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jstage_search_articles

Read-onlyIdempotent

Search academic articles on J-STAGE using keyword, author, title, journal, ISSN, affiliation, or year filters; inspect matching diagnostics to interpret noisy full-text search results.

Instructions

Search articles on J-STAGE. Returns the unified response envelope.

J-STAGE matches text against full text and treats multi-word terms loosely, so a high result.total is often noisy — read matching_mode (full_text_broad), result.breadth, and the diagnostics before treating a count as the size of a literature. A SCRIPT_LATIN_QUERY diagnostic means the query matched Latin-script text and metadata only; re-issue in kanji/kana. The same string can return very different totals on CiNii (metadata conjunction).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

A4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the bar is lower, and the description still adds substantial context. It explains full-text broad matching, loose multi-word handling, the meaning of matching_mode/result.breadth/diagnostics, SCRIPT_LATIN_QUERY implications, and differences from CiNii. This goes far beyond the structured annotations.

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 front-loaded with the core purpose and then provides a dense but relevant paragraph of caveats. Every sentence earns its place, with no filler or repetition of annotation 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 search tool's complexity and the existing output schema, the description covers the response envelope, diagnostics, matching behavior, and cross-source caveats. It does not explicitly address when to choose this tool over siblings or provide examples, but the essential invocation and result-interpretation context is present.

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?

Schema description coverage is 0% at the top level, but the nested schema properties have individual descriptions. The tool description adds meaningful semantics for the central text parameter, explaining full-text matching, noise, and re-issuing in kanji/kana, which is not in the schema. It does not discuss filters or pagination, but those are covered in the nested schema.

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 opens with 'Search articles on J-STAGE' and 'Returns the unified response envelope,' clearly stating the verb, resource, and scope. It is distinguishable from siblings like jstage_list_issues and jstage_get_article_by_doi by the search focus, though it does not explicitly contrast itself with them.

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 gives practical guidance for interpreting noisy results and re-issuing Latin-script queries in kanji/kana, which helps an agent act after receiving results. However, it does not explicitly state when to prefer this tool over the sibling tools or when not to use it, so usage selection is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.