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

The description discloses the core behavior: it 'fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format'. This adds meaningful behavioral detail beyond the annotations, which already indicate read-only and idempotent behavior. It also specifies the output as a single text blob, setting expectations for the response format.

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: the first states the core function, the second explains the process, and the third gives concrete use cases. Every sentence adds value, with no redundant filler. It is front-loaded with the primary purpose and reads clearly.

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 simple two-parameter tool with no output schema, the description is complete: it explains what the tool does, how it works (fetch, extract, emit), what the output looks like (single text blob), and why it is useful. No critical information is missing 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?

Schema coverage is 100%, so the parameters 'url' and 'max_links' are already fully documented in the schema. The description mentions 'any URL' and the purpose, but doesn't add syntax or format details beyond the schema. Per the baseline rule for high schema coverage, a score of 3 is appropriate.

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 'Generate a production-ready llms.txt file for any URL', specifying an exact verb, resource, and purpose. It differentiates itself from siblings like ai_visibility_check and scan_competitor_ai_presence by focusing on the specific output artifact (llms.txt) rather than broader AI visibility scanning.

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 under 'Useful for:', including getting a client's site indexed, drafting for one's own project, or auditing a competitor. It lacks explicit 'when not to use' guidance or alternative tool references, but the clear use cases make the intended context obvious.

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