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MAD Synapse · Web & Research

Wikipedia lookup

wiki
Read-onlyIdempotent

Wikipedia in any language: search a topic and get the best article's summary, description, thumbnail and link — or the full article text. Search + REST summary from Wikipedia. full=true returns the article as plain text (sections kept), capped by max_chars. Disambiguation pages are flagged with alternatives. When to use: For encyclopedic topics; for papers use arxiv_search or doi_lookup. Price: free. Errors: returns isError with a message for invalid input or an upstream failure (not charged).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fullNotrue = return the full article text, not just the summary. Default false.
langNoWikipedia language code, e.g. "en", "de", "pt-br". Default "en".en
queryYesTopic or article title to look up.
max_charsNoTruncate full article text to this many characters (with full=true). Range 500-60000. Default 8000.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
typeNo
foundNo
titleNo
summaryNo
thumbnailNo
descriptionNo
last_editedNo
other_matchesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already declare the safe, idempotent, open-world read profile, but the description adds materially more: full=true returns plain text with sections kept and truncation by max_chars, disambiguation pages are flagged with alternatives, the call is free, and errors surface as isError without being charged. That is unusually rich behavioral disclosure.

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?

Front-loaded with the core behavior and every sentence carries information (output shape, truncation, disambiguation, when-to-use, cost, errors). "Search + REST summary from Wikipedia" is mildly implementation-flavored filler, but overall it is tight.

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 4-parameter lookup with an output schema, the description covers everything an agent needs to call it correctly: language, summary vs. full text, truncation limit, disambiguation handling, error semantics, and cost. No meaningful gaps remain.

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 100%, so baseline is 3; the description still adds meaning by explaining that full returns plain text (sections preserved) and that max_chars caps that output, clarifying the interaction between the two parameters. It adds little for query or lang beyond 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?

Names a specific resource (Wikipedia articles) and the concrete actions/results: search a topic, get the best article's summary, description, thumbnail and link, or the full text. It also distinguishes itself from sibling retrieval tools by calling out paper-oriented alternatives.

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

Usage Guidelines5/5

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

"When to use: For encyclopedic topics; for papers use arxiv_search or doi_lookup" gives an explicit condition and routes the agent to named alternatives. The full vs. summary choice is also framed with its cost in output size.

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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