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user_contribs

Review recent Wikipedia edits by a username or IP address to audit activity, profile contributors, and spot single-purpose accounts.

Instructions

What a Wikipedia editor has been doing — their recent contributions across the encyclopedia. Shows the latest edits by a named account (or an IP address, e.g. user='192.0.2.1'): edited pages, timestamps, byte-size deltas, edit comments, and flags for new pages, minor edits, and edits still current. The header reports registration date and total edit count. The reverse angle of contributors (who edits this article): profile a top contributor, audit an anonymous IP's activity, or spot single-purpose accounts (edits confined to one topic hint at a conflict of interest). namespace scopes the search (default 0 = articles). Read-only — GET only, no new dependencies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoWikipedia language code (default 'en')en
userYesWikipedia username or IP address (e.g. 'Jimbo Wales')
limitNoMax contributions to return (default 10, max 50)
namespaceNoNamespace to search (default 0 = articles; 3 = user talk)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.25

TDQS

A4.6/5.0
Behavior4/5

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

No annotations, so the description carries the burden and mostly does: it declares read-only, GET-only, no new dependencies, and enumerates the returned fields including flags and a header with registration date and edit count. It stops short of mentioning rate limits or pagination, but the behavioral profile is well covered for a read tool.

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 purpose in the first clause, then details, then the sibling relationship, then a compact annotation-style tail. Dense but every sentence contributes; the parenthetical example list of fields is slightly heavy.

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?

With no output schema, the description compensates by describing exactly what the response contains (edited pages, timestamps, byte deltas, comments, flags, header metadata). Combined with full param coverage and explicit read-only status, an agent has everything needed to call it 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 coverage is 100% (baseline 3), and the description still adds value: it explains that `user` accepts an IP address with a concrete example and that `namespace` scopes the search with the article default, which goes beyond the terse schema text.

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?

States a specific verb and resource - 'recent contributions' by a named editor or IP - and explicitly positions itself as 'the reverse angle of `contributors`', letting an agent distinguish the two siblings immediately.

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?

Gives explicit use cases: profile a top contributor, audit an anonymous IP, spot single-purpose accounts. It also names the alternative tool and the axis on which the choice is made (who edits this article vs what this editor edits).

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