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

Annotations declare readOnlyHint, idempotentHint, and non-destructive behavior, covering the safety profile. The description adds behavioral context: it fetches the page, extracts title/description/key links, and emits standard markdown, plus clarifies output is a text blob. This is valuable but doesn't mention potential network errors or rate limits.

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?

Three sentences with a clear structure: main action, process, output, and use cases. Every sentence contributes, with no fluff or unnecessary details.

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 2-parameter read-only tool with no output schema, the description fully covers the output format ('single text blob ready to drop at site-root/llms.txt'), the process, and the use cases. It lacks only minor edge-case details, which are not essential for a tool of this simplicity.

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 baseline is 3. The description mentions extracting title/description/key links, which indirectly relates to max_links, but it doesn't add semantics beyond what the schema's own parameter descriptions already provide.

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 a production-ready llms.txt file for any URL, using a specific verb ('Generate') and resource ('llms.txt'). It distinguishes from sibling tools by emphasizing the llms.txt output format, which no other tool mentions.

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?

It provides explicit use cases (getting a client's site indexed, drafting for your own project, auditing a competitor) and clarifies it works for 'any URL'. However, it does not mention when to prefer sibling tools like scan_competitor_ai_presence, so it lacks explicit exclusions or alternatives.

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