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CrossRef Datasets Cited by an Article

crossref-datacitations.citations.from_article
Read-onlyIdempotent

Find datasets (Crossref-DOI or DataCite-DOI) cited by a given scholarly work DOI. Returns each cited dataset's DOI, registration agency (Crossref/DataCite), and the citation timestamp. Useful for surfacing the underlying data behind a paper for reproducibility or follow-up analysis. Data: api.crossref.org/beta/datacitations (CrossRef Data Citations API), no auth required, CC0 metadata.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsNoNumber of citation events to return (1-500, default 20)
article_doiYesDOI of the scholarly work to find cited datasets for (e.g. "10.1016/j.jpeds.2026.114997")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, open-world, and non-destructive behavior, so the bar is lower. The description adds valuable context beyond annotations: it notes the API endpoint (api.crossref.org/beta/datacitations), states that no auth is required, and mentions CC0 metadata. It also outlines the return fields, giving an agent a concrete expectation of the response.

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 compact (three sentences), front-loads the core purpose, and each sentence earns its place: it defines the function, lists the output, and gives a use case plus data-source/auth info. No fluff or redundant restatement of the title.

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 simple 2-parameter read-only tool with an output schema present, the description is complete. It covers the operation, the required input, output contents, data source, auth requirements, and a representative use case. The annotations handle the safety profile, and nothing an agent needs to invoke it correctly is missing.

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 schema fully documents both parameters (article_doi and rows). The description does not add extra meaning beyond the schema; it mentions the DOI concept but doesn't elaborate on parameter formatting, defaults, or constraints beyond what's already in the schema. Baseline 3 is appropriate.

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 states a specific action ('Find datasets... cited by a given scholarly work DOI') and specifies the resource (Crossref/DataCite DOIs) and the direction (from an article). It also names the exact output fields (DOI, registration agency, citation timestamp), leaving no ambiguity about what the tool does or how it differs from the sibling tools like browse or to_dataset.

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 gives a clear use case ('surfacing the underlying data behind a paper for reproducibility or follow-up analysis') and states the input requirement (a scholarly work DOI). However, it does not explicitly mention when to prefer this over the sibling tools (browse, to_dataset) or provide exclusion criteria, so it falls short of a 5.

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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