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NeuralVerge Business Intelligence

South Korea companies search

run_kr_companies_search

Search the South Korea company registry (DART) by company name or stock code: name, DART corp code, market, stock code and link. 1 point per returned record.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYesCompany name. e.g. 삼성전자
max_itemsNoMax items (up to 250) Default: 25.
start_pageNoStarting page

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden, and it does add one genuinely useful non-schema fact: '1 point per returned record' discloses the cost model. However, it says nothing about pagination behavior, empty-result behavior, or whether a failed search still charges, which matters for a paid search endpoint.

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?

Two tight clauses: what is searched and returned, then the cost. The key fact (registry + search keys) is front-loaded and every sentence earns its place.

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?

With no output schema, the description correctly enumerates the returned fields (name, DART corp code, market, stock code, link), and it covers cost. Only the pagination interaction between start_page and max_items is left entirely to the schema.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline would be 3, but the description adds meaning the schema lacks: keyword accepts a stock code as well as a company name, whereas the schema description only says 'Company name'. That is a real clarification beyond the structured fields.

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: searching the South Korean company registry (DART), plus the search keys (company name or stock code) and the returned fields. It is clear what the tool does, but it never explicitly distinguishes itself from the sibling run_kr_companies (lookup) or run_kr_company_filings.

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 'by company name or stock code' implies the input mode and therefore the usage context, but there is no explicit when-to-use statement, no exclusions, and no pointer to the alternative run_kr_companies or run_kr_company_filings tools.

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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