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Schema.gov.it MCP Server

Schema.gov.it MCP Server

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by italia
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TypeScript
Hybrid

Check Quality

check_quality
Read-onlyIdempotent

Detect missing labels or descriptions in ontology resources, with optional filtering to exclude imported resources for accurate quality checks.

Instructions

Verify quality issues like missing labels or descriptions.

Args:

  • limit: Maximum results to return (default: 50)

  • ontologyUri: (optional) Restrict check to resources whose URI starts with this ontology namespace. Use this to avoid false positives from resources imported from other ontologies (e.g. core ontology classes referenced as range/domain in the target ontology). Mirrors the URI prefix heuristic used by explore_ontology.

Returns:

  • List of resources missing rdfs:label or skos:prefLabel (checked in both default graph and all named graphs)

When to use ontologyUri:

  • Pass the ontology URI (from list_ontologies) when checking a specific ontology to exclude imported resources. Resources imported from another ontology (e.g. a core class used as range) are NOT a quality issue of the importing ontology — they are defined, with their labels, in the originating ontology.

Note: Checks owl:Class, owl:ObjectProperty, owl:DatatypeProperty, and skos:Concept. Label lookup spans both the default graph and all named graphs to avoid false positives caused by label triples residing in a named graph different from where the type assertion was found.

False positive filtering: Resources that have only a bare type declaration (a owl:Class with no other properties) are automatically excluded. These are typically import stubs — classes or properties referenced from another module but never developed locally. Only resources with at least one non-type triple are flagged, ensuring the report covers entities that are being actively developed but are missing editorial metadata.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "check_quality"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
ontologyUriNoRestrict check to resources whose URI starts with this ontology namespace (use the URI from list_ontologies). Excludes resources imported from other ontologies.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations indicate read-only, open-world, idempotent, non-destructive behavior. The description adds significant detail: specific resource types checked, label lookup across all graphs, and false positive filtering of import stubs, providing behavioral depth beyond annotations without contradiction.

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?

Well-structured with sections for args, returns, when-to-use, notes, and false positive filtering. Front-loaded with purpose. While slightly lengthy, every section adds value with minimal redundancy.

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?

For a quality check tool with no output schema, the description comprehensively covers what is checked, how parameters affect results, false positive handling, and return format. It is complete enough for an AI agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50% (ontologyUri described, limit not). The description adds: default for limit (50), detailed usage of ontologyUri to avoid false positives, and its relationship to explore_ontology. This meaningfully supplements 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?

The description clearly states it verifies quality issues like missing labels or descriptions, specifying the resource types checked (owl:Class, owl:ObjectProperty, etc.). This distinctly separates it from siblings like 'check_overlaps' or 'check_coverage'.

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?

The description includes a 'When to use ontologyUri' section with explicit guidance on when to pass the ontology URI to exclude imported resources, reducing false positives. It also explains false positive filtering. While it doesn't list alternatives explicitly, the context is clear.

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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