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bar_exam_search

[KEY REQUIRED · no credits, 60/day] 변호사시험(변시) 코퍼스를 검색합니다 — 15회 전 회차 2,340문항(선택형 2,250 + 사례형 45 + 기록형 45), 인용이 law.go.kr 검증을 통과한 금답안. 사건번호('2014도6992')·조문('형법 제310조')·키워드로 조회하면 회차·과목·문항번호·공식 정답·지문·인용 조문/판례와 링크를 돌려줍니다. / Search the Korean bar exam (변호사시험) corpus — all 15 rounds, 2,340 questions (2,250 MCQ + 45 case-type + 45 record-type) with gold-standard answers whose citations passed law.go.kr verification.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qYesDocket, statute article or keyword.
limitNoMax results (1-20, default 5).
roundNoFilter by exam round 1-15 (optional).
subjectNoFilter by subject: 공법 / 민사법 / 형사법 (optional).
client_tagNo선택. client_tag: 호출자 식별용, **응답에 영향 없음**(8~64자, 영숫자·_-.). 서버 로그에만 남아 호출을 골라 세는 데 씁니다. 형식이 어긋나면 무시합니다 — 거절하지 않습니다. 질의 본문에 섞지 마세요: 본문에 넣으면 질문의 일부가 되어 분류와 검증 결과가 달라집니다. / Optional caller label (8-64 chars). Logged only; never affects the response. Invalid values are ignored, not rejected. Do not put it in the query text — there it becomes part of the question.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / client_tag
      Added value: +{
+  "description": "선택. client_tag: 호출자 식별용, **응답에 영향 없음**(8~64자, 영숫자·_-.). 서버 로그에만 남아 호출을 골라 세는 데 씁니다. 형식이 어긋나면 무시합니다 — 거절하지 않습니다. 질의 본문에 섞지 마세요: 본문에 넣으면 질문의 일부가 되어 분류와 검증 결과가 달라집니다. / Optional caller label (8-64 chars). Logged only; never affects the response. Invalid values are ignored, not rejected. Do not put it in the query text — there it becomes part of the question.",
+  "type": "string"
+}
  2. Added

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: a key is required, a daily quota of 60 applies, citations have passed law.go.kr verification, and client_tag is logged-only and ignored if invalid (not rejected). It also warns that putting client_tag in the query text changes results. This goes beyond minimal disclosure, though it doesn't describe error handling or pagination behavior, which are minor gaps for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the most critical constraint ([KEY REQUIRED · no credits, 60/day]), then the corpus scope, then the return details. It includes both Korean and English translations, which is slightly redundant but not wasteful. It is structured and informative without excessive fluff, earning a solid score.

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?

With 5 parameters, no output schema, and no annotations, the description must cover both usage and returns. It enumerates the output fields (round, subject, question number, official answer, text, cited statutes/cases, links) and explains the client_tag edge case thoroughly. It does not explicitly describe result ordering, pagination, or how multiple matches are presented, but for a search tool with a limit parameter, the essentials are covered.

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 description coverage is 100%, so the baseline is 3. The description adds extra value by giving concrete examples for the 'q' parameter ('2014도6992', '형법 제310조') and by extensively clarifying the client_tag parameter's semantics: it never affects the response, is only logged for caller identification, is ignored if invalid rather than rejected, and must not be placed in the query text. This supplements the schema meaningfully.

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 clearly states a specific verb ('search') and resource (Korean bar exam corpus), with detailed content (15 rounds, 2,340 questions, breakdown by type) and a precise list of returned fields (round, subject, question number, official answer, text, cited statutes/cases, links). It distinguishes itself from siblings like lookup_statute or search by being specific to the bar exam corpus, making its purpose unmistakable.

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 gives clear context: it is for searching the bar exam corpus using docket numbers, statute articles, or keywords, and mentions the daily limit of 60 and key requirement. However, it does not explicitly state when to prefer this tool over siblings like lookup_precedent, lookup_statute, or search, nor does it mention any exclusions (e.g., when not to use). Thus it provides context but lacks explicit alternative guidance.

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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