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TeXmeijin

Manalink MCP Server

by TeXmeijin

get_subject_master

Retrieve subject labels and their corresponding IDs to map and organize subject data within the Manalink MCP Server, enabling efficient search and categorization.

Instructions

科目マスタを取得します。このマスタの取得を通じて、科目のラベルとIDの対応を取得します。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/server.ts:19-30 (registration)
    Registration of the 'get_subject_master' tool, including its description and inline handler function that returns the subjects master as formatted JSON text.
    server.tool(
      "get_subject_master",
      "科目マスタを取得します。このマスタの取得を通じて、科目のラベルとIDの対応を取得します。",
      async () => {
        return {
          content: [{
            type: "text" as const,
            text: JSON.stringify(subjects, null, 2)
          }]
        };
      }
    );
  • The subjects master data array used by the get_subject_master tool handler.
    export const subjects: Subject[] = [
      { id: 40, name: "英語", code: "english" },
      { id: 45, name: "理科", code: "science" },
      { id: 46, name: "化学", code: "chemistry" },
      { id: 47, name: "物理", code: "physics" },
      { id: 48, name: "算数", code: "math" },
      { id: 49, name: "中学数学", code: "juniorhighschoolmath" },
      { id: 50, name: "高校数学", code: "highschoolmath" },
      { id: 51, name: "国語", code: "language" },
      { id: 52, name: "古典", code: "classic" },
      { id: 53, name: "社会", code: "social" },
      { id: 212, name: "その他の科目", code: "others" },
      { id: 2655, name: "総合型・学校推薦型対策", code: "essay" },
      { id: 2657, name: "金融", code: "finance" },
      { id: 2658, name: "情報", code: "information" }
    ];
  • Type definition (schema) for Subject entries in the master data.
    export interface Subject {
      id: number;
      name: string;
      code: string;
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool '取得します' (gets/retrieves), implying a read-only operation, but doesn't clarify aspects like authentication needs, rate limits, error conditions, or whether it returns all data or requires filtering. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 two concise sentences in Japanese, front-loaded with the core purpose and followed by a clarifying detail about the output. Every word earns its place, with no redundancy or unnecessary elaboration, making it efficient and well-structured.

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 (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains the purpose and output semantics, which is sufficient for basic use. However, it lacks behavioral context (e.g., read-only nature, potential constraints) and usage guidelines relative to siblings, making it minimally viable but not fully comprehensive.

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?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds value by explaining the semantic output: '科目のラベルとIDの対応を取得します' (obtains correspondence between subject labels and IDs), which clarifies what the tool returns beyond just 'subject master'. This compensates for the lack of an output 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 clearly states the tool's purpose: '科目マスタを取得します' (get subject master) and specifies what is obtained: '科目のラベルとIDの対応' (correspondence between subject labels and IDs). It distinguishes the resource (subject master) and the specific mapping provided. However, it doesn't explicitly differentiate from sibling tools like get_grade_master or get_course_features, which likely retrieve different master data types.

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. It doesn't mention sibling tools (e.g., get_grade_master for grade data) or specify contexts where this tool is appropriate (e.g., when needing label-ID mappings for subjects). Usage is implied only by the purpose statement, with no explicit when/when-not instructions or 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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