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Wikimedia Rest

by io.github.pipeworx-io
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Onthisday

onthisday
Read-onlyIdempotent

"What happened on this day" / "events that happened on May 21" / "historical events on a date" — births, deaths, events, holidays, and selected occurrences from history for any month+day. Pass type="all" for everything, or filter to "births" / "deaths" / "events" / "holidays" / "selected".

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "day": 14,
      "type": "births",
      "month": 3
    },
    "name": "onthisday"
  }
}

Input Schema

NameRequiredDescriptionDefault
dayYes
langNo
typeYesOne of "all", "births", "deaths", "events", "holidays", "selected".
monthYes
projectNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / type / description
      Added value: +"One of \"all\", \"births\", \"deaths\", \"events\", \"holidays\", \"selected\"."
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, lowering the bar. The description adds value by explaining the different content types returned and that results are for any month+day. It does not contradict annotations.

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

Conciseness5/5

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

The description is compact, front-loaded with real-world queries, and uses a dash-separated list to enumerate content types. Every phrase adds useful information, with no redundant or filler words.

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

Completeness4/5

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

Given an output schema exists and annotations are strong, the description covers the essential purpose and filtering behavior. It could mention that 'lang' and 'project' are optional, but this is a minor gap. Overall it is sufficiently complete for a simple read-only lookup tool.

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 only 20%, so the description must compensate. It does explain the 'type' values, matching the schema's own description, and implies month/day are numbers. However, it does not explain optional parameters like 'lang' and 'project', which are only shown in examples. This is a partial but not complete compensation.

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 opens with natural language queries that clearly define the tool's function: retrieving historical events for a given date. It enumerates the types of occurrences (births, deaths, events, holidays, selected) and distinguishes it from other sibling tools that focus on pages or entities.

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?

It provides explicit usage instructions for the 'type' parameter ('Pass type="all" for everything, or filter to...'), which gives clear guidance on filtering. However, it does not mention when to prefer this tool over alternatives, so it stops short of a full 'when-to-use' explanation.

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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