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Nehra-Amaterasu

paper-search-mcp

search_crossref

Search academic papers from CrossRef database with customizable filters and sorting to obtain metadata.

Instructions

Search academic papers from CrossRef database.

CrossRef is a scholarly infrastructure organization that provides persistent identifiers (DOIs) for scholarly content and metadata. It's one of the largest citation databases covering millions of academic papers, journals, books, and other scholarly content.

Args: query: Search query string (e.g., 'machine learning', 'climate change'). max_results: Maximum number of papers to return (default: 10, max: 1000). filter: CrossRef filter string (e.g., 'has-full-text:true,from-pub-date:2020'). sort: Sort field ('relevance', 'published', 'updated', 'deposited', etc.). order: Sort order ('asc' or 'desc'). Returns: List of paper metadata in dictionary format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNo
orderNo
queryYes
filterNo
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It describes the return format as a list of metadata dictionaries but does not discuss side effects, rate limits, or authentication requirements. The background on CrossRef is contextual but not behavioral.

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?

The description is well-structured with Args/Returns sections but includes a somewhat lengthy background paragraph about CrossRef. While informative, it could be more concise without losing clarity.

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?

Given the complexity (5 params, 1 required) and the existence of an output schema, the description fully covers the tool's purpose, parameters, and return type. No critical information is missing for an agent to use 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?

With 0% schema description coverage, the description compensates by explaining all five parameters with examples and default values. It adds meaning beyond the schema, though sort options are listed but not enumerated.

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 clearly states 'Search academic papers from CrossRef database' with a specific verb and resource. It distinguishes itself from numerous sibling search tools by specifying CrossRef as the target database.

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

Usage Guidelines3/5

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

While the name and context implicitly indicate it's for searching CrossRef, the description does not provide explicit guidance on when to use it versus other search tools (e.g., search_openalex, search_pubmed) or state any exclusions.

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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