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

Description discloses the internal process (fetch page, extract title/description/links, emit markdown) and output format, adding value beyond annotations which already indicate safety and idempotency.

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, each earning its place: purpose, process, use cases. No redundant information, well-structured for quick comprehension.

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?

Adequately covers purpose, parameters, output format, and use cases. No gaps in required information given the simplicity and strong annotations.

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, but description adds practical details (URL example, default and max for max_links), enhancing understanding beyond schema alone.

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?

Description clearly states it generates an llms.txt file for a URL, specifying the verb ('generate'), resource ('llms.txt'), and distinguishing from sibling tools focused on AI 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?

Explicitly lists three use cases (client sites, own projects, competitor auditing), providing clear context for when to use. No explicit exclusion of alternatives, but sufficient for decision-making.

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