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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavior context: it fetches the page, extracts specific elements, and returns a single text blob ready for deployment. This goes beyond annotations without contradicting them.

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 compact and well-structured. The first sentence states the core purpose and audience, the second explains the process and output, and the final clause lists concrete use cases. Every sentence earns its place; there is no redundant or vague content.

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 tool with only two parameters and no output schema, the description provides sufficient contextual coverage: it explains the input (URL), the optional parameter (max_links is implied by the schema but not described), the transformation process, and the exact output shape ('single text blob'). It also addresses practical use cases. The lack of an output schema is mitigated by the explicit description of the return format.

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% for both parameters, so the baseline is 3. The description reinforces the 'url' parameter by mentioning 'for any URL' but does not add new semantic details beyond the schema. The 'max_links' parameter is not referenced in the description, but the schema already explains it adequately.

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 specific function: generating an llms.txt file for a given URL. It names the exact output format (standard llms.txt markdown) and the process (fetch, extract, emit). This distinguishes it from all sibling tools, which cover different research or subscription tasks.

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 clear 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'). It does not explicitly mention alternatives or exclusions, but the application contexts are well-defined, satisfying the 'clear context' threshold.

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