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meritz-securities

meritz-codegen

Official

search_api

Read-onlyIdempotent

Find Meritz Open APIs via natural language. Narrow by category for account, trading, forex, or locate auth endpoints using 'token' or 'oauth'.

Instructions

자연어로 API 를 찾습니다. 예: search_api('삼성전자 현재가'), search_api('매수'), search_api('실시간 체결통보'). category 로 좁힐 수 있습니다 (account·domestic_market·overseas_market·trading·forex·reference·realtime·oauth2). 인증(접근토큰 발급·폐기)은 '토큰'·'인증'·'oauth'·'revoke' 로 찾습니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keywordYes
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, and the description is consistent with this by saying it 'finds' APIs rather than performing actions. It adds useful behavioral context by describing natural-language querying, category narrowing, and auth-related search patterns, while avoiding any contradiction.

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 compact: two dense sentences with no filler. The main purpose is front-loaded, examples come immediately, and the category and auth guidance are packed into the remaining text without redundancy.

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?

Given an output schema exists and annotations cover the safety profile, the description covers the essentials: how to search, what categories are valid, and how to target auth-related APIs. The only notable omission is explicit guidance on when to use sibling tools like get_api_detail or list_categories.

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 description coverage is 0%, so the description must compensate. It does so well: keyword is illustrated with realistic example queries, and category is enriched with the full list of supported values. It does not formally define keyword beyond examples, but the examples are sufficient for practical use.

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 a specific verb and resource: it finds APIs using natural language, with concrete examples like '삼성전자 현재가' and '매수'. It does not explicitly differentiate itself from sibling tools like list_categories or get_api_detail, so it falls short of a 5.

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?

The description gives clear usage context: it explains that category can narrow results, lists the valid category values, and provides authentication-specific search keywords such as '토큰' and 'oauth'. It does not state when not to use this tool or mention alternative sibling tools, but the guidance is concrete and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.