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by io.github.andacuzel
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Generate JSON-LD for a site

generate_schema
Read-only

Fetches a domain’s homepage for its real title, meta description and declared language, then returns ready-to-paste JSON-LD structured data of the requested type. Fields the scan cannot know — a FAQ’s actual questions, a product’s real price — come back as clearly bracketed placeholders, never invented values.

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>",
      "type": "<type>"
    },
    "name": "generate_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault
typeYes"organization" returns Organization + WebSite schema as an @graph; the others (faqpage, article, product, localbusiness) each return one schema of that @type.
domainYesA bare domain, e.g. "example.com".

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/openWorld/idempotent=false, and the description adds real value on top: it explains that a live homepage fetch happens and that unknowable fields come back as bracketed placeholders rather than fabricated values, which is important for an agent interpreting the output. It stops short of covering failure modes (unreachable domain) or caching, so not a 5.

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?

Two sentences, front-loaded with the action and result, with the caveat about placeholders placed exactly where it matters. No filler.

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?

With no output schema, the description carries the burden of describing the return value, and it does so adequately (ready-to-paste JSON-LD, bracketed placeholders, @graph nuance left to the schema). Missing only error/edge behavior for domains that fail to fetch.

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 coverage is 100% and the type enum is already fully documented in the schema, so the description's contribution is limited to reinforcing that output varies by requested type. The placeholder examples (FAQ questions, product price) hint at what each type yields but do not add syntax or constraints beyond the schema.

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?

Specific verb chain (fetches the homepage, returns JSON-LD) with the exact resource and output form. It is clearly distinct from siblings like scan_site, generate_robots_txt, and generate_llms_txt, which produce different artifacts.

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 use case is implied — you call this when you need paste-ready structured data for a site — but there is no explicit when-to-use, no mention of when scan_site or compare_sites would be the better choice, and no stated prerequisites beyond having a bare domain.

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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