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na_search

Read-only

Search the National Assembly Library of Korea's databases for books, theses, articles, and more, with options to filter by database type and apply search conditions.

Instructions

[자료검색] 국회도서관의 도서·학위논문·국내외 기사 등 목록DB를 검색한다.

search: 검색항목,키워드 형식이 필수다(그냥 키워드만 넣으면 오류). | 로 여러 개를 연결하면 AND 로 묶인다. 예: 전체,교육|자료명,불평등. OR(합집합)이 필요하면 na_collect(terms=[…]) 를 쓸 것 — 이 API 에 OR 문법은 없다.

검색항목(통합검색 전용 7종): 기본검색 · 전체 · 자료명 · 저자 · 발행자 · 키워드 · 청구기호 🔴 그 밖의 값을 쓰면 오류가 나지 않고 검색어가 통째로 무시되어 전체 카탈로그 13,097,591건이 반환된다. 특히 저자명 은 상세검색(dbname 지정 시)에서는 유효한 이름이라 헷갈리기 쉽다 — 통합검색에서는 반드시 저자 를 쓸 것. 이 도구는 화이트리스트로 미리 막고 오류를 돌려준다.

dbname: 지정하면 상세검색(/detail)으로 전환된다. 21종 중 정확한 문자열이어야 한다: 일반도서 · E-BOOK · 고서 · 세미나자료 · 웹자료 · 학위논문 · 국내기사 · 국외기사 · 학술지,잡지 · 신문 · 전자저널 · 동영상자료 · 오디오자료 · 전자매체 · 마이크로폼자료 · 지도/기타자료 · 외국법률번역DB · 국회회의록 · 국회의안정보 · 표,그림DB · 지식공유 🔴 상세검색은 검색항목 어휘가 DB마다 다르고(학위논문=논문명, 일반도서=자료명, 국내기사=기사명, 국회의안정보=의안명, 국회회의록=안건 …) 통합검색과 달리 틀리면 ERR04 로 실패한다(실측). 이 도구가 호출 전에 검증해 막으므로 정확한 어휘는 na_fields 로 확인할 것.

option: 상세검색 전용. 발행년도,2000|발행년도,2010 (하나면 그 해부터 현재까지, 둘이면 between), 원문유무,1(유)/0(무).

page_size: 한 페이지 건수(최대 1000). 기본은 최대치. max_records: 최대 회수 건수.

⚠️ 회수 한계 99,000건pageno 가 최대 99이고 페이지당 최대 1000건이다(실측). total 이 이를 넘으면 응답의 cap_hit 이 참이 되고, 그때는 max_records 를 올려도 더 받을 수 없다(검색식을 쪼개야 한다). truncated 는 max_records 를 올리면 해결된다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dbnameNo
optionNo
searchYes
page_sizeNo
max_recordsNo
extra_paramsNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.1

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnlyHint and openWorldHint annotations, the description discloses critical behaviors: invalid search-field values silently return the entire 13,097,591-record catalog, dbname mismatches fail with ERR04, and the API caps retrieval at 99,000 records via pageno 99 and page_size 1000. It also explains cap_hit and truncated semantics.

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?

Although long, the description is densely informative and well-structured: purpose first, then search syntax, field whitelist, dbname behavior, option syntax, paging, and limits. Warnings and examples are placed exactly where confusion would occur, and no sentence is filler.

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 nearly every operational constraint needed to invoke this complex tool correctly, including validation behavior, pagination limits, and response flags. It falls slightly short by not describing extra_params and not summarizing the general result shape, especially since there is no output schema.

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?

With 0% schema description coverage, this description fully compensates for search, dbname, option, page_size, and max_records, including required formats, allowed values, defaults, and failure modes. The only gap is extra_params, which appears in the schema but is never explained in the description.

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 first sentence names a specific action and resource: searching the National Assembly Library catalog DB for books, theses, and articles. It further distinguishes this tool from siblings by explicitly routing OR needs to na_collect and field-vocabulary checks to na_fields.

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?

The description gives explicit when-to-use guidance: use na_collect when OR semantics are needed, use na_fields to confirm valid field names for detailed search, and use dbname to switch to detailed search. It also explains what happens if the documented format is not followed.

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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