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Scan a site for AI-agent readiness

scan_site
Read-only

Checks a public website from the outside: which AI agents its robots.txt allows or blocks (training crawlers, AI search crawlers, user-triggered assistants), whether its content is readable without JavaScript, and whether it offers llms.txt and markdown. Returns a 0–100 score, a grade and prioritised findings with recommendations. Takes a few seconds.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "domain": "<domain>"
    },
    "name": "scan_site"
  }
}

Input Schema

NameRequiredDescriptionDefault
domainYesDomain or URL, e.g. example.com

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds genuinely new context beyond them: the scan is external/non-mutating in practice, it takes 'a few seconds' (latency expectation), and it returns a 0–100 score, a grade and prioritised findings. Missing only operational details like rate limits or failure modes for unreachable domains.

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

Conciseness4/5

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

Effectively one front-loaded sentence plus a return-value sentence and a latency note — no filler, and the most important claim (what is checked) comes first. The parenthetical list of agent categories is slightly heavy but earns its place by scoping the robots.txt check.

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 single-parameter read-only tool with no output schema, the description covers purpose, scope, expected return shape and latency. What an agent still lacks is error behaviour (invalid or unreachable domain) and any note on whether the scan is cached or rate-limited, but nothing essential to invoking it correctly is absent.

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?

There is a single required parameter with 100% schema description coverage ('Domain or URL, e.g. example.com'), so the schema already carries the semantics. The description adds only the implicit constraint that the site must be public and externally reachable, which is marginal value. Baseline 3 is appropriate.

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

Purpose5/5

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

States a specific verb and resource ('Checks a public website from the outside') and then enumerates exactly what is inspected: robots.txt agent permissions, JS-free readability, llms.txt and markdown availability. This is far more specific than the sibling names classify_request or list_known_agents, so an agent can distinguish them without opening any schema.

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 framing ('AI-agent readiness', 'public website', 'from the outside') strongly implies when this tool applies, but there is no explicit when-to-use / when-not-to-use statement and no named alternative. Guidance is inferred rather than stated, which is the definition of a minimum-viable 3.

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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