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seanshin0214

Dr. QuantMaster MCP Server

by seanshin0214

apa_reporting

Generate APA-style statistical reporting templates for research results to ensure proper formatting and compliance with academic standards.

Instructions

APA 스타일 통계 보고 템플릿

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
test_typeYes검정 유형
resultsYes결과 값들

Implementation Reference

  • Registration of the 'apa_reporting' tool including name, description, and input schema for test_type and results.
      name: "apa_reporting",
      description: "APA 스타일 통계 보고 템플릿",
      inputSchema: {
        type: "object",
        properties: {
          test_type: { type: "string", description: "검정 유형" },
          results: { type: "object", description: "결과 값들" },
        },
        required: ["test_type", "results"],
      },
    },
  • The handler function for 'apa_reporting' tool. It takes args with test_type and returns a basic APA style reporting template string.
    function handleApaReporting(args: Record<string, unknown>) {
      return {
        test_type: args.test_type,
        template: "t(df) = X.XX, p < .05, d = X.XX, 95% CI [X.XX, X.XX]"
      };
    }
Behavior1/5

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. However, it fails to describe any behavioral traits—such as whether this tool creates, modifies, or outputs data; what permissions or inputs are needed; or any side effects like file generation. The description is too minimal to inform the agent about how the tool behaves, making it opaque and risky to invoke.

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 a single, concise phrase in Korean, which is appropriately sized for a simple tool. It is front-loaded with the core idea but lacks detail that could earn a higher score. While efficient, it under-specifies the tool's purpose, slightly reducing its effectiveness despite the brevity.

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 the tool's complexity (2 parameters, nested objects, no output schema) and lack of annotations, the description is incomplete. It does not explain what the tool outputs (e.g., a formatted report, code, or text), how results are structured, or any behavioral context. For a tool that likely generates statistical reports, this leaves critical gaps, making it inadequate for the agent to use confidently.

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 input schema has 100% description coverage, with parameters 'test_type' and 'results' documented in the schema itself. The description adds no additional meaning about these parameters—it does not explain what 'test_type' values are expected or how 'results' should be structured. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but the description misses an opportunity to clarify usage (e.g., example test types).

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 'APA 스타일 통계 보고 템플릿' (APA style statistical reporting template) is vague and tautological—it essentially restates the tool name 'apa_reporting' in Korean with minimal added context. While it hints at generating APA-style reports, it lacks a specific verb (e.g., 'generate' or 'create') and does not clearly distinguish this tool from siblings like 'write_results_section' or 'code_template', which might also produce formatted outputs. This leaves the agent uncertain about the exact action.

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

Usage Guidelines1/5

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 does not mention prerequisites, context (e.g., after statistical tests), or exclusions, nor does it reference sibling tools like 'write_results_section' for comparison. Without this, the agent must guess based on the tool name alone, which is insufficient for reliable selection.

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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