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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses the operational pipeline: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format.' It also clarifies the output as a single text blob for site-root placement. No contradiction with annotations exists.

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, front-loaded with the primary action. Every sentence earns its place: main function, process, output, and use cases. No redundant or vague wording.

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 two-parameter tool with no output schema, the description covers purpose, process, output format, and use cases adequately. Minor omissions like URL accessibility or error handling are not critical given the tool's simplicity.

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 schema provides full descriptions for both parameters (100% coverage), so the baseline is 3. The description adds no extra parameter-specific detail beyond what the schema already states, though it does mention extracting title/description/key links, which indirectly relates to how the url is used.

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 exact action: 'Generate a production-ready llms.txt file for any URL' and explains its purpose for AI crawlers. This specific verb+resource clearly distinguishes it from sibling tools like ai_visibility_check, which focus on checking visibility rather than generating the file.

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 a clear 'Useful for:' section listing three specific use cases (client site indexing, self-project drafting, competitor auditing). It gives strong context on when to use the tool, though it does not explicitly mention alternatives or when not to use it.

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