check_ai_visibility

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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it only states the tool's purpose. It does not reveal whether the check involves a live network fetch, what signals are analyzed (e.g., robots.txt, llms.txt, meta tags), or whether results are instantaneous or sampled. Nothing is disclosed that contradicts annotations because no annotations exist.

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 a single, front-loaded sentence with zero wasted words, stating the action before the object. It is efficient, though slightly terse — a phrase clarifying what 'discoverable' means could be added without hurting conciseness.

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?

This is a low-complexity tool with one required parameter and an output schema present, so the description does not need to describe return values and the input is fully documented in the schema. The main context gap is the absence of any explanation of what 'AI discoverability' is based on, but for such a simple tool the definition is nearly complete.

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% — the url parameter already documents its type and accepted formats ('example.com' or 'https://example.com'). The tool description adds no additional meaning about the parameter, so the baseline 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 states a clear action ('Check') and a specific resource/scope ('how discoverable a website is to AI assistants and AI search engines'), so an agent can tell what the tool does at a glance. There are no sibling tools to distinguish from, and the term 'discoverability' is left slightly undefined, so it falls just short of a 5.

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?

Because there are no sibling tools, there are no alternatives to exclude, but the description still provides only implied use context: if an agent wants to know a site's AI visibility, this is the tool. There is no explicit when-to-use guidance, exclusions, or prerequisites, making the usage guidance minimally adequate.

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