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

Annotations already confirm read-only/idempotent behavior. The description adds value by explaining the tool fetches the page, extracts key data, and outputs a markdown blob, plus that it's 'production-ready'. This goes beyond the safety profile and gives meaningful operational context.

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 composed of three focused sentences: what it does, what the output is, and when to use it. It is front-loaded with the core function and avoids unnecessary filler, though the 'useful for' list could be slightly trimmed without loss.

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 relatively simple tool with strong annotations and no output schema, the description covers the input (URL), the process (fetch/extract), the output format (text blob at site-root/llms.txt), and typical use cases. It lacks edge-case or limitation details, but is sufficiently complete for the tool's complexity.

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 full descriptions for both parameters (url with example, max_links with default/maximum). The description does not add further parameter-specific details, but since schema coverage is 100%, 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 identifies the tool's purpose: generating an llms.txt file for a URL. It specifies the verb (generate), resource (llms.txt), and the process (fetches page, extracts title/description/key links). It does not explicitly compare against sibling tools, but the function is distinct and 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 concrete 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'), giving clear context for when to use it. It does not mention exclusions or alternatives, but the guidance is actionable.

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