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ChangooLee

MCP OpenDART

by ChangooLee

get_unregistered_exec_compensation

Retrieve compensation details for unregistered executives to analyze insider compensation transparency and control risks in South Korean corporations using OpenDART financial data.

Instructions

미등기임원 보수 내역을 통한 내부자 보상 투명성 및 통제 리스크 분석

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
corp_codeYes고유번호 (8자리)
bsns_yearYes사업연도 (예: 2024)
reprt_codeYes보고서코드 (11011: 사업보고서, 11012: 반기보고서, 11013: 1분기, 11014: 3분기)
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a read-only analysis function but doesn't disclose output format, data sources, rate limits, or error conditions. The phrase '투명성 및 통제 리스크 분석' suggests analytical processing, but specifics are missing.

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 a single, efficient sentence in Korean that conveys the core purpose without unnecessary words. It's front-loaded with key terms ('미등기임원 보수 내역') but could be slightly more structured for clarity.

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 tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on what the analysis entails, expected outputs, or how results are formatted. Given the complexity implied by 'analysis' and the absence of structured behavioral data, more context is needed.

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 parameters are well-documented in the schema. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain how parameters relate to the analysis). Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool analyzes 'internal compensation transparency and control risk' through 'unregistered executive compensation details', which provides a general purpose. However, it lacks a specific action verb (e.g., 'retrieve', 'fetch', 'analyze') and doesn't clearly distinguish from sibling tools like 'get_executive_compensation_approved' or 'get_executive_compensation_by_type', making it somewhat vague.

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?

No explicit guidance is provided on when to use this tool versus alternatives. The description mentions analysis but doesn't specify contexts, prerequisites, or exclusions. Users must infer usage from the tool name and parameters 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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