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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable process context: it fetches the page, extracts title/description/key links, and emits standard llms.txt markdown. It also notes the output format and drop location, going beyond what annotations alone provide. It does not mention failure modes, which keeps it from a 5.

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 and well-structured: two sentences covering purpose and process, followed by a focused 'Useful for' list. It is front-loaded with the primary purpose and contains no redundant or filler 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?

With no output schema, the description adequately conveys the return value (a 'single text blob' in standard llms.txt markdown). It covers purpose, process, output format, and use cases. It lacks minor prerequisites like URL accessibility or redirect behavior, but the description is otherwise complete for a tool of this simplicity.

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 the schema already documents both parameters clearly (url as 'Full URL of the site to summarize' and max_links with default/max). The description does not add parameter-specific meaning beyond what the schema provides, so the baseline of 3 applies.

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 function with a specific verb ('Generate'), resource ('llms.txt file'), and scope ('for any URL'). It also provides concrete use cases, which distinguishes it from siblings like ai_visibility_check or scan_competitor_ai_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 provides explicit use-case scenarios ('getting a client's site indexed', 'drafting llms.txt for your own project', 'auditing how an AI crawler would see a competitor'). It does not mention when not to use the tool or name alternative tools, but the context is clear enough for selection.

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