Check how machines read a site

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive, so safety is covered. The description adds real context beyond them: it is free, instant, requires no account, and does not invoke any model. It doesn't discuss rate limits or failure modes, but the behavioral picture is solid.

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?

Front-loaded with the value proposition and the routing hint is placed at the end where it belongs. The enumerations are dense but each clause adds distinct information; it is on the longer side but not padded.

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?

An output schema exists so return values need not be described, yet the description still summarizes them, and the sibling routing closes the main ambiguity. For a single-parameter read tool, an agent has everything needed to call it correctly.

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% and the single url parameter is already documented in the schema. The description reinforces that the target is a public website but adds no syntax or format detail beyond what the schema provides. Baseline 3 applies.

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?

States a specific verb+resource ('read a website the way an AI engine does') and enumerates exactly what it returns: crawler access from robots.txt, identity files, Organization schema, a score out of 100, and named fixes. It clearly distinguishes itself from the sibling analyze_site by contrast.

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 frames the use case ('before it ever answers about it') and names the alternative with the selecting condition: 'for whether the engines actually name the site, run analyze_site.' The 'No model is asked' line reinforces when this tool applies versus the model-based sibling.

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