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

Annotations already provide readOnly, idempotent, and non-destructive hints. The description adds behavioral details: fetches the page, extracts content, and emits standard markdown. This complements annotations without contradiction.

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 concise (three sentences plus a use-case line) with immediate purpose statement. No unnecessary words or repetitions; each sentence contributes value.

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?

Given the simple tool (2 params, no output schema), the description covers behavior (fetch, extract, output), use cases, and output format. It lacks error handling or rate limit info, but annotations cover safety. Adequate for the complexity.

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%, and both parameters (url, max_links) are described in the schema. The description does not add meaning beyond the schema; it only repeats the purpose indirectly. Baseline 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 it generates an llms.txt file for any URL, specifying output format (markdown), extracted elements (title, description, key links), and use cases. This distinguishes it from sibling tools like ai_visibility_check and scan_competitor_ai_presence by focusing on 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 lists three explicit use cases (indexing client sites, drafting own llms.txt, auditing competitors), giving clear context. However, it does not explicitly state when not to use this tool or mention specific alternatives among siblings.

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