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Schema.gov.it MCP Server

Schema.gov.it MCP Server

Official
by italia
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

Check Overlaps

check_overlaps
Read-onlyIdempotent

Find potential overlaps in Italian government data by detecting same-label collisions and explicit mappings like owl:sameAs and skos:exactMatch.

Instructions

Identify potential overlaps (same labels) or explicit mappings.

Args:

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

Returns:

  • List of potential overlaps with relation type:

    • owl:sameAs mappings

    • skos:exactMatch mappings

    • Same Label collisions

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_overlaps"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare the tool is read-only, idempotent, and non-destructive. The description adds that it returns a list of overlaps with relation types (owl:sameAs, skos:exactMatch, Same Label), which is useful but does not disclose full behavioral traits like result limits beyond the default 50, or whether results are exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise but slightly redundant: the Returns section repeats the relation types already mentioned in the first sentence. It is front-loaded with the purpose, but the Args section is necessary. Overall, it could be more streamlined.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only tool with one parameter and no output schema, the description covers purpose, parameter, and return structure. However, it lacks context about the scope of the check (e.g., entire knowledge graph vs. specific dataset) and does not explain what 'Same Label collisions' means precisely.

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 description coverage is 0%, so the description must compensate. It clearly documents the single parameter 'limit' with its default value (50), adding meaning beyond the schema's type and default. However, it could be improved by noting any accepted range or behavior when omitted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool identifies potential overlaps (same labels) or explicit mappings, using specific verbs and resources. It distinguishes its function from sibling tools like 'check_quality' or 'check_coverage' by focusing on overlaps, but does not explicitly differentiate from all siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It only describes what the tool does without context for usage decisions.

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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