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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds specific process details ('Fetches the page, extracts title/description/key links') and output format, providing transparency beyond the 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 three succinct sentences: first states purpose and output, second explains process, third lists use cases. It is front-loaded, every sentence adds value, and there is no redundancy.

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 two simple parameters, no output schema, and safe annotations, the description covers all necessary aspects: what it produces, how it works, and when to use it. The return format is described as 'single text blob' in standard markdown, which is sufficient given the tool's 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 coverage is 100% with descriptions for both parameters. The description echoes the schema with examples and default/max values, adding some clarity but not significant new meaning beyond what the schema already provides.

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 action ('Generate'), the resource ('a production-ready llms.txt file'), and the target audience ('AI crawlers'). It distinguishes itself from siblings by specifying the output format and use cases, making the tool's unique purpose unambiguous.

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 explicitly lists three use cases: indexing a client's site, drafting for one's own project, and auditing a competitor. However, it does not mention when to avoid using this tool or suggest sibling alternatives, leaving room for clearer differentiation.

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