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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format,' and clarifies that output is a 'single text blob ready to drop at site-root/llms.txt.' This extends beyond the structured annotations.

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 well-structured: it opens with the core purpose, then the process, then a short bullet-like 'Useful for' list. It is concise and front-loaded, though the 'Useful for' list adds a bit of length that is slightly redundant with the first sentence but still provides useful context. Overall, every sentence contributes to understanding.

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?

The description is complete for a simple tool with two parameters and no output schema. It explains the input ('any URL'), the process (fetch page, extract title/description/key links), the output format (standard llms.txt markdown, single text blob), and the intended use cases. An agent has enough information to select and invoke the tool correctly.

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 for both parameters (url and max_links), so the schema already explains their meaning. The description does not add any parameter-specific details beyond the schema, which is acceptable given the high coverage. It neither clarifies default behavior (e.g., max_links default 25) nor adds examples beyond the schema.

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: 'Generate a production-ready llms.txt file for any URL' with a specific output format ('standard llms.txt markdown'). It names the target audience (AI crawlers like ChatGPT, Claude, Perplexity) and distinguishes itself from sibling tools by focusing specifically on generating llms.txt rather than scanning visibility or researching entities.

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 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.' It gives clear context for when to use the tool, though it does not mention when not to use it or explicitly contrast with alternatives like ai_visibility_check.

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