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DART-MCP

by 2geonhyup
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search_json_financial_data

Retrieve financial statements for Korean companies via JSON API when primary search tools fail, providing balance sheets, income statements, and cash flow data for analysis.

Instructions

회사의 재무 정보를 JSON API를 통해 제공하는 실패시 보완하는 보조 도구.
search_disclosure, search_detailed_financial_data이 2023년 9월 이전 자료 분석에 실패했을 때 대안으로 활용.

Args:
    company_name: 회사명 (예: 삼성전자, 네이버 등)
    bsns_year: 사업연도 (4자리, 예: "2023")
    ctx: MCP Context 객체
    reprt_code: 보고서 코드 ("11011": 사업보고서, "11012": 반기보고서, "11013": 1분기보고서, "11014": 3분기보고서)
    fs_div: 개별/연결구분 ("OFS": 재무제표, "CFS": 연결재무제표)
    statement_type: 재무제표 유형 ("BS": 재무상태표, "IS": 손익계산서, "CIS": 포괄손익계산서, "CF": 현금흐름표, "SCE": 자본변동표)
                   None인 경우 모든 유형의 재무제표 정보를 반환합니다.
    
Returns:
    선택한 재무제표 유형(들)의 세부 항목 정보가 포함된 텍스트 (당기 데이터만 표시)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
company_nameYes
bsns_yearYes
reprt_codeNo11011
fs_divNoOFS
statement_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal some behavioral traits: it's a fallback/supplemental tool, it returns current period data only ('당기 데이터만 표시'), and it returns text with detailed item information. However, it doesn't disclose important aspects like whether it's read-only, potential rate limits, authentication requirements, error handling, or what happens when parameters are invalid. The description adds some context but leaves significant gaps.

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 well-structured with purpose first, usage guidelines second, then parameter documentation, and finally return information. Each section is focused and adds value. While not extremely brief, every sentence serves a clear purpose. The parameter documentation is comprehensive but necessary given the poor schema coverage. The structure helps an agent quickly understand what the tool does and how to use it.

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

Completeness4/5

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

Given the complexity (5 parameters, financial data tool), no annotations, and no output schema, the description does a good job of providing necessary context. It explains the tool's purpose, when to use it, all parameters in detail, and what the return contains. The main gap is in behavioral aspects like error conditions, performance characteristics, or authentication needs. However, for a tool with this level of parameter complexity and no structured documentation support, the description provides substantial contextual information.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description fully compensates by providing comprehensive parameter documentation. Each of the 5 parameters gets clear explanations in Korean with examples and enum values where applicable. The description adds crucial semantic information beyond the bare schema, including format requirements (4-digit year), code mappings for reprt_code, statement_type options with their meanings, and the effect of null values. This is exactly what's needed when schema coverage is poor.

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: '회사의 재무 정보를 JSON API를 통해 제공하는 실패시 보완하는 보조 도구' (provides company financial information via JSON API as a fallback supplement). It specifies the resource (financial information) and method (JSON API), and distinguishes it from siblings by mentioning it's an alternative when search_disclosure and search_detailed_financial_data fail for pre-September 2023 data. However, it doesn't explicitly state the specific verb beyond '제공' (provide).

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

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool: 'search_disclosure, search_detailed_financial_data이 2023년 9월 이전 자료 분석에 실패했을 때 대안으로 활용' (use as an alternative when search_disclosure and search_detailed_financial_data fail for pre-September 2023 data analysis). It names specific sibling tools and gives a clear temporal boundary (before September 2023), making it easy for an agent to decide when to select this tool over alternatives.

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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