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NeuralVerge Business Intelligence

South Korea company

run_kr_companies

Get one company from the South Korea registry (DART) by DART corp code, stock code or registry link: name, English name, market, registration numbers, address, industry, established date, representatives, name history and representative history. 15 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyYesDART corp code, stock code or registry URL. e.g. 00126380

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden, and it does add real behavioral context: a per-record cost ('15 point per returned record') and a full inventory of the fields returned. It omits auth requirements and error behavior, but the cost and output disclosure are genuinely valuable and unusual.

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?

Two sentences, front-loaded with the action and the identifier, then the cost. The long field enumeration is informative but slightly dense; nothing is wasted, though it could be trimmed.

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?

There is no output schema, so the description correctly compensates by listing the returned fields, and it discloses the cost. For a single-identifier read tool the description is largely self-sufficient, though it does not mention the search sibling or failure modes.

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%, and the schema already documents the single 'company' parameter as 'DART corp code, stock code or registry URL' with an example. The description restates the same three accepted identifier forms without adding format or validation detail, so the baseline 3 applies.

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?

States a specific verb and resource ('Get one company from the South Korea registry (DART)') and enumerates the returned fields, making it clear this is a single-record lookup rather than a search. It never names the sibling run_kr_companies_search, so the differentiation from it is only implicit.

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

Usage Guidelines3/5

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

The phrase 'Get one company ... by DART corp code, stock code or registry link' implies the lookup use case, and a reader can infer this is for single-record retrieval rather than bulk discovery. However, no when-to-use condition, prerequisites, or alternative (e.g. run_kr_companies_search) is stated, leaving routing to inference.

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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