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

With no annotations, the description carries the full behavioral burden. It discloses that the tool reports what is present, missing, and how to fix it, which implies a read-only diagnostic, but it does not explicitly confirm no side effects, authentication requirements, rate limits, or network-fetch behavior.

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 front-loaded with the core purpose and then efficiently enumerates the checked artifacts. It uses two sentences with no redundant or wasted language, and every listed item is directly relevant to the tool's scope.

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?

No output schema exists, so the description must convey return behavior. It does so at a high level by stating that the tool returns what is there, what is missing, and how to fix it, though it does not describe the output structure or field-level detail.

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 both the url and fresh parameters are already documented in the schema. The description does not add parameter-specific meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 uses a specific verb and resource: it checks how well a website welcomes AI agents. It enumerates concrete checks such as robots.txt rules, llms.txt, sitemap, A2A agent card, MCP endpoint, and OpenAPI description, making the tool's scope immediately clear and distinct from the unrelated sibling tools.

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 purpose implies it should be used to audit a site's AI-agent readiness, and the schema's fresh parameter hints at rechecking after a fix. However, the description does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or routing guidance.

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