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Dianel555

Paper Search MCP

by Dianel555

search_sciencedirect

Search academic papers from Elsevier's ScienceDirect database to find relevant research articles using filters for year, author, journal, and open access status.

Instructions

Search academic papers from Elsevier ScienceDirect database (requires API key)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query string
maxResultsNoMaximum number of results to return
yearNoYear filter (e.g., "2023", "2020-2023")
authorNoAuthor name filter
journalNoJournal name filter
openAccessNoFilter for open access articles only
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only mentions the API key requirement, but doesn't describe what the search returns (e.g., metadata, abstracts, full text availability), pagination behavior, rate limits, authentication scope, or error conditions. This leaves significant gaps for a search tool with 6 parameters.

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 a single, efficient sentence that communicates the core purpose and key requirement. It's appropriately sized and front-loaded with the main functionality, though it could potentially be more structured with separate usage notes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a search tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what kind of results are returned, how they're formatted, whether there's pagination, or any limitations. The API key mention is helpful but insufficient for full contextual understanding.

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 already documents all 6 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score of 3 for high schema coverage.

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?

The description clearly states the tool searches academic papers from the Elsevier ScienceDirect database, which is a specific verb (search) and resource (academic papers from ScienceDirect). It distinguishes from siblings like search_arxiv or search_pubmed by specifying the database source, though it doesn't explicitly contrast with all similar search tools in the list.

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?

The description mentions 'requires API key' which provides some context about prerequisites, but it doesn't offer guidance on when to use this tool versus alternatives like search_scopus or search_semantic_scholar. No explicit when/when-not instructions or comparison to sibling tools are provided.

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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