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SMABoundless

semantic-scholar-mcp-server

by SMABoundless

paper_batch

Reduce API calls by retrieving up to 500 paper details in a single batch request.

Instructions

Retrieve details for multiple papers in a single request (up to 500). More efficient than calling paper_get repeatedly. Pass a list of paper IDs in any supported format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoComma-separated fields to return, overriding defaults. Paper fields: paperId, title, abstract, authors, year, citationCount, referenceCount, influentialCitationCount, isOpenAccess, openAccessPdf, fieldsOfStudy, externalIds, url, venue, publicationVenue, publicationTypes, publicationDate, journal, citations, references. Author fields: authorId, name, affiliations, homepage, paperCount, citationCount, hIndex.
paper_idsYesList of paper IDs to retrieve (1-500). Supports all ID formats.
response_formatNoOutput format: 'markdown' for human-readable text (default), 'json' for raw structured datamarkdown
Behavior3/5

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

With no annotations, the description reveals batch limit (500) and ID format flexibility, but lacks details on error handling, ordering, or return structure.

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 concise sentences, front-loaded with action, no fluff. Every word serves a purpose.

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?

For a simple batch retrieval tool, the description covers key aspects (limit, efficiency, ID format). Missing mention of fields parameter behavior, but schema covers it.

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 coverage is 100%, and description only reiterates ID format support, adding no new meaning beyond the schema's parameter descriptions.

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 the tool retrieves details for multiple papers, distinguishes itself from paper_get by emphasizing efficiency and batch nature.

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?

Explicitly contrasts with paper_get for repeated calls, indicating when to use. Does not list when not to use or other alternatives like search.

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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