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lawmadi-os

by io.github.peter120525-cmd

ask

한국 법률 질문에 답합니다. 60명의 전문 리더 중 한 명에게 자동 배정하고, 인용한 조문을 law.go.kr에서 실시간 검증한 분석을 돌려줍니다. 한국어·영어 모두 지원합니다. / Ask a Korean legal question. Routes to 1 of 60 specialist AI legal leaders and returns a statute-verified analysis (real-time law.go.kr check). Korean and English.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoResponse language. Auto-detected if omitted.
queryYesLegal question in Korean or English (max 2000 chars).
idempotency_keyNo선택. 재시도 안전 키(8~64자, 영숫자·_-.). 같은 키로 다시 부르면 **두 번 과금되지 않고** 보관된 답변을 그대로 돌려줍니다(24시간). 타임아웃·연결 끊김으로 응답을 못 받았을 때 같은 키로 재시도하세요. / Optional retry-safe key (8-64 chars). Retrying with the same key is never charged twice and replays the stored answer for 24h.

Schema Changelog

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

  1. Changed1 schema field changed
    • addedInput schema / properties / idempotency_key
      Added value: +{
+  "description": "선택. 재시도 안전 키(8~64자, 영숫자·_-.). 같은 키로 다시 부르면 **두 번 과금되지 않고** 보관된 답변을 그대로 돌려줍니다(24시간). 타임아웃·연결 끊김으로 응답을 못 받았을 때 같은 키로 재시도하세요. / Optional retry-safe key (8-64 chars). Retrying with the same key is never charged twice and replays the stored answer for 24h.",
+  "type": "string"
+}
  2. Added

TDQS

A3.6/5.0
Behavior4/5

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

There are no annotations, so the description carries the full transparency burden. It discloses non-obvious behavior: automatic routing to one of 60 specialists, real-time law.go.kr verification, and bilingual support. It does not describe response format or limitations, but it goes well beyond a generic question-answering statement.

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?

The description is compact and front-loaded, delivering purpose in the first sentence and workflow in the second. The bilingual repetition is justified for the tool's Korean/English audience, and every sentence earns its place.

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?

For a 3-parameter tool with full schema coverage and no output schema, the description provides sufficient operational context: routing, verification, and language behavior. It could add response shape or exclusion criteria, but it is not severely incomplete.

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

Parameters3/5

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

The input schema already documents all parameters with 100% coverage, so the baseline is 3. The description adds only the fact that Korean and English are supported, which maps to the lang parameter; it does not add further parameter-level meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Ask a Korean legal question' with a distinctive workflow of routing to 1 of 60 specialist AI legal leaders and returning a statute-verified analysis via real-time law.go.kr checks. It is specific and action-oriented, but it does not explicitly distinguish itself from overlapping sibling tools like ask_expert or chat_leader.

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

Usage Guidelines2/5

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

The description implies usage for Korean legal questions but provides no explicit when-to-use guidance or alternatives. With sibling tools like ask_expert, chat_leader, lookup_statute, and verify_citations, the description gives no basis for choosing among them.

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

A3.8/5.0
Disambiguation4/5

Most tools target clearly distinct resources (statutes, precedents, bar exam, documents, content, account), and cross-references in descriptions explicitly disambiguate similar actions like search vs lookup_statute vs lookup_precedent. A few close pairs exist (ask vs ask_expert, latest_content vs get_daily_content, bar_exam_search vs get_exam_answer), but each pair has clear differentiators.

Naming Consistency4/5

The set predominantly follows snake_case verb_noun naming (get_account, lookup_statute, verify_citations, generate_document). Minor deviations like latest_content (no verb) and bar_exam_search (noun-first) break the pattern, but the overall convention is readable and predictable.

Tool Count4/5

At 19 tools, the surface is on the heavier side but each tool addresses a distinct need across a broad legal domain (Q&A, research, document generation, bar exam corpus, content, account management). The count feels justified for the stated scope, though it approaches the upper boundary of reasonable.

Completeness4/5

The server covers the main legal workflows well: Q&A (ask, chat_leader), research (lookup_statute, lookup_precedent, search, verify_citations), document drafting (generate_document), and bar exam prep (bar_exam_search, get_exam_answer). Minor gaps exist, such as no browse/list-all endpoints for statutes or precedents and no way to manage generated documents, but agents can work around these.

Resources