Check a site's AI search visibility: which AI crawlers (OAI-SearchBot, PerplexityBot, GPTBot, ClaudeBot and more) robots.txt allows, whether the homepage ships readable text without JavaScript, and whether an llms.txt exists.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | A site to check, e.g. example.com or https://example.com |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the three behaviors performed, including nuanced details like testing whether readable text ships without JavaScript, which goes beyond the schema. It does not mention network side effects, rate limits, or unreachable-site behavior, but the read-only 'check' semantics are reasonably transparent.
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 one front-loaded sentence that states the core purpose first, then uses a colon and a compact list for the concrete checks. Every phrase contributes; there is no redundancy, filler, or repetition of schema details.
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?
With a single simple parameter and no output schema, the description gives enough information to invoke the tool and understand the high-level return categories. A minor gap is that it does not describe the exact return shape or edge-case behavior (e.g., unreachable domains, missing robots.txt), but for a one-parameter check tool this is adequately 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?
The schema already fully documents the single url parameter with an example format ('example.com or https://example.com'), so the baseline is 3. The tool description adds little parameter-specific meaning beyond the schema, though the overall purpose reinforces that the URL identifies the site being checked.
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 specific verb ('Check'), a clear resource ('a site's AI search visibility'), and enumerates three concrete diagnostic outcomes: allowed AI crawlers, JS-free readable homepage text, and llms.txt existence. This clearly distinguishes it from the sibling generation/linting/validation 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 'check' framing and the enumerated checks make the intended use clear: use this tool when you want a broad visibility assessment of a site. It does not explicitly name sibling tools or state when not to use them, but the context is strong enough to route an agent correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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