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Check which AI crawlers a live site allows

check_site
Read-onlyIdempotent

Fetch a site's /robots.txt (http/https on the default port only; private, loopback and internal addresses are refused; up to 512,000 bytes; results cached for 5 minutes) and report, for one path, which registry AI crawlers are allowed or blocked, plus validation errors and warnings. Read-only: one GET of /robots.txt with a RobotsGate user-agent. Same engine as GET /api/check.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesSite URL or bare hostname, e.g. example.com. Only the scheme and host are used.
pathNoURL path to test, starting with "/" (default "/").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
pathNo
cacheNo
final_urlYes
redirectsNo
fetched_atNo
ai_crawlersNoPer-crawler results, or null when robots.txt was unreachable
http_statusYes
robots_foundYes
interpretationYes
personal_agentsNoObject, or null when robots.txt was unreachable

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already cover read-only/idempotent/open-world, and the description adds substantial extra context: a 512,000-byte fetch limit, a 5-minute result cache, refusal of private/loopback/internal addresses, default-port-only restriction, a single GET with a specific user-agent, and the fact that output includes validation errors and warnings. These are exactly the operational traits annotations cannot express.

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?

Front-loaded with the verb and the resource, followed by a constraints parenthetical and two short supporting sentences. Dense but every clause carries information; the long parenthetical is the only mild readability cost.

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

Completeness5/5

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 explained, and the description still covers scope, fetch limits, caching, security refusals and the engine identity. Nothing an agent needs to invoke this correctly appears to be missing.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3; the description goes slightly further by framing the result as being 'for one path', clarifying that the path parameter drives which allow/block determination is returned. It adds a little meaning over the schema but no format or syntax detail beyond it.

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?

States a specific verb+resource ('Fetch a site's /robots.txt ... report ... which registry AI crawlers are allowed or blocked'), which is concrete and agent-legible. It implicitly separates itself from validate_robots by emphasizing a live fetch, but never names a sibling or explicitly contrasts the check/validate/generate split among the four tools.

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?

Usage is implied rather than stated: the agent can infer this is the tool for inspecting a live site rather than generating or validating a local file. There is no explicit when-to-use/when-not guidance and no sibling alternative named, so selection among check_site, validate_robots and list_crawlers is left to inference.

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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