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check_citations

Check that every factual item in a script is backed by a quote that appears word for word in a source text, that numbers and names in the prose appear in the quotes, and that the prose retells rather than copies. Hosted limit: 3000 characters of prose per call; for longer scripts run the local server.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimsYes{"config": {...}, "sections": [{"title": str, "items": [{"id": str, "text": str, "claims": [{"src": str, "quote": str}]}]}]}
sourcesYesMap of source id -> full source text.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose useful operational behavior: the 3000-character prose limit per call and the local-server fallback. It does not describe permissions/auth needs or what a failing check produces, so it falls short of full disclosure for a tool with no output schema.

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?

Two sentences: the first front-loads the core verification behavior, the second carries the operational limit and fallback. No filler, and the most important information comes first.

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

Completeness3/5

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

For a nested-object tool with no output schema and no annotations, the description should also indicate the shape of the result (what a citation failure looks like). It explains inputs and limits well but is silent on return values and error behavior, leaving a real gap given there is no output schema to fall back on.

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%, but the claims parameter is documented only as a cryptic stringified JSON template. The description compensates by clarifying semantics: quotes must match word for word, numbers and names in prose must appear in quotes, and prose must not copy — constraints an agent needs to build valid claims/sources input.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb ("Check") and enumerates three concrete verification criteria: verbatim quote backing, numbers/names appearing in quotes, and prose retelling rather than copying. It is very clear what the tool does, but it never names or distinguishes itself from the sibling check_numbers, which overlaps with the numbers/names criterion.

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 states the context of use (scripts with sources) and provides an explicit alternative path: the 3000-character hosted limit with an instruction to run the local server for longer scripts. It lacks any guidance on how this differs from check_numbers, so a sibling-selection rule is missing.

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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