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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable process context: fetches the page, extracts title/description/key links, and emits the standard markdown format. This goes 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, front-loaded with the core purpose, and every sentence earns its place by adding process, output format, or use cases. No fluffy or redundant 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?

For a simple 2-parameter tool with strong annotations and no output schema, the description is complete: it explains purpose, process, output format, and use cases. There are no obvious gaps that would hinder an agent from selecting and invoking the tool correctly.

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 does not add parameter-specific details beyond what the schema already provides; it only loosely maps 'url' to 'any URL' and mentions key links. This does not elevate the score above baseline.

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 uses a specific verb 'Generate' and resource 'llms.txt file for any URL', clearly distinguishing the tool from siblings like ai_visibility_check. It also states the output format and use cases, making the purpose unmistakable.

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 lists explicit 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. However, it does not explicitly name alternatives or state when not to use this tool, so it lacks the full 'when/when-not' guidance required for a 5.

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