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scan_site

Run a live AI-accessibility audit of a domain: robots.txt policy for every tracked AI crawler, live user-agent probes, JavaScript-free readability, structured data and llms.txt. Returns a score out of 100 with per-check detail.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesBare hostname, for example example.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of disclosure. It transparently explains that the tool performs live probes, checks robots.txt and llms.txt, and returns a score with per-check detail. It does not mention potential side effects or operational caveats, but the core behavior is well disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single information-dense sentence that front-loads the purpose and uses a compact list to convey scope, then states the return format. No filler or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one parameter and no output schema, the description is largely complete: it explains what checks are performed and what the return value looks like (score out of 100 with per-check detail). Minor gaps are the lack of alternative routing and any timing/side-effect context, but nothing critical is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the single parameter 'domain' is already well documented with an example. The tool description adds no additional parameter semantics beyond what the schema provides, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb ('Run') and resource ('a live AI-accessibility audit of a domain'), and enumerates concrete checks. It does not explicitly distinguish itself from sibling tools like site_report or crawl_preflight, but the scope is specific enough that an agent can infer its function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use it: when a live AI-accessibility audit of a domain is needed. However, it gives no explicit guidance on when to choose this tool over siblings such as site_report or crawl_preflight, and offers no exclusions or prerequisites.

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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