Validate JSON-LD

Overview

You send a JSON-LD document and we confirm it parses as JSON-LD — duplicate keys and all — then, if you name a profile, check the node against a pinned copy of the schema.org rules for an Article, a Product, or an Organization, or against property rules you supply yourself. You get back the types we saw, the contexts the document names, and a finding for every required property that is missing and every recommended one worth adding. A remote @context is noted but never fetched, so this is a completeness check rather than semantic reasoning.

A structured-data check that reaches out to schema.org to do its job is a check that gives you a different answer when the network has a bad day.

When to use it

Scope

Non-goals

• Does not fetch a remote @context, and refuses to pretend otherwise
• Does not expand, flatten, or reason over the graph the way a JSON-LD processor would
• Does not fetch a page or pull the markup out of HTML for you
• Does not check every schema.org type — only the three pinned profiles and your own rules

Properties

Capabilities

Cost & billing

Flat rate per invocation

File handling

How we handle your data

Input schema

Output schema

API contract

curl -sS -X POST "$BASE/v1/execute" -H "Authorization: Bearer $KEY" -H 'Content-Type: application/json' -d '{"skillKey":"web.validate_json_ld","input":{"document":{"@type":"Organization","name":"Acme"}}}'

import { Squillify } from "@squillify/sdk";

const sq = new Squillify({ apiKey: process.env.SQUILLIFY_API_KEY });

const { output } = await sq.execute("web.validate_json_ld", {"document":{"name":"Acme","@type":"Organization","@context":"https://schema.org"},"profile":"schema_org_organization"});

Errors

Other limits

Limitations

• Does not fetch a remote @context, and refuses to pretend otherwise
• Does not expand, flatten, or reason over the graph the way a JSON-LD processor would
• Does not fetch a page or pull the markup out of HTML for you
• Does not check every schema.org type — only the three pinned profiles and your own rules
• Resolving or expanding a remote @context
• Reasoning about what the data means rather than what it contains

How to call

POST /v1/execute (requires authentication)

{
  "skillKey": "web.validate_json_ld",
  "input": {
    "document": {
      "name": "Acme",
      "@type": "Organization",
      "@context": "https://schema.org"
    },
    "profile": "schema_org_organization"
  }
}

Examples

{
  "document": {
    "name": "Acme",
    "@type": "Organization",
    "@context": "https://schema.org"
  },
  "profile": "schema_org_organization"
}

{
  "findings": [
    {
      "details": {},
      "path": "/url",
      "code": "PROFILE_RECOMMENDED_MISSING",
      "message": "missing recommended property: url",
      "severity": "warning"
    },
    {
      "details": {},
      "path": "/logo",
      "code": "PROFILE_RECOMMENDED_MISSING",
      "message": "missing recommended property: logo",
      "severity": "warning"
    }
  ],
  "nodeTypes": [
    "Organization"
  ],
  "_meta": {
    "nodeCount": 1,
    "profile": "schema_org_organization",
    "vocabularyProfile": "schema-org-pinned-1"
  },
  "profileValid": true,
  "valid": true,
  "contextIdentifiers": [
    "https://schema.org"
  ],
  "warnings": [
    "Remote @context recognized but not resolved: https://schema.org"
  ]
}

{
  "document": {
    "@type": "Thing",
    "name": "Example"
  },
  "profile": "syntax_only"
}

{
  "findings": [],
  "nodeTypes": [
    "Thing"
  ],
  "_meta": {
    "nodeCount": 1,
    "profile": "syntax_only",
    "vocabularyProfile": "schema-org-pinned-1"
  },
  "profileValid": true,
  "valid": true,
  "contextIdentifiers": [],
  "warnings": []
}

Recommended use cases

• Catch missing schema.org properties before a page goes live
• Hold structured data to your own house rules as part of a build
• Check what web.extract_json_ld pulled out of a page

Avoid for

• Resolving or expanding a remote @context
• Reasoning about what the data means rather than what it contains

Related skills

Composable with

Safety & privacy

• Runs without calling any external service.
• Your payloads are never stored permanently.
• Telemetry captures metadata only — never your payload contents.
• We never train models on your payloads.
• No human reviews your payloads.

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