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seanshin0214

Dr. QuantMaster MCP Server

by seanshin0214

create_project_structure

Generates organized folder structures for quantitative research projects using customizable templates to maintain consistency and streamline workflow setup.

Instructions

연구 프로젝트 폴더 구조 생성

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
project_nameYes프로젝트명
base_pathYes기본 경로
templateNo템플릿

Implementation Reference

  • The main handler function implementing the 'create_project_structure' tool logic. It extracts project_name and template from args, defines predefined folder structures for different templates (basic, replication, full), and returns the project structure details along with a README template.
    async function handleCreateProjectStructure(args: Record<string, unknown>) {
      const projectName = args.project_name as string;
      const template = (args.template as string) || "basic";
    
      const structures: Record<string, string[]> = {
        basic: ["/code", "/data", "/output", "/docs"],
        replication: ["/code/analysis", "/code/data_prep", "/data/raw", "/data/processed", "/output/tables", "/output/figures", "/docs"],
        full: ["/code/00_master", "/code/01_data", "/code/02_analysis", "/code/03_robustness", "/data/raw", "/data/processed", "/data/temp", "/output/tables", "/output/figures", "/output/logs", "/docs", "/paper"]
      };
    
      return {
        project_name: projectName,
        template,
        structure: structures[template],
        readme_template: "# Project Name\n\n## Structure\n\n## Replication Instructions\n\n## Data Sources\n\n## Contact"
      };
    }
  • Switch case in handleToolCall function that routes calls to the 'create_project_structure' tool to its handler function.
    case "create_project_structure":
      return handleCreateProjectStructure(args);
  • Tool registration entry in the exported 'tools' array, defining the name, description, and input schema for 'create_project_structure'.
      name: "create_project_structure",
      description: "연구 프로젝트 폴더 구조 생성",
      inputSchema: {
        type: "object",
        properties: {
          project_name: { type: "string", description: "프로젝트명" },
          base_path: { type: "string", description: "기본 경로" },
          template: { type: "string", enum: ["basic", "replication", "full"], description: "템플릿" },
        },
        required: ["project_name", "base_path"],
      },
    },
  • Input schema definition specifying required parameters project_name and base_path, and optional template enum for the tool.
    inputSchema: {
      type: "object",
      properties: {
        project_name: { type: "string", description: "프로젝트명" },
        base_path: { type: "string", description: "기본 경로" },
        template: { type: "string", enum: ["basic", "replication", "full"], description: "템플릿" },
      },
      required: ["project_name", "base_path"],
    },
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. '생성' implies a write operation, but the description doesn't specify whether this creates physical folders, requires specific permissions, has side effects, or what happens on failure. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

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, efficient phrase in Korean that directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, with every element earning its place.

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 (a mutation operation creating folder structures), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral details, making it inadequate for safe and effective use by an AI agent.

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?

Schema description coverage is 100%, so the schema already documents all three parameters (project_name, base_path, template with enum values). The description adds no additional meaning about parameters beyond what's in the schema, such as format examples or constraints, resulting in the baseline score of 3.

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 action ('생성' meaning 'create') and resource ('연구 프로젝트 폴더 구조' meaning 'research project folder structure'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'code_template', 'prereg_template', or 'replication_package' that might also involve project structure creation, which prevents a perfect score.

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. There's no mention of prerequisites, context, or comparison with sibling tools like 'code_template' or 'replication_package', leaving the agent to guess based on the tool name alone.

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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