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atlaspi-mcp

atlaspi-mcp

by Soil911
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

compare_entities

Compare two historical entities by ID to receive a structured report covering temporal overlap, territorial differences, status, capitals, and sources.

Instructions

Confronta due entita' storiche dato il loro id numerico. Ritorna un report strutturato con sovrapposizione temporale, differenze di estensione territoriale, diversita' di status, capitali e fonti. Utile per domande comparative tipo 'paragona Roma Repubblicana e Impero Bizantino' o 'che differenze ci sono tra il Sacro Romano Impero e l'Impero Carolingio?'.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id1": "<id1>",
      "id2": "<id2>"
    },
    "name": "compare_entities"
  }
}

Input Schema

NameRequiredDescriptionDefault
id1YesID della prima entita'.
id2YesID della seconda entita'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.3

TDQS

A3.6/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions the tool returns a structured report with certain fields, but does not discuss potential errors, required permissions, or any side effects. The agent would need to assume it is safe, but lacks explicit reassurance.

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?

Two sentences efficiently cover action, output, and use cases. The first sentence states the core function, and the second provides examples. No extraneous information, though it could be slightly more concise by removing the redundant 'dato il loro id numerico'.

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 comparison tool with no output schema, the description outlines the return structure (temporal overlap, territorial differences, etc.). However, it omits details like output format (JSON?), handling of invalid IDs, or entity type restrictions. It is adequate but not fully explicit.

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 coverage is 100% with descriptions for both required parameters (id1, id2). The description adds no additional detail beyond stating they are numeric IDs. Thus, it neither improves nor detracts from the schema, earning the baseline score of 3.

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?

Description clearly states it compares two historical entities by ID and returns a structured report with specific aspects like temporal overlap and territorial differences. Examples of comparative questions further clarify purpose. It distinguishes from siblings like get_entity (single entity) and what_changed_between (change over time).

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 explicitly says 'Utile per domande comparative' and gives examples, guiding when to use. It does not explicitly exclude cases or mention alternatives, but the context is sufficiently clear for an AI agent to infer appropriate usage.

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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