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Website Auditor MCP

Generate JSON-LD schema

generate_schema
Read-only

Generate JSON-LD structured data drafts for a website so search engines and AI assistants understand its content; replace placeholder names before embedding.

Instructions

Generate structured data (JSON-LD schema) tailored to a website, to improve how AI assistants and search engines understand it. Use this when someone asks for "schema," "structured data," "JSON-LD," or wants the actual markup to implement a recommendation. Returns a DRAFT, not finished markup: every name field arrives as a placeholder — "Your Business Name" on the business types, and on a Product the product's own name and brand as "Your Product Name" and "Brand Name" — that the owner must replace with real names confirmed with them, never guessed from the domain or copied from an audit. placement_notes says what to replace first, then where to embed the finished snippet, so relay the whole ask and do not tell the user to paste the draft as returned. Requires a Website Auditor subscription ($10/month; eligible new customers get a 7-day free trial — payment method required, no charge until the trial ends) — if the user doesn't have one, call get_sample_audit first to show them the exact output format, free and with no API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNoSchema type; "auto" (also the default when omitted) does not detect anything — it returns an Organization draft.
domainYesThe website domain, e.g. "example.com".

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonldNoThe JSON-LD draft (object or array). NOT ready to paste: every name field arrives as a placeholder — "Your Business Name" on the business types, and on a Product the product's own name and brand as "Your Product Name" and "Brand Name" — that the owner must replace with real names confirmed with them, never guessed from the domain or copied from an audit.
placement_notesYesWhat to replace in the draft first — each name placeholder, confirmed with the owner — then where to embed the finished snippet, e.g. "in the <head> of every page". Relay the whole string, in that order: the replacement ask comes before the placement.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.0.25
    • changedInput schema / properties / type / description
      Previous value: -"Schema type, or auto-detect."New value: +"Schema type; \"auto\" (also the default when omitted) does not detect anything — it returns an Organization draft."
    • changedOutput schema / properties / jsonld / description
      Previous value: -"The JSON-LD document, ready to paste into the site."New value: +"The JSON-LD draft (object or array). NOT ready to paste: every name field arrives as a placeholder — \"Your Business Name\" on the business types, and on a Product the product's own name and brand as \"Your Product Name\" and \"Brand Name\" — that the owner must replace with real names confirmed with them, never guessed from the domain or copied from an audit."
    • changedOutput schema / properties / placement_notes / description
      Previous value: -"Where to put the snippet, e.g. \"in the <head> of every page\"."New value: +"What to replace in the draft first — each name placeholder, confirmed with the owner — then where to embed the finished snippet, e.g. \"in the <head> of every page\". Relay the whole string, in that order: the replacement ask comes before the placement."
  2. Changed1 schema field changedv1.0.23
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": false,
      +  "properties": {
      +    "jsonld": {
      +      "description": "The JSON-LD document, ready to paste into the site."
      +    },
      +    "placement_notes": {
      +      "description": "Where to put the snippet, e.g. \"in the <head> of every page\".",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "placement_notes"
      +  ],
      +  "type": "object"
      +}
  3. First observedv1.0.6

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare it is a non-destructive read, but the description goes far beyond: it discloses that output is a DRAFT with placeholder name fields, that names must never be guessed from the domain or copied from an audit, what placement_notes contains, how to relay it to the user, and the $10/month subscription with 7-day trial requirement. That is unusually rich behavioral context for a readOnly tool.

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 paragraph is front-loaded with purpose, then triggers, then behavioral caveats, and nearly every sentence carries actionable content. It is dense and long, but the length is largely justified by the draft/placeholder and subscription prerequisites rather than padding.

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?

With an output schema present and full parameter coverage, the description only needs to supply what structured fields cannot: the subscription prerequisite, the draft-with-placeholders caveat, and the fallback tool. All of these are present, so an agent has everything needed to call and correctly relay 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?

Schema description coverage is 100%, so the schema already documents both `domain` and the `type` enum including the "auto" default behavior. The description adds no further syntax, format, or selection guidance for these parameters, so the baseline 3 applies.

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?

The first sentence names a specific verb and artifact — generate JSON-LD structured data tailored to a website — plus the outcome it serves. It is clearly distinguishable from the audit/report siblings because it produces markup rather than analysis.

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

Usage Guidelines5/5

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

It gives explicit trigger phrases ("schema," "structured data," "JSON-LD") and states the alternative path when prerequisites are unmet: if the user lacks the required subscription, call get_sample_audit first. This is exactly the when/when-not/alternative guidance the dimension asks for.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.