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seanshin0214

Dr. QuantMaster MCP Server

by seanshin0214

timeseries_guide

Guide for time series analysis using ARIMA, VAR, VECM, GARCH, and state space models with stationarity testing options.

Instructions

시계열 분석 가이드 (ARIMA, VAR, 공적분)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
analysisYes분석 유형
stationarityNo정상성 검정 포함

Implementation Reference

  • The main handler function for the 'timeseries_guide' tool. It takes input arguments and returns a structured workflow guide for timeseries analysis (e.g., ARIMA, VAR) including steps like stationarity tests and diagnostics.
    function handleTimeseriesGuide(args: Record<string, unknown>) {
      return {
        analysis: args.analysis,
        workflow: [
          "1. Stationarity test (ADF, KPSS)",
          "2. Determine order (ACF, PACF, Information criteria)",
          "3. Estimate model",
          "4. Diagnostics (Ljung-Box, residual ACF)",
          "5. Forecasting / Impulse response"
        ]
      };
    }
  • Registration of the 'timeseries_guide' tool in the exported tools array, including name, description, and input schema definition.
    {
      name: "timeseries_guide",
      description: "시계열 분석 가이드 (ARIMA, VAR, 공적분)",
      inputSchema: {
        type: "object",
        properties: {
          analysis: { type: "string", enum: ["arima", "var", "vecm", "garch", "state_space"], description: "분석 유형" },
          stationarity: { type: "boolean", description: "정상성 검정 포함" },
        },
        required: ["analysis"],
      },
    },
  • Tool handler dispatch in the main handleToolCall switch statement, mapping the tool name to its handler function.
    case "timeseries_guide":
      return handleTimeseriesGuide(args);
  • Input schema for the 'timeseries_guide' tool, defining parameters like 'analysis' (required, enum of timeseries methods) and optional 'stationarity' boolean.
    inputSchema: {
      type: "object",
      properties: {
        analysis: { type: "string", enum: ["arima", "var", "vecm", "garch", "state_space"], description: "분석 유형" },
        stationarity: { type: "boolean", description: "정상성 검정 포함" },
      },
      required: ["analysis"],
    },
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. The description only states what the tool is about, not how it behaves: it doesn't specify whether this generates code, provides explanations, returns structured guidance, or has any limitations. For a guidance tool with zero annotation coverage, this is a significant gap in behavioral 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 extremely concise - a single phrase listing the tool's focus areas. Every word earns its place by specifying the analytical domain and key methods. There's no wasted verbiage 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?

For a guidance tool with no annotations and no output schema, the description is insufficiently complete. It doesn't indicate what form the guidance takes (text, code examples, structured advice), what depth it provides, or what users can expect as output. The context signals show this is a 2-parameter tool with method selection, but the description doesn't help users understand what they'll receive.

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 both parameters thoroughly. The description doesn't add any meaning beyond what's in the schema - it doesn't explain what 'analysis' choices mean in practice or how 'stationarity' affects the guidance. With complete schema coverage, the baseline 3 is appropriate.

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: providing guidance for time series analysis with specific methods listed (ARIMA, VAR, cointegration). It uses a specific verb ('guide') and identifies the resource domain (time series analysis). However, it doesn't explicitly differentiate from sibling tools like 'get_method_guide' or 'suggest_method' that might also provide methodological guidance.

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, appropriate contexts, or when other tools like 'get_method_guide' or 'suggest_method' might be more suitable. The user must infer usage from the title 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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