Skip to main content
Glama

schema_validate

Fetch any public URL to validate its JSON-LD structured data schemas, check required fields per schema type, and suggest missing schemas.

Instructions

Fetch a URL and validate its JSON-LD structured data schemas.

Detects all blocks, checks required fields per schema type, and suggests missing schemas based on URL patterns. Does not require authentication -- works on any public URL.

Returns detected schemas, validation results per schema, and recommendations. The valid flag and verdict check only this tool's local required-field presence rules, not full Schema.org validity or Google rich-result eligibility. Recommended properties are reported separately and do not affect validity. Verdicts: healthy (all schemas valid) | missing_schemas (none found) | invalid_schemas (found but at least one has missing required fields) | fetch_error (URL not reachable).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses the auth-free behavior, the exact meaning of the 'valid' flag, the limitation that it checks only local required-field rules and not full Schema.org or rich-result eligibility, that recommended properties do not affect validity, and it enumerates all four verdict values.

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-loaded with the core action, then behavioral caveats, then verdict enumeration. The verdict list is a bit sprawling but each item earns its place by removing ambiguity. Generally tight.

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?

An output schema exists so return structure needn't be restated, yet the description still clarifies the semantics of the valid flag, verdict, and recommendations — precisely the interpretive context an agent needs. Nothing material for correct invocation is missing.

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 0% on the single url param. The description implies format ('any public URL') but adds no syntax or format detail beyond the obvious string and URL semantics. Minimal but adequate for one self-evident parameter.

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: 'Fetch a URL and validate its JSON-LD structured data schemas.' It further specifies exactly what is detected (<script type="application/ld+json"> blocks) and what is suggested, distinguishing it clearly from the sibling schema_generate.

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?

Provides clear usage context ('Does not require authentication -- works on any public URL') and implicitly contrasts with schema_generate by being a validation rather than generation tool. However, it never explicitly names an alternative or states when-not to use it, so it stops short of full routing guidance.

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