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AIAgentStudy

korea-shopping-mcp

by AIAgentStudy

결과 로컬 저장

save_results

Save recent or selected search, comparison, and trend results to local Markdown or JSON files. Ideal for wishlists and record keeping.

Instructions

직전(또는 resultId로 지정한) 검색/비교/트렌드 결과를 마크다운 또는 JSON 파일로 로컬에 저장합니다. 위시리스트/기록 용도로 사용하세요.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNo저장 형식 (기본 markdown)markdown
filenameNo파일명(확장자 생략 가능). 생략 시 자동 생성
resultIdNo저장할 결과 id(예: search-1). 생략 시 가장 최근 결과를 저장
Behavior3/5

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

The description adds behavioral context beyond annotations by explaining the result selection logic (most recent or specified by resultId) and the file saving action. However, it does not disclose potential side effects such as overwriting existing files, behavior when no result exists, or return values. Annotations only provide readOnlyHint=false, which is already implied by 'saves', so the description adds limited new behavioral detail.

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 two sentences long, with the first sentence front-loading the core function and the second providing the intended use case. Every word is purposeful, with no redundant or vague phrasing, making it highly concise and well-structured.

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?

The description covers the tool's purpose, result selection logic, output formats, and use case, which is sufficient for an agent to understand how to invoke it. It lacks details about error handling, return values, or overwriting behavior, but given the simple nature of the tool and the comprehensive schema descriptions, the description is adequately complete.

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?

The input schema already provides 100% coverage with descriptions for all three parameters, including format, filename, and resultId. The tool description mentions '직전(또는 resultId로 지정한)' which aligns with the resultId schema description, but does not add any additional parameter semantics beyond what the schema already states.

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?

The description states a specific verb ('저장합니다' - saves) and resource (search/comparison/trend results) to a local file, with explicit formats (markdown or JSON). This clearly distinguishes it from sibling tools like search_products, compare_products, and shopping_trends, which generate results rather than save them.

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 explicitly says '위시리스트/기록 용도로 사용하세요' (use for wishlist/record purposes), giving a clear context for when to use the tool. It does not explicitly mention when not to use it or name alternatives, but the intended use case is specific and helpful.

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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