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 process details (fetching the page, extracting metadata, emitting markdown) and output format (single text blob), which goes beyond the structured data and provides useful context for the agent.

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 concise (3 sentences) and front-loaded with the core purpose. Each sentence adds value: purpose, process, and use cases. No unnecessary fluff.

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 tool with good annotations and schema, the description is complete. It explains what it does, how it works, output format, and use cases. However, it doesn't mention error handling or edge cases (e.g., invalid URL, max_links bounds), which would make it a 5.

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% and both parameters have clear descriptions. The tool description does not add extra meaning beyond what the schema 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 purpose with a specific verb ('Generate') and resource ('a production-ready llms.txt file'). It explains the process (fetches page, extracts title/description/key links, emits standard format) and distinguishes itself from siblings by focusing on the llms.txt output file. The use cases (client indexing, own project, competitor auditing) further clarify its unique role.

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 clear context on when to use the tool via the 'Useful for' list, covering client work, personal projects, and competitor auditing. However, it does not explicitly state exclusions or name alternative sibling tools, 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.