검색 결과의 콘텐츠 ID로 상세 정보(운영시간·주소·연락처·이미지·일정 등)를 조회한다. language로 번역 버전을 가져온다. 요청 언어판이 없으면 한국어로 대체한다.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | 콘텐츠 ID (search_contents 결과의 id) | |
| language | No | 언어. ko(기본)/en/ja/zh-CN/zh-TW/ru/ms |
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?
Annotations already declare readOnlyHint=true, so the tool is safe. The description adds transparency about behavior: it retrieves details and provides language fallback to Korean if the requested version is unavailable. This extra context justifies a score of 4.
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 two short sentences that are front-loaded with the primary action, then secondary detail. No redundant information; every sentence adds value.
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?
Given no output schema, the description lists the types of information returned (hours, address, etc.) and handles language behavior. It provides sufficient context for an agent to understand what to expect, though a sample response could further improve completeness.
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 100% with descriptions for both parameters. The description adds value by clarifying that 'id' comes from search_contents results and explaining the language fallback logic, which goes beyond what the schema provides.
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 clearly specifies the action: retrieve detailed information (business hours, address, contact, images, schedule) by content ID from search results. It distinguishes from sibling tools like search_contents (searching) and get_sync_status (sync status), making the tool's purpose unambiguous.
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?
The description indicates the tool is used after a search (by referencing 'search_contents result') and explains language fallback behavior. However, it does not explicitly state when not to use it or mention alternatives, though the context is sufficient for basic guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool serves a unique, clearly distinct purpose: search_contents for searching, get_content_detail for retrieving detailed info by ID, and get_sync_status for checking data freshness. No overlap in functionality.
Tool names follow a consistent verb_noun pattern with snake_case: search_contents, get_content_detail, get_sync_status. The pattern is predictable and intuitive.
With 3 tools, the set is slightly small but appropriate for a focused tourism data query service. Each tool is essential and covers core operations without unnecessary bloat.
The tools cover the primary use cases: searching by various filters, getting detailed content, and checking data sync status. Minor gaps exist (e.g., no direct listing of categories or recommendations), but the core information retrieval workflow is complete.