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한국일보 뉴스 (Hankookilbo)

분야별 편집부 추천 기사

list_recommended_articles
Read-only

특정 분야(정치·경제·사회 등)에서 '편집부가 추천하는/읽을 만한 기사'를 물을 때 사용합니다. 반환 목록은 조회수 인기 순위가 아니라 편집 추천이며, 순위(랭킹) 값을 갖지 않습니다. '많이 본/핫한/인기' 기사는 list_popular_news 를 쓰세요. 분야 코드는 list_sections 로 확인합니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
page_sizeNo가져올 기사 수(1~최대치로 클램프).
section_cdYes섹션 코드 슬러그(소문자). list_sections 로 확인. 예: politics, economy, opinion.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo페이징 메타데이터(있을 때).
itemsNo기사 카드 목록.

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true. Description adds context that the list is not popularity-ranked and has no ranking values, clarifying output nature.

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?

Two concise sentences plus a sibling reference. Front-loaded with purpose, no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With output schema present and simple parameter set, the description covers purpose, exclusion of popularity ranking, and sibling tool guidance. Complete for the tool's complexity.

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 has 100% coverage with descriptions. Description reinforces section_cd usage by referencing list_sections, adding value beyond schema.

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 explicitly states the tool returns editorial recommendations for a specific section, distinguishing it from popularity-based lists. It includes clear verb ('사용합니다') and resource ('추천 기사').

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use (editorial recommendations) and when-not-to-use (popular articles, directing to list_popular_news). Also advises checking section codes via list_sections.

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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TDQS

A4.4/5.0
Disambiguation5/5

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).

Naming Consistency5/5

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.

Tool Count5/5

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.

Completeness5/5

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.