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오류 제보·질문 기록

report_issue

오류·개선 제보, 그리고 원문 질문 기록(category="question_log").

**제보**: 사용자가 "틀렸다"고 지적하면 **먼저 이 도구로 제보한 뒤** 정정 답을 제시하라.
도구 결과가 조문·수치·판례와 명백히 불일치할 때도 제보하라. 추측으로 부르지 말 것.
서버가 직전 도구 호출 기록을 자동 첨부하므로 도구명·인자를 기억으로 적을 필요 없다.

**원문 질문 기록**(`category="question_log"`): 이 서버는 네가 이미 도구 호출로 번역한
뒤를 본다 — **사용자가 실제로 무엇을 물었는지 볼 수 없다.** "관공서 물품 살 때 수의계약
얼마까지 되나요?"가 `search_law(query="수의계약")`로 도착하면, 질문에 있던 '관공서'·
'물품 구매'라는 맥락은 우리에게 영영 안 남는다. 그 원문이 질문은행·평가셋·로드맵의
유일한 원천이다.
**응답이 `hint`로 기록을 요청하면 그때 남겨라** — 0건·범위 밖·부분 답변이 그런 자리다.
네가 스스로 "잘 답했다"고 느낀 경우까지 남길 필요는 없다. `message`에 원문을 넣되
**개인 식별 조합은 일반형으로 바꿔서** 넣는다(기관명·사건번호·금액 조합 등).

Args:
    category: "wrong_citation"(오인용) | "outdated_law"(개정 미반영) |
        "wrong_ruling"(룰엔진 오판정) | "tool_error"(도구 오류) |
        "feature_request"(기능 요청) | "question_log"(원문 질문 기록) | "other"
    message: 무엇이 어떻게 잘못됐는지 구체적으로. **question_log이면 사용자의 원문 질문**
    related_tool: 문제가 난 도구명 (예: "search_references")
    related_query: 문제를 재현하는 질의·입력
    expected: 올바르다고 생각하는 값·조문 (알고 있다면)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYes
categoryYes
expectedNo
related_toolNo
related_queryNo

TDQS

A4.9/5.0
Behavior5/5

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

With annotations all false and providing little safety context, the description carries the full burden and does so well. It discloses that the server auto-attaches prior tool-call history, that the server cannot see the user's original question after translation, and that personal identifying combinations must be generalized.

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 long but well-structured with bolded key terms and clear sections. Every paragraph adds necessary operational detail, though the question_log explanation is somewhat verbose. It is front-loaded with the core purpose and remains readable.

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?

Given the tool's complexity, zero output schema, and minimal annotations, the description is remarkably complete. It covers purpose, triggers, exclusions, privacy handling, server behavior, and parameter semantics, leaving no major operational gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains category values, message content requirements, related_tool with an example, related_query as a reproducing query, and expected as the believed-correct value or provision. This fully covers all five parameters.

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 identifies the tool as a reporting/logging mechanism for errors, improvements, and original question logs. It distinguishes itself from sibling legal-research tools by using specific verbs like '제보' and '기록' with explicit categories.

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: report before correcting when the user says something is wrong, report on clear mismatches with legal text, and log question_log only when the response hint requests it. It also states when NOT to use it ('네가 스스로 잘 답했다고 느낀 경우까지 남길 필요는 없다').

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

A4.6/5.0
Disambiguation4/5

Each tool has a distinct role: decision-rules, price adjustment, delay penalties, exemption guidance, statute retrieval, case retrieval, and three specialized search tools. search_law, search_references, and search_cases look similar at first glance, but their descriptions clearly separate statutory text, full reference corpus, and caselaw/interpretation. The main ambiguity is between search_law and search_references for mixed practical queries.

Naming Consistency4/5

Almost all tools follow a snake_case verb_noun pattern: check_price_adjustment, decide_contract_method, estimate_delay_penalty, get_law_article, search_references. delay_exemption_guide is the one name that leads with a noun rather than a verb, and get_law_article_asof adds an as-of suffix that is not mirrored elsewhere, but the overall style remains predictable.

Tool Count5/5

Eleven tools are well-scoped for a Korean public-contract advisory server: three rule calculators, one exemption guide, paired search/retrieval tools, an as-of law lookup, and a feedback/question-log tool. Each tool earns its place, and the count is neither bloated nor too thin.

Completeness4/5

The server covers the main contract lifecycle well: selecting contract method, price escalation, delay penalty calculation, and delay exemption guidance, backed by statutes, references, and caselaw retrieval. Some narrower lifecycle aspects such as termination, sanctions, or post-award administration are only reachable through general search rather than dedicated decision tools, which is a minor gap agents can work around.