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Validate JSON-LD structured data (Schema.org)

validate_jsonld
Read-onlyIdempotent

Validate JSON-LD structured data against the Schema.org vocabulary. Accepts raw JSON-LD or an HTML snippet/page containing blocks (pass the text, not a URL: this tool never fetches anything). Returns valid true/false, error/warning/info counts, the Schema.org types found, and up to 25 issues with JSON paths, messages and did-you-mean suggestions. Read-only. Same engine as the RichProof JSON API (POST /api/validate).

Input Schema

NameRequiredDescriptionDefault
inputYesJSON-LD text (e.g. {"@context":"https://schema.org","@type":"Product","name":"…"}) or HTML containing <script type="application/ld+json"> blocks.
include_rawNoAlso return the full /api/validate JSON (all issues) in structuredContent.raw.

Output Schema

NameRequiredDescriptionDefault
rawNoFull /api/validate response (only when include_raw is true)
infosYes
typesNo
validYes
blocksNo
errorsYes
issuesYes
versionYes
warningsYes
issuesOmittedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already establish the read-only, idempotent, closed-world profile, and the description reinforces it ('Read-only') while adding genuinely new behavioral facts: no network fetching, a hard cap of 25 returned issues, did-you-mean suggestions, and the exact backend engine/endpoint. It does not discuss size limits or failure behavior for malformed input, so it stops short of full disclosure.

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-loads the action and input modes, then the return shape, then the read-only/engine provenance note. Every sentence carries information, though the closing 'Same engine as the RichProof JSON API (POST /api/validate)' is more implementation trivia than a decision aid for the agent.

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, the description needn't enumerate return fields, yet it still summarizes the response (valid flag, counts, types, issue list) so the agent knows what to expect. Input modes, non-fetching behavior, and the read-only guarantee cover everything needed to invoke it correctly.

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 both parameters are already documented in structured form, which sets the baseline at 3. The description restates the input modes but adds no new syntax, format, or constraint detail beyond the schema (e.g. the 60000 maxLength is never mentioned).

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?

States a specific verb+resource ('Validate JSON-LD structured data against the Schema.org vocabulary') and immediately bounds the input domain (raw JSON-LD or HTML with ld+json script blocks). An agent knows exactly what this tool does and what it accepts without opening the schema.

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?

Explicitly tells the caller to pass text rather than a URL and that the tool never fetches anything, which is the main misuse risk for a validation tool. There are no sibling tools to compare against, so no alternative routing guidance is needed, but there is also no explicit 'when not to use' beyond the URL exclusion.

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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