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

The description explains the mechanism ('fetches the page, extracts title/description/key links, emits the standard llms.txt markdown format') and output ('single text blob ready to drop'). This goes beyond the annotations (readOnly, openWorld, idempotent, non-destructive) by adding functional detail without contradicting them. It doesn't discuss potential failures or network dependencies, but the added context is strong.

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 the core purpose upfront, followed by behavior and use cases. No wasted words; each sentence adds value. The structure is front-loaded and easy to scan.

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 two-parameter tool with no output schema, the description fully covers purpose, behavior, output format, and use cases. It even specifies the output placement ('site-root/llms.txt'), which is a useful contextual detail. The description is complete enough for an agent to select and invoke the tool 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 covers both parameters (url, max_links) with clear descriptions, and schema coverage is 100%, so baseline is 3. The description only references URL implicitly ('any URL') and doesn't add new information about max_links or parameter behavior, so it stays at baseline.

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 states a clear verb ('Generate') and resource ('llms.txt file'), specifies the target ('any URL') and the end result ('AI crawlers can index the site cleanly'). It distinguishes itself from sibling tools like scan_competitor_ai_presence by focusing on file generation rather than scanning or visibility checks.

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?

Provides explicit use cases ('getting a client's site indexed by AI', 'drafting llms.txt for your own project', 'auditing how an AI crawler would see a competitor') which frame when to use it. However, it doesn't name alternative tools or explicitly state when not to use it.

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