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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context: it performs a network fetch, extracts specific page elements, and emits a ready-to-drop text blob, which goes beyond the annotation safety profile without contradicting it.

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 primary action and audience, followed by process and use cases. Every sentence earns its place; no redundancy or filler.

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 two-parameter tool with strong annotations and no output schema, the description is comprehensive. It explains what happens (fetch, extract, emit), the output nature (single text blob), and where to use it (site-root/llms.txt), leaving no critical gaps for an agent to select and invoke correctly.

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% with both url and max_links having descriptions. The tool description adds no additional parameter-specific details beyond the overall purpose and output format, so the schema carries the parameter documentation burden as expected.

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 verb 'Generate' and the resource 'llms.txt file', with specific scope ('for any URL'). It details the process (fetches page, extracts title/description/key links) and output format (standard llms.txt markdown), distinguishing it from sibling tools like ai_visibility_check or scan_competitor_ai_presence.

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 'Useful for' context listing three concrete scenarios (client indexing, own project drafting, competitor auditing), giving clear when-to-use guidance. It does not mention alternatives or when-not-to-use, but the context is strong enough to guide tool selection.

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