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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety/purity of the operation is established. The description adds valuable behavioral context: it fetches the page, extracts specific elements, and emits a single text blob ready for site-root deployment. It does not disclose edge cases (e.g., inaccessible URLs), but the annotation coverage lowers the burden.

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 tight sentences: purpose, process/output, and use cases. Every sentence earns its place, the core action is front-loaded, and the use-case list communicates practical value without drifting into irrelevant detail.

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?

This is a simple tool with only two parameters, full schema coverage, and annotations covering safety and idempotence. The description explicitly states the output format and where to place the result, compensating for the absence of an output schema. An agent has everything needed to invoke it correctly for typical use cases.

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%: url and max_links are both explained, including max_links' default (25) and maximum (50). The description adds no meaning beyond 'any URL' and does not mention max_links at all, so it stays at the baseline of 3 where the schema carries the parameter documentation.

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 opens with a specific verb and resource: 'Generate a production-ready llms.txt file for any URL.' It clearly details the process (fetches page, extracts title/description/key links) and the exact output (single text blob in standard llms.txt markdown), making it easy to distinguish from sibling tools like scan_competitor_ai_presence or ai_visibility_check.

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 'Useful for:' section provides concrete scenarios for when to invoke this tool: indexing a client's site, drafting for one's own project, or auditing how an AI crawler sees a competitor. It does not explicitly name alternative tools or describe when not to use it, but the context is sufficiently clear.

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