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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds the crucial behavioral trait that it makes an external network fetch ('Fetches the page'). It also discloses output format and that it emits a 'single text blob.' This adds context beyond annotations, such as network dependency and the standard output, though it does not detail failure modes. With annotations covering safety, this is above average.

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 four sentences, each earning its place: purpose, process, output, and use cases. It is front-loaded with the main verb and resource, and there is no filler or redundancy. Efficient and well-structured.

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 tool has no output schema, so the description compensates by explaining the return value ('llms.txt markdown format'). It covers the workflow and use cases. It lacks explicit error-handling or invalid-URL guidance, but for a simple fetch-and-format tool with good annotations, this is minor. Overall complete but with slight gaps.

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%, so the schema fully documents both parameters. The description does not add extra meaning about parameters beyond what the schema provides; it mentions 'extracts title/description/key links' but not parameter syntax or interplay. Baseline 3 is appropriate since the schema 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 uses a specific verb and resource: 'Generate a production-ready llms.txt file for any URL.' It clearly distinguishes from sibling tools like 'scan_competitor_ai_presence' by focusing on outputting the llms.txt format. It also explains the process (fetches page, extracts data) and the standard format, making the purpose unambiguous.

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, drafting for your own project, and auditing competitor AI crawler view. While it does not explicitly mention alternatives or when not to use, the use cases are clear enough to guide the agent. Sibling tools like 'scan_competitor_ai_presence' imply overlap, but no exclusion is stated. Clear context without exclusions merits a 4.

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