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citation_needed

Scan a Wikipedia article for sentences tagged citation needed, or search by topic to find unsourced claims. Use it to identify missing citations for editing or research.

Instructions

Find statements Wikipedia has flagged as needing a source. Two angles: pass article to extract every sentence in that article carrying a {{citation needed}} tag (the exact claims editors flagged, with tag dates), or pass topic (or neither) to search Wikipedia for articles with unsourced claims on that topic, each with the flagged claim's text. Use it to find sourcing work as an editor or to spot the shakiest claims in a topic you're researching. The verification companion to references: this finds what's missing a source. Tag-name matching is English-centric; lang accepted for API consistency. Read-only — GET only, no new dependencies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoWikipedia language code (default 'en')en
limitNoMax claims/articles to return (default 10, max 25)
topicNoKeyword to scope the search (e.g. 'climate'); omit for a Wikipedia-wide sample
articleNoExact article title to scan for tagged claims (takes precedence over topic)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.26

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description usefully discloses read-only GET-only behavior, no new dependencies, and an English-centric tag-matching limitation. It does not cover auth or rate-limit behavior, but the safety and tagging constraints are clearly surfaced.

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-loads the purpose and mode selection, with each sentence contributing useful routing or behavior. It is slightly dense and includes minor redundancy such as 'read-only — GET only', but remains well-structured and appropriately sized.

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 no output schema, the description does a reasonable job explaining what each mode returns: tagged sentences with dates for `article`, and articles with flagged claim text for `topic`. It omits some return-shape and pagination details, but the core behavior is sufficiently covered.

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 description coverage is 100%, so the baseline is 3. The description restates the `article` vs `topic`/neither modes and precedence, and adds that `article` returns tagged sentences with tag dates, but it adds limited parameter-level syntax or format detail 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?

States a specific verb and resource: finding Wikipedia statements flagged as needing a source. It distinguishes itself from the sibling `references` by explicitly calling itself the verification companion that finds missing sources, so an agent can tell the tools apart without opening schemas.

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?

Gives clear usage contexts: find sourcing work as an editor or spot shaky claims in a topic. It also explains the two primary modes via `article` vs `topic`/neither, but does not state explicit when-not conditions or fully route the agent away from alternatives.

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