Skip to main content
Glama
seanshin0214

Dr. QuantMaster MCP Server

by seanshin0214

compare_methods

Compare statistical methods by analyzing their strengths, weaknesses, and application conditions to select the most appropriate approach for your research.

Instructions

여러 통계 방법 비교 (장단점, 적용조건)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodsYes비교할 방법들
criteriaNo비교 기준 (예: assumptions, efficiency, robustness)

Implementation Reference

  • The main handler function `handleCompareMethods` that implements the tool logic. It compares pairs of statistical methods (e.g., FE vs RE, DID vs SCM) using predefined comparison data and falls back to suggesting another tool if no predefined comparison exists.
    function handleCompareMethods(args: Record<string, unknown>) {
      const methods = args.methods as string[];
    
      const comparison: Record<string, any> = {
        fe_vs_re: {
          methods: ["Fixed Effects", "Random Effects"],
          key_difference: "FE는 개체 고정효과와 X 상관 허용, RE는 비상관 가정",
          decision: "Hausman test: H₀ 기각 → FE, H₀ 수용 → RE (효율성)",
          tradeoff: "FE: 일관성 | RE: 효율성 (시간불변 변수 추정 가능)"
        },
        did_vs_scm: {
          methods: ["DID", "Synthetic Control"],
          key_difference: "DID는 다수 처치/통제, SCM은 단일 처치 단위에 적합",
          decision: "처치 단위 수: 1 → SCM, 다수 → DID",
          tradeoff: "DID: 통계 검정 용이 | SCM: 평행추세 가정 완화"
        },
        psm_vs_iv: {
          methods: ["PSM", "IV/2SLS"],
          key_difference: "PSM은 관찰변수 통제, IV는 비관찰 내생성 해결",
          decision: "Selection on observables → PSM, Selection on unobservables → IV",
          tradeoff: "PSM: 도구변수 불필요 | IV: 비관찰 교란 통제"
        }
      };
    
      const methodKey = methods.sort().join("_vs_");
      const result = comparison[methodKey] || {
        methods,
        message: "상세 비교를 위해 search_stats_knowledge 도구 사용을 권장합니다."
      };
    
      return result;
    }
  • Registration of the 'compare_methods' tool in the exported `tools` array, including its name, description, and inputSchema definition.
    {
      name: "compare_methods",
      description: "여러 통계 방법 비교 (장단점, 적용조건)",
      inputSchema: {
        type: "object",
        properties: {
          methods: {
            type: "array",
            items: { type: "string" },
            description: "비교할 방법들"
          },
          criteria: {
            type: "array",
            items: { type: "string" },
            description: "비교 기준 (예: assumptions, efficiency, robustness)"
          },
        },
        required: ["methods"],
      },
    },
  • Input schema for the 'compare_methods' tool defining the expected arguments: array of methods (required) and optional criteria.
    inputSchema: {
      type: "object",
      properties: {
        methods: {
          type: "array",
          items: { type: "string" },
          description: "비교할 방법들"
        },
        criteria: {
          type: "array",
          items: { type: "string" },
          description: "비교 기준 (예: assumptions, efficiency, robustness)"
        },
      },
      required: ["methods"],
  • Registration of the handler in the `handleToolCall` switch statement, mapping the tool name to `handleCompareMethods`.
      return handleCompareMethods(args);
    case "get_formula":
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. While it mentions the tool compares methods' 'advantages/disadvantages' and 'application conditions', it doesn't describe what the comparison output looks like, whether it's a summary table or detailed analysis, if there are limitations to the comparison, or what format the results take. For a tool with no annotations and no output schema, this leaves significant behavioral questions unanswered.

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 extremely concise - a single phrase that efficiently communicates the core functionality. Every word earns its place: '여러 통계 방법 비교' establishes the action and target, while '(장단점, 적용조건)' adds valuable context about what aspects are compared. There's no wasted language or unnecessary elaboration.

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 that there are no annotations and no output schema, the description is insufficiently complete. While concise, it doesn't explain what the comparison output looks like, how results are structured, or what limitations might exist. For a tool that presumably generates comparative analysis of statistical methods, users need more context about the nature and format of the comparison results.

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%, with both parameters ('methods' and 'criteria') having descriptions in the schema. The tool description doesn't add any parameter-specific information beyond what's already in the schema. It mentions 'advantages/disadvantages, application conditions' which somewhat relates to the 'criteria' parameter, but doesn't provide additional semantic context about parameter usage or constraints.

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: '여러 통계 방법 비교 (장단점, 적용조건)' translates to 'Compare multiple statistical methods (advantages/disadvantages, application conditions)'. This specifies the verb (compare) and resource (statistical methods) with additional context about what aspects are compared. However, it doesn't explicitly differentiate from sibling tools like 'suggest_method' or 'get_method_guide' which might have overlapping functionality.

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. With many sibling tools related to statistical methods (suggest_method, get_method_guide, test_selection, etc.), there's no indication of when this comparison tool is appropriate versus those other options. The description only states what the tool does, not when to use it.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/seanshin0214/quantmaster-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server