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Rudra-ravi

Wikipedia MCP Server

by Rudra-ravi

summarize_article_for_query

Read-onlyIdempotent

Retrieve a focused summary of a Wikipedia article around a given query, with adjustable snippet length.

Instructions

Get a summary of a Wikipedia article tailored to a specific query.

The summary is a snippet around the query within the article text or summary. The max_length parameter controls the length of the snippet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
queryYes
max_lengthNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYes
queryYes
summaryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.0.1
  2. Removedv1.5.8
  3. Changed3 schema fields changedv1.0.0
    • removedInput schema / properties / max_length / title
      Removed value: -"Max Length"
    • removedInput schema / properties / query / title
      Removed value: -"Query"
    • removedInput schema / properties / title / title
      Removed value: -"Title"
  4. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: the summary is a snippet around the query within the article text or summary, and max_length controls snippet length. This goes beyond the annotations without contradicting them.

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 two sentences, efficiently front-loaded with the main purpose, followed by a concise explanation of the snippet and max_length. Every sentence adds value with no fluff.

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?

With an output schema present and strong annotations (readOnly, idempotent), the description covers the core behavior and key parameter. It does not explain edge cases like query-not-found behavior, but this is not essential given the schema and annotations. The tool is well-specified for an agent to select and invoke 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 description coverage is 0%, so the description must compensate. It explicitly explains max_length ('controls the length of the snippet') and implicitly explains query ('tailored to a specific query') and title (the article title). This adds meaning beyond the bare parameter names, though it does not elaborate on constraints or defaults for title and query.

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 a specific verb and resource: 'Get a summary of a Wikipedia article tailored to a specific query.' This distinguishes it from generic summary tools like get_summary and from section-specific summarize_article_section, by emphasizing query-tailored output.

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 clearly implies when to use the tool: when a query-focused summary is needed. However, it does not explicitly mention alternatives or exclusions, such as 'Use get_summary for generic article summaries.' The context is clear but lacks explicit comparison with siblings.

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