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ociupitu

Academic Search MCP

by ociupitu

search_papers

Search academic papers by relevance using Semantic Scholar. Filter results by year, field, citation count, venue, or open access PDF availability.

Instructions

Relevance search for papers on Semantic Scholar.

Args:
    query: the search query string.
    limit: maximum number of results (default 10, capped at 100).
    year: a single year or range, e.g. "2018", "2015-2022", "2016-", "-2015".
    fields_of_study: restrict to fields, e.g. ["Economics", "Business"].
    min_citation_count: drop papers with fewer citations than this.
    venue: restrict to venues, e.g. ["Marketing Science"].
    open_access_pdf: if True, only return papers that have an open-access PDF.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNo
limitNo
queryYes
venueNo
fields_of_studyNo
open_access_pdfNo
min_citation_countNo
Behavior2/5

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

No annotations provided. Description only describes parameters, not behavioral traits like rate limits, authentication, or side effects. It implies a read-only search but does not state it.

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?

Concise block of text with a summary line and parameter list. Could be more structured (e.g., bullet points) but no redundant 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?

Covers parameter semantics well, but lacks usage guidelines, output format description, and behavioral context. Adequate but with clear gaps.

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 well by explaining each parameter's purpose and format, e.g., year range examples. However, default values for some parameters like 'year' are not explicitly stated.

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?

Description states 'Relevance search for papers on Semantic Scholar', which is a clear verb+resource. However, it does not differentiate from sibling tools like 'search_by_topic'.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives. Sibling tools like 'fetch_paper_details' and 'search_by_topic' are not referenced.

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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