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Korean company profile: DART registry data joined with its public-procurement vendor record

kr_company_profile

Use when an agent needs a normalized profile of a South Korean company for KYB, research or sales. Input: id (companyId from /v1/kr/company/resolve). Output: JSON profile: names, business/corporate/DART/stock ids, market, KSIC code, founding date, fiscal year end, address, homepage, KONEPS supplier registration. No CEO names. DART data is a weekly snapshot of KRX-listed companies (asOf in response). Data: OpenDART, KONEPS. Example: ?id=kr-dart-00126380 Price: $0.0045 USDC (Base or Solana) via x402.

Input Schema

NameRequiredDescriptionDefault
idYescompanyId from /v1/kr/company/resolve

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden and does well: it discloses the data staleness ('weekly snapshot of KRX-listed companies, asOf in response'), a scope limitation ('No CEO names'), the upstream sources (OpenDART, KONEPS), and the metered cost/payment rail. It omits auth/rate-limit behavior, keeping it out of the 5 range.

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?

Front-loaded with the usage trigger, then Input/Output, then sources, example, and price in a dense but scannable label-value structure. Every sentence carries information, though the run-on packing is slightly list-like rather than prose-clean.

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

Completeness5/5

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

No output schema exists, so the description must describe return values, and it enumerates the profile fields (names, business/corporate/DART/stock ids, market, KSIC, founding date, fiscal year end, address, homepage, KONEPS registration) plus the asOf freshness field. Nothing needed to call or interpret this single-purpose tool is missing.

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 is 3, but the description adds real value: it names the parameter, ties it to the producing endpoint (companyId from /v1/kr/company/resolve), and supplies a concrete example value (?id=kr-dart-00126380) that clarifies the expected format.

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

Purpose5/5

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

States a specific verb + resource ('normalized profile of a South Korean company') and distinguishes itself from the adjacent siblings kr_company_resolve (supplies the id) and kr_company_procurement (different data slice). An agent can route to it without opening the schema.

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

Usage Guidelines4/5

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

Explicitly names the trigger context ('for KYB, research or sales') and points to /v1/kr/company/resolve as the prerequisite for the id. It stops short of naming when-not-to-use or the alternative sibling tools (resolve, procurement), so 4 rather than 5.

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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