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

Annotations already indicate readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable context beyond that: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format'. It also clarifies the output as 'a single text blob ready to drop at site-root/llms.txt'. This gives the agent a clear model of the tool's behavior 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 three sentences, with the core purpose and process in the first sentence, output format in the second, and use cases in the third. Every sentence adds meaningful information with no redundancy. It is front-loaded and well-structured.

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 relatively simple tool with no output schema, the description covers the essential aspects: what it does, how it works (fetch, extract, emit), the output format, and practical applications. Combined with complete schema annotations and parameter descriptions, the context is fully adequate.

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?

The input schema already provides 100% coverage for both parameters (url and max_links) with descriptive text. The description adds no additional parameter-specific meaning beyond what the schema gives, meeting the baseline of 3. It does not enhance or clarify parameter usage further.

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 tool's purpose: 'Generate a production-ready llms.txt file for any URL'. It specifies the verb (generate), resource (llms.txt file), and differentiates from siblings by mentioning the exact output and use cases like AI crawler indexing and competitor auditing. This is a specific, non-tautological description.

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 use cases: 'getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor'. This gives clear context for when to use the tool, but it does not mention exclusions or alternative tools like 'ai_visibility_check' or 'scan_competitor_ai_presence'. Therefore, it falls short of a 5 but exceeds a 3.

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