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

The description discloses that the tool 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format', which adds behavioral context beyond the readOnlyHint, openWorldHint, and idempotentHint annotations. It explains the fetch-and-extract process and the output format. No contradictions with 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 a single sentence followed by a concise 'Useful for' list. It front-loads the core purpose and maintains relevance throughout. The list of use cases adds practical value but makes the description slightly longer than strictly necessary. Still, it is well-structured and efficient.

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?

For a tool with only 2 parameters and no output schema, the description provides sufficient context: it explains the process, the output format ('standard llms.txt markdown format', 'single text blob'), and typical use cases. It does not mention edge cases or failure behavior, but given the annotations and simplicity, the description is complete enough for an agent to select and invoke the tool effectively.

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 already provides 100% coverage with detailed descriptions for both 'url' and 'max_links'. The tool description does not add additional parameter-level details beyond what the schema already states. It mentions 'any URL' but that is just a generic reference. Baseline 3 is appropriate given the schema already does the heavy lifting.

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 action: 'Generate a production-ready llms.txt file for any URL'. It specifies the resource (llms.txt), the target (any URL), and the purpose (AI crawlers can index the site cleanly). This distinguishes it from sibling tools like ai_visibility_check or scan_competitor_ai_presence, which focus on visibility analysis rather than file generation.

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'. This gives clear context for when to use the tool. However, it does not mention when not to use it or explicitly reference alternative tools, so it falls short of a perfect score.

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