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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so safety is known. The description adds process details (fetches the page, extracts title/description/key links, emits standard markdown) and output format (single text blob), which go beyond the 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 three sentences, front-loaded with the core action, followed by process and use cases. Every sentence earns its place, with no redundant or vague phrasing.

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 two well-documented params and strong annotations, the description covers purpose, process, output, and use cases. It could mention limitations (e.g., public URLs only) or error handling, but these are not essential given the simplicity and the openWorldHint annotation.

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 parameters are well-documented. The description reinforces that the tool works for 'any URL' and mentions extraction of title/description/key links, but it does not add significant new meaning beyond what the schema already provides.

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 with a specific verb ('Generate') and resource ('llms.txt file for any URL'), and explicitly mentions AI crawlers as the audience. It differentiates itself from sibling tools like scan_competitor_ai_presence by focusing on generating a standard file format with concrete use cases.

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 spells out when to use this tool: getting a client's site indexed, drafting llms.txt for a project, or auditing a competitor's AI visibility. It does not explicitly mention exclusions or alternatives, but the guidance is clear and actionable.

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