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DART 재무제표 분석 MCP 서버

by keioseung

generate_financial_chart

Create text-based financial charts for specific metrics like revenue, net income, or debt-to-equity by analyzing DART API data for multiple companies and reporting years.

Instructions

특정 재무 지표에 대한 텍스트 차트를 생성합니다

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
corp_codesYes분석할 회사들의 고유번호 목록
metricYes차트로 표시할 지표 (revenue, netIncome, totalAssets, totalEquity, debtToEquity, returnOnEquity, profitMargin)
report_codeYes보고서 코드
yearYes분석할 사업연도
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. It mentions generating a 'text chart' but doesn't specify output format, size limits, error handling, or performance characteristics. For a tool with 4 required parameters and no output schema, this lack of behavioral detail is a significant gap.

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 sentence in Korean that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 complexity of 4 required parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what a 'text chart' entails, how results are returned, or any prerequisites, leaving critical gaps for effective tool use in a financial context.

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 input schema fully documents all parameters. The description adds no additional semantic context beyond implying that parameters define the chart's content. This meets the baseline for high schema coverage but doesn't enhance understanding of parameter interactions 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 action ('generate') and resource ('text chart for specific financial metrics'), making the purpose understandable. However, it doesn't distinguish this tool from its siblings like 'generate_financial_dashboard' or 'generate_comparison_table', which likely serve similar visualization purposes.

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 siblings like 'analyze_financial_data' and 'generate_comparison_table', there's no indication of whether this is for quick summaries, detailed analysis, or specific contexts, leaving usage ambiguous.

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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