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

Annotations already indicate a safe, idempotent, read-only operation. The description adds valuable behavioral details: it fetches the page, extracts specific elements (title, description, key links), and outputs a standard markdown format. This goes beyond the annotations and helps the agent understand the exact process and output.

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 long, front-loaded with the core action, and every sentence adds value without redundancy. It is efficiently structured and easy to parse.

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 parameters, no output schema, rich annotations), the description covers all necessary aspects: purpose, behavior, usage examples, and output format. There are no gaps in understanding how to use the tool or what it produces.

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 input schema already provides descriptive text for both parameters (url and max_links), including default and max for max_links. The description does not add any new semantic information beyond what the schema provides, so a baseline score 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 verb 'generate', the resource 'llms.txt file', and the target 'any URL'. It distinguishes from sibling tools by specifying the exact output format and use case, which is unique among the listed siblings.

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 three concrete use cases (client site indexing, own project drafting, competitor auditing), which clearly indicate when to use the tool. However, it does not explicitly state when not to use it or mention alternative tools.

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