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

Even though annotations already declare readOnlyHint=true and idempotentHint=true, the description adds valuable behavioral context by explaining the underlying process: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format.' This reveals how the tool operates beyond the annotations, and there is no contradiction.

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 structured into four sentences: main action, process, output format, and use cases. It is slightly verbose but every sentence earns its place, providing essential information without redundancy. It is appropriately front-loaded with the core purpose in the first sentence.

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?

Despite having no output schema, the description explicitly states the output ('a single text blob ready to drop at site-root/llms.txt') and covers the input (URL), process, and use cases. The tool is simple (2 parameters, no nested objects), and the description gives complete context for an agent to decide when and how to invoke it.

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 has 100% description coverage, with clear descriptions for 'url' and 'max_links'. The tool description does not add parameter-specific meaning beyond what the schema already provides, so the baseline score of 3 is appropriate. The description's process explanation ('extracts title/description/key links') implicitly relates to parameters but not directly.

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 states a specific verb ('Generate'), a clear resource ('llms.txt file'), and the target ('any URL'), making the tool's purpose unambiguous. It also distinguishes from sibling tools like 'scan_competitor_ai_presence' by focusing on generating the file itself rather than just auditing presence.

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 explicitly lists use cases ('getting a client's site indexed by AI', 'drafting llms.txt for your own project', 'auditing how an AI crawler would see a competitor'), providing clear context for when to use the tool. It does not mention exclusions or alternatives, but the use cases are specific enough to differentiate from siblings.

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