than mere auditing, and the use cases mention competitor auditing which ties to sibling tools but the primary purpose is distinct.

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 contexts for use: '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.' However, it does not explicitly exclude alternatives or mention when to choose a different tool (e.g., ai_visibility_check) for deeper analysis, so it stops short of full guidance.

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