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seanshin0214

Dr. QuantMaster MCP Server

by seanshin0214

journal_guide

Provides journal-specific statistical reporting guidelines for quantitative research papers, helping researchers format results according to publication standards.

Instructions

저널별 통계 보고 가이드

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
journalYes목표 저널
methodNo사용 방법론

Implementation Reference

  • The main handler function for the 'journal_guide' tool. It extracts the journal name from arguments and returns a predefined guide object containing style, expectations, and stats_reporting details for specific journals like econometrica, aer, jfe.
    function handleJournalGuide(args: Record<string, unknown>) {
      const journal = args.journal as string;
      const guides: Record<string, any> = {
        econometrica: {
          style: "Rigorous mathematical notation",
          expectations: ["Novel theoretical contribution", "Clean identification", "Formal proofs"],
          stats_reporting: "Full estimation details, robustness in appendix"
        },
        aer: {
          style: "Clear causal identification",
          expectations: ["Policy relevance", "Clean natural experiment or RCT", "Replication data"],
          stats_reporting: "Main results in text, extensive robustness"
        },
        jfe: {
          style: "Empirical finance focus",
          expectations: ["Financial data", "Asset pricing or corporate finance", "Economic significance"],
          stats_reporting: "t-statistics in parentheses, clustering at firm level"
        }
      };
    
      return { journal, guide: guides[journal] || { message: "Journal guide not found" } };
    }
  • The input schema definition for the 'journal_guide' tool, specifying the expected parameters: journal (required, enum of journal names) and optional method.
    inputSchema: {
      type: "object",
      properties: {
        journal: {
          type: "string",
          enum: ["econometrica", "aer", "jfe", "ms", "smj", "amj", "jf", "rfs"],
          description: "목표 저널"
        },
        method: { type: "string", description: "사용 방법론" },
      },
      required: ["journal"],
  • Registration of the 'journal_guide' tool in the exported 'tools' array, including name, description, and input schema.
      name: "journal_guide",
      description: "저널별 통계 보고 가이드",
      inputSchema: {
        type: "object",
        properties: {
          journal: {
            type: "string",
            enum: ["econometrica", "aer", "jfe", "ms", "smj", "amj", "jf", "rfs"],
            description: "목표 저널"
          },
          method: { type: "string", description: "사용 방법론" },
        },
        required: ["journal"],
      },
    },
  • Registration of the handler function in the main 'handleToolCall' switch statement, dispatching calls to 'handleJournalGuide'.
    case "journal_guide":
      return handleJournalGuide(args);
Behavior1/5

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

No annotations are provided, so the description must fully disclose behavioral traits. It fails to do so—it doesn't indicate if this is a read-only guide, if it modifies data, requires authentication, has rate limits, or what the output format is. For a tool with no annotations, this lack of behavioral information is inadequate.

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 a single, concise phrase in Korean that directly states the tool's topic. It's front-loaded with no wasted words, making it efficient and easy to parse, though it lacks detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a text guide, structured data) or behavioral aspects. For a tool with two parameters and potential complexity in statistical reporting, more context is needed to be fully useful.

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

Parameters3/5

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

The schema description coverage is 100%, with clear descriptions for both parameters (e.g., '목표 저널' for journal, '사용 방법론' for method). The description adds no additional meaning beyond the schema, such as explaining parameter interactions or usage examples. Baseline 3 is appropriate since the schema adequately documents parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description '저널별 통계 보고 가이드' (Journal-specific statistical reporting guide) is vague about what the tool actually does. It mentions a guide related to statistical reporting for journals but doesn't specify the action (e.g., generates, provides, explains) or what resource it operates on. While it distinguishes from siblings by mentioning journals, it's too general to clearly understand its function.

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 prerequisites, context, or compare it to sibling tools like 'get_method_guide' or 'suggest_method', leaving the agent with no usage instructions.

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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