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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, covering safety. The description adds process details: 'Fetches the page, extracts title/description/key links' and output format as a 'single text blob', enhancing transparency beyond annotations without 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 three sentences, each serving a purpose: what it does, how it does it, and when to use it. It is front-loaded with the primary function and avoids unnecessary redundancy, though the use-case list makes it slightly longer than the leanest examples.

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 only 2 parameters and no output schema, the description covers the necessary ground: process, output format ('ready to drop at site-root/llms.txt'), and use cases. It does not mention error handling or edge cases, but for a simple generation tool, this is adequate.

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%, with both 'url' and 'max_links' well-described (including default and max values). The description itself doesn't 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 a specific verb ('Generate') and resource ('llms.txt file'), and elaborates on the process: fetches the page, extracts key info, and emits standard markdown. This distinguishes it from sibling tools like 'ai_visibility_check' or 'scan_competitor_ai_presence', which have different purposes.

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 includes a 'Useful for' section with three concrete use cases (client sites, own project, competitor audit), giving clear context on when to use it. It does not explicitly mention alternatives or when-not-to-use, but the unique purpose renders that less critical.

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