get_mbti_horoscope'MBTI 운세', '오늘 내 MBTI 운세', 'ENFP 운세'처럼 MBTI 기반 오늘의 운세를 물을 때 사용합니다. 운세 내용은 포함하지 않고 제목·발행일·원문 링크만 반환하며, 운세 본문은 다른 기사와 동일하게 item.url 의 한국일보 원문에서만 확인할 수 있습니다. 기본은 오늘(한국 시간), date(YYYY-MM-DD)로 특정 날짜 지정 가능.
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | 조회할 날짜(YYYY-MM-DD). 생략 시 오늘(한국 시간) 운세. |
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | 반환된 운세의 발행 일시. | |
| item | No | 운세 기사 카드(메타데이터·원문 링크만, 운세 내용 미포함). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations declare readOnlyHint and openWorldHint. Description adds behavioral details: only returns metadata (title, date, link), default date is today (Korean time), allows custom date. This adds value beyond annotations.
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?
Two sentences, front-loaded with examples, no redundant words. Every sentence serves a purpose: query examples, return limitations, date parameter explanation.
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?
Tool is simple with one optional parameter. Description covers what the tool does, what it returns, and constraints. Output schema exists, so return values are fully documented. No gaps.
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 has 100% coverage with description for the date parameter. Description further explains default behavior (today Korean time) and format (YYYY-MM-DD).
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?
Description opens with specific query examples ('MBTI 운세', '오늘 내 MBTI 운세', 'ENFP 운세') and clearly states the tool is for MBTI-based daily horoscope. It distinguishes from sibling tools like get_daily_horoscope by explicitly scoping to MBTI.
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?
Describes when to use the tool: when querying MBTI horoscope. Provides context on what it returns (title, date, link) and what it does not (full content). Lacks explicit 'when not to use' but context is clear and no alternatives need exclusion.
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 targets a distinct purpose: horoscopes (daily vs MBTI), news listings (latest, most read, popular, recommended, timely, top headlines), sections, and search. Descriptions provide clear usage examples and explicitly differentiate similar-sounding tools like list_most_read_news (editor-curated) vs list_popular_news (view-count based).
All tool names follow a consistent verb_noun pattern in snake_case: get_ for horoscopes, list_ for various news lists and sections, and search_ for search. No mixing of camelCase or other conventions.
10 tools is appropriate for a news server. It covers the main news consumption patterns (latest, popular, recommended, by section, search) plus two specialized horoscope tools. Neither too sparse nor overwhelming.
The tool surface covers typical news site operations: browsing latest, popular (both view-based and editor-curated), by category, headlines, time-based recommendations, and search. Horoscope retrieval is an extra feature. The missing article text retrieval is intentional (metadata-only return). No obvious gaps for the intended domain.