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czwziy

scholar-toolkit-mcp

by czwziy

search_biorxiv

Find recent bioRxiv papers by category. Filter results by category name like 'bioinformatics' to get relevant academic articles from the last 30 days.

Instructions

Search academic papers from bioRxiv.

Note: bioRxiv API filters by category name within the last 30 days, not full-text keyword search. Use a category keyword such as 'bioinformatics', 'neuroscience', 'cell biology', etc.

Args: query: Category name to filter by (e.g., 'bioinformatics', 'neuroscience'). 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
Behavior5/5

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

No annotations are provided, so the description carries full responsibility. It clearly discloses that the bioRxiv API does not perform full-text keyword search but instead filters by category name and is limited to the last 30 days. It also notes that the query parameter expects a category name, not arbitrary keywords, which is crucial for correct use.

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?

The description is concise: a short sentence, a helpful note, and docstring-style parameter descriptions. Every sentence adds value, and the structure is easy to scan. No unnecessary information.

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?

Given the tool's simplicity (2 parameters) and the presence of an output schema (not shown but mentioned), the description is fairly complete. It addresses the key behavioral nuance (category filter, 30-day window) and parameter meanings. However, it could be slightly more complete by noting any rate limits or the specific fields in the returned metadata, which are not described.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains that 'query' is a category name (e.g., 'bioinformatics'), and 'max_results' controls the number of returned papers (default 10). This adds essential meaning beyond the bare schema, which only provides type and default.

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 bioRxiv', which is a specific verb+resource. It distinguishes from sibling search tools by specifying the source (bioRxiv) and adds a clarifying note about the API's category-based filtering and 30-day window, which differentiates it from other search tools.

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

Usage Guidelines3/5

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

The description explains that the API filters by category name within the last 30 days and provides example category keywords. However, it does not explicitly state when to use this tool versus alternative search tools for other repositories (e.g., search_arxiv, search_pubmed). The guidance is partially implicit but lacks explicit when-to-use or when-not-to-use comparisons with siblings.

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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