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

The annotations already declare read-only, idempotent, and non-destructive behavior. The description adds process transparency by explaining the fetch-extract-emit workflow and the output format. This goes beyond annotations but doesn't disclose potential edge cases such as handling large pages or timeouts, though it's adequate.

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 reasonably concise, with each sentence contributing to understanding. The 'Useful for' section somewhat repeats the purpose but adds client-oriented usage examples. Overall, it's well-structured and not overly verbose.

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 tool with only two parameters and no output schema, the description is comprehensive: it explains the process, output format, and practical use cases. The note about the output being a text blob ready for site-root placement covers return value adequately.

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?

Both parameters (url and max_links) are fully described in the input schema with 100% coverage. The description does not add parameter-specific semantics beyond what the schema already provides, so a 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 clearly states the tool's function: generating a production-ready llms.txt file for any URL. It specifies the process (fetches, extracts, emits) and the output format, distinguishing it from sibling tools like ai_visibility_check which focus on checking AI visibility rather than generating files.

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 includes a 'Useful for' section listing concrete scenarios (getting client sites indexed, drafting for own project, auditing competitors). However, it does not explicitly mention when to avoid this tool or provide 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.