품목 키워드로 전국 도매시장 경매 가격을 검색합니다.
Args:
product_keyword: 품목 키워드 (예: "사과", "딸기", "배추", "고추", "포도")
market_code: 도매시장 코드 (빈 문자열이면 전국 검색)
date: 정산일 (YYYY-MM-DD). 빈 문자열이면 오늘.
num_results: 조회 건수 (기본 100, 최대 1000)
Returns:
품목별 가격 정보 + 시장별 평균/최고/최저가 요약
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | ||
| market_code | No | ||
| num_results | No | ||
| product_keyword | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the disclosure burden. It does add useful behavior context: empty market_code/date semantics and num_results max of 1000. However, it does not mention read-only safety, authentication requirements, rate limits, or error behavior. 'Search' implies a read operation, but deeper behavioral transparency is limited.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured with Args and Returns sections. Every sentence adds value, and the purpose is front-loaded in the first line. No redundant or ambiguous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward search tool with an output schema, the description sufficiently covers purpose, parameters, and return summary. What's missing is explicit routing among sibling tools and any caveats about data coverage or latency, but overall it is nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description fully compensates by explaining every parameter in Korean: product_keyword with examples, market_code default meaning, date format and default, and num_results default/max. This adds substantial meaning beyond the raw schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: '검색합니다' (searches) '전국 도매시장 경매 가격' (nationwide wholesale market auction prices) by product keyword. This clearly identifies the tool's function, though it does not explicitly differentiate from sibling tools like get_realtime_auction or get_price_trend.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is only implied through the description and parameter defaults (e.g., empty market_code means nationwide, empty date means today). There is no explicit guidance on when to use this tool versus alternatives such as compare_market_prices, get_price_trend, or get_auction_summary.
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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