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czwziy

scholar-toolkit-mcp

by czwziy

search_crossref

Search CrossRef for academic paper metadata using keywords, filters, and sorting options to control results.

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
queryYes
max_resultsNo
filterNo
sortNo
orderNo

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 full burden. It mentions returning 'list of paper metadata in dictionary format' and a default/max for max_results. However, it does not disclose rate limits, authentication needs, error handling, or read-only nature. Additional behavioral details are missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description includes a general introduction about CrossRef (e.g., 'scholarly infrastructure organization') that adds context but is not essential for tool usage. The Args section is clear, but the overall length could be reduced without losing key information.

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?

The tool has 5 parameters (1 required), no enums, and an output schema exists. The description covers all parameters and return format. However, it does not explain filter syntax in depth or query capabilities, and it could benefit from mentioning pagination or result limits beyond max_results.

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 description coverage is 0%, but the description includes a docstring-like Args section that explains each parameter with examples (e.g., query: 'machine learning', filter: 'has-full-text:true,from-pub-date:2020', sort values). This adds significant meaning beyond the schema's bare titles and types.

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 it searches academic papers from CrossRef, using specific verb 'search' and resource 'academic papers from CrossRef database'. It distinguishes from many sibling tools that target other databases or operations (e.g., download_*, search_arxiv, etc.).

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?

The description provides context that CrossRef is a large citation database, implying use for metadata search. However, it does not explicitly state when to use this tool versus the many other search tools (e.g., search_pubmed, search_semantic) or when not to use it. No alternatives or exclusions are mentioned.

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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