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Preferly

by ai.preferly
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Check business structured data

check_business_schema
Read-onlyIdempotent

Use this when the user asks whether a website's structured data (schema.org JSON-LD) describes the business correctly. It reads the homepage's JSON-LD and reports the business type it found (Organization, LocalBusiness or a subtype), which business fields are present, missing or look off (name, url, phone, address, hours and more), and where the structured data and the page disagree. Input: one public website. Reads robots.txt, the homepage and /llms.txt as PreferlyBot; changes nothing.

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": {
      "website": "<website>"
    },
    "name": "check_business_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
websiteYesThe public website to check, like example.com or https://www.example.com. One site per call.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety bar is low; the description still adds real value by naming the exact resources fetched (robots.txt, homepage, /llms.txt), the crawler identity (PreferlyBot), and confirming nothing changes. With no output schema, describing what the report contains is also useful behavioral context.

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?

The description is front-loaded with the usage trigger, then the behavior, then the input, and every sentence carries information. The final 'Input: one public website' line is mildly redundant with the schema but is short enough not to hurt.

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?

For a single-parameter read-only audit tool with no output schema, the definition covers the trigger, the exact sources read, the crawler identity, and the shape of the report, so an agent has everything needed to call it and interpret the result.

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 only one parameter and schema coverage is 100%, with the schema already documenting format examples and 'one site per call'. The description's 'Input: one public website' adds the public-only constraint but otherwise restates the schema, so it sits at the baseline for a fully documented single parameter.

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 states a specific verb and resource: it reads a homepage's schema.org JSON-LD and reports the business type found, which fields are present/missing/suspect, and where markup disagrees with the page. That is far more precise than a restatement of the name, though it never explicitly contrasts itself with the close sibling check_business_info.

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

Usage Guidelines4/5

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

The opening clause gives a clear triggering condition ('when the user asks whether a website's structured data ... describes the business correctly'), which is enough to route an agent. It stops short of naming alternatives or stating when-not to use it, so an agent must infer the boundary with check_business_info on its own.

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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