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seanshin0214

Dr. QuantMaster MCP Server

by seanshin0214

rdd_bandwidth

Select optimal bandwidth parameters for regression discontinuity designs using IK, CCT, or CV methods to ensure valid causal inference results.

Instructions

RDD 대역폭 선택 가이드

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
designYesRDD 유형
methodNo대역폭 선택 방법

Implementation Reference

  • The handler function implementing the 'rdd_bandwidth' tool. Returns guidance on RDD bandwidth selection methods (IK, CCT, CV) including descriptions and example code snippets for R and Stata.
    function handleRddBandwidth(args: Record<string, unknown>) {
      return {
        design: args.design,
        methods: {
          ik: "Imbens-Kalyanaraman (2012) - 기본 선택",
          cct: "Calonico-Cattaneo-Titiunik (2014) - bias correction",
          cv: "Cross-validation - 데이터 기반"
        },
        stata: "rdrobust y x, c(0) kernel(triangular)",
        r: "rdrobust(Y, X, c = 0)"
      };
    }
  • Registration of the 'rdd_bandwidth' tool in the exported tools array, including name, description, and input schema.
    {
      name: "rdd_bandwidth",
      description: "RDD 대역폭 선택 가이드",
      inputSchema: {
        type: "object",
        properties: {
          design: { type: "string", enum: ["sharp", "fuzzy"], description: "RDD 유형" },
          method: { type: "string", enum: ["ik", "cct", "cv"], description: "대역폭 선택 방법" },
        },
        required: ["design"],
      },
    },
  • Registration of the tool handler in the switch statement of handleToolCall function.
    case "rdd_bandwidth":
      return handleRddBandwidth(args);
  • Input schema definition for the 'rdd_bandwidth' tool, specifying parameters for RDD design type and bandwidth selection method.
    inputSchema: {
      type: "object",
      properties: {
        design: { type: "string", enum: ["sharp", "fuzzy"], description: "RDD 유형" },
        method: { type: "string", enum: ["ik", "cct", "cv"], description: "대역폭 선택 방법" },
      },
      required: ["design"],
    },
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 only states it's a 'guide' without explaining what that entails—e.g., whether it performs calculations, returns recommendations, requires specific inputs beyond the schema, or has any side effects like data processing. This is inadequate for a tool with parameters and no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single phrase ('RDD 대역폭 선택 가이드') that is overly concise to the point of under-specification. It lacks any structure or elaboration to clarify the tool's purpose or usage, making it inefficient for an agent to understand without additional context. This is not true conciseness but rather omission of necessary details.

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

Completeness1/5

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

Given the tool has 2 parameters, no annotations, and no output schema, the description is incomplete. It fails to explain what the tool does, how it behaves, or what it returns, leaving significant gaps for an agent to invoke it correctly. Compared to siblings like 'calc_effect_size' or 'suggest_method', this description provides minimal contextual value.

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 clear enum values and descriptions for both parameters ('design' and 'method'). The description adds no additional meaning beyond the schema, such as explaining how these parameters interact or what 'RDD 유형' (RDD type) entails. Since schema coverage is high, the baseline score of 3 is appropriate.

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 'RDD 대역폭 선택 가이드' (RDD bandwidth selection guide) is tautological—it essentially restates the tool name 'rdd_bandwidth' in Korean without specifying what the tool actually does (e.g., whether it calculates, recommends, or visualizes bandwidth). It does not distinguish this tool from its many siblings, which include various statistical and coding tools like 'calc_effect_size' or 'suggest_method'.

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 any context, prerequisites, or exclusions, nor does it reference sibling tools like 'compare_methods' or 'suggest_method' that might be related. This leaves the agent with no information to decide when this tool is appropriate.

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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