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iwaokimura

mcp-cinii

by iwaokimura

search_cinii

Search academic articles, books, dissertations, data, and research projects in CiNii Research. Filter results by resource type and language, with pagination support.

Instructions

Search CiNii Research for academic articles, books, grants, and data.

Args: query: Search keywords (e.g. "機械学習" or "machine learning"). count: Number of results to return (1–200, default 20). start: 1-based result offset for pagination (default 1). lang: Response language, "ja" (Japanese) or "en" (English). Default "ja". resource_type: Filter by resource type. One of "Article", "Book", "Dissertation", "Data", "Research Project", or "" (all types).

Returns: JSON-LD response from CiNii Research as a formatted JSON string.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoja
countNo
queryYes
startNo
resource_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must fully disclose behavior. It covers parameters and return format, but omits potential issues like rate limits, authentication, or error conditions. It explains it's a search (likely read-only) but lacks depth.

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 very concise, with a clear title sentence and well-structured Arg list. Every sentence provides useful information, and there is no unnecessary verbosity.

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 has 5 parameters and an output schema (though not shown), the description covers parameters well and states the return format. It lacks information on error handling or prerequisites, but for a search tool this is fairly complete.

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 adds significant meaning: it explains each parameter's purpose, defaults, valid ranges (e.g., count 1–200), and the resource_type options. However, it could be more detailed for enums or exact formats.

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 action ('Search'), the resource ('CiNii Research'), and the scope ('academic articles, books, grants, and data'), distinguishing it from the sibling 'get_cinii_item' which likely retrieves a single item.

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 does not explicitly state when to use this tool versus alternatives. It implies broad search, but lacks direct comparison to 'get_cinii_item' or conditions for use.

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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