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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is clear. The description adds process transparency by explaining it 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format'. This goes beyond the annotations and helps the agent understand the tool's behavior.

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 core action, and includes a 'Useful for' list that is scannable. Every sentence adds value: purpose, process/output, and use cases. No filler or redundancy.

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 2 parameters, no output schema, and strong annotations, the description is complete. It covers the workflow, output format, and practical use cases. The absence of error-handling details is acceptable given the tool's simplicity and the fact that annotations cover the read-only, idempotent nature.

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 mentions the URL parameter implicitly ('for any URL') and refers to 'key links' (which maps to max_links conceptually), but it doesn't add detail about parameter types or defaults beyond what the schema already provides. It neither enhances nor harms parameter understanding.

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'. It specifies the exact output (a text blob for site-root/llms.txt) and differentiates from sibling tools by focusing on generation rather than scanning or checking AI presence. The verb 'Generate' plus the resource 'llms.txt file' makes the purpose unambiguous.

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 ('Useful for: 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') and implies when to use it. However, it does not explicitly mention alternatives or when not to use it, so it lacks the 'when-not' guidance that would earn a 5.

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