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Nehra-Amaterasu

paper-search-mcp

search_zenodo

Retrieve academic papers from Zenodo open repository by search query. Results include metadata such as title, authors, and publication date.

Instructions

Search academic papers from Zenodo open repository.

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?

With no annotations, the description must disclose behavioral traits. It only states the return format ('List of paper metadata') without addressing pagination, rate limits, authentication, or sorting. The default max_results is noted but not elaborated.

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, with a clear purpose sentence followed by structured Args and Returns sections. No redundant information, but the format could be slightly improved by integrating the default value inline rather than in a separate docstring.

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?

Given the tool's simplicity and the presence of an output schema (context signal), the description is adequate for basic usage. However, it lacks information on pagination, error handling, and repository-specific quirks, leaving some gaps for complex queries.

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?

Despite 0% schema coverage, the description adds meaningful semantics: 'query: Search query string (e.g., 'machine learning')' provides a concrete example, and 'max_results: Maximum number of papers to return (default: 10)' clarifies the parameter's behavior. This compensates well for the schema's lack of description.

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's function: 'Search academic papers from Zenodo open repository.' It uses a specific verb (search) and resource (academic papers) and uniquely identifies the repository (Zenodo), distinguishing it from sibling search_* tools for other databases.

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 is provided on when to use this tool vs. alternatives like search_arxiv or search_base. The description does not mention coverage, advantages, or situations where Zenodo is appropriate.

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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