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, covering safety. The description adds valuable context beyond annotations: it fetches the page, extracts title/description/key links, and emits a single text blob ready to drop at site-root/llms.txt. This clarifies the operation's nature without contradicting 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 two sentences plus a 'Useful for' list. It is front-loaded with the main purpose and outcome, and every sentence adds value: what it does, how it works, output format, and use cases. 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?

Despite having no output schema, the description explicitly states the output is 'a single text blob ready to drop at site-root/llms.txt'. Combined with clear process description, parameter schema coverage, and annotations, the description is fully complete for the tool's moderate 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 description coverage is 100%, so the description does not need to add much parameter-level detail. The description mentions 'URL' and 'max_links' implicitly through the fetch/extract behavior, but the schema already handles parameter documentation. Baseline 3 is appropriate given high schema coverage.

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 a specific verb ('Generate'), resource ('llms.txt file'), and scope ('for any URL'), and explains the core actions (fetch, extract, emit standard format). It distinguishes itself from sibling tools like ai_visibility_check and scan_competitor_ai_presence by focusing on the generation of the llms.txt artifact rather than analysis.

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'), giving clear context for when to use the tool. However, it does not explicitly mention alternatives or when not to use it, so it falls just short of a 5.

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