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Nehra-Amaterasu

paper-search-mcp

search_core

Search academic papers from the CORE database by query. Returns paper metadata including title, authors, and links.

Instructions

Search academic papers from CORE.

Args: query: Search query string (e.g., 'machine learning'). max_results: Maximum number of papers to return (default: 10). Returns: List of paper metadata in dictionary format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
max_resultsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must cover behavioral aspects. It only mentions returning a list of paper metadata, but does not disclose rate limits, authentication needs, or any side effects. The read-only nature is implied but not stated.

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 concise—two sentences plus an Args section. The purpose is front-loaded. Minor improvement could be separating the args from the main description, but it's well-structured overall.

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?

With an output schema (though not shown), the description needn't detail return values, but it still mentions the return format. Missing usage guidelines and behavioral details make it somewhat incomplete for a search tool with many siblings.

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 0%, but the description includes an Args section that adds an example for query ('e.g., 'machine learning') and notes the default for max_results. This adds some value beyond the schema, though it remains relatively basic.

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 CORE' which specifies the verb (search) and the resource (academic papers from CORE). Among many sibling tools for different sources, this uniquely identifies the tool's purpose.

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 provides no guidance on when to use this tool versus alternatives like search_arxiv or search_pubmed. It does not mention when not to use it or any prerequisites.

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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