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lawmadi-os

by io.github.peter120525-cmd

ask_expert

전문가 모드 법률 분석 — 전체 검증 파이프라인을 돌려 더 깊이 인용된 답변을 만듭니다. ask보다 느립니다. Pro 요금제 전용입니다(Pro 크레딧 팩 구매 시 활성화). 잔액만으로는 열리지 않으며, Pro가 아니면 2크레딧을 차감하지 않고 거절합니다 — 그 경우 ask(1크레딧)를 쓰세요. / Expert mode legal analysis — runs the full verification pipeline for a more detailed, deeply-cited answer. Slower than ask. Pro plan only (unlocked by buying the Pro credit pack); a positive balance alone is not enough. Non-Pro callers are refused without being charged — use ask (1 credit) instead.

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). 전문가 답변은 2크레딧이라 타임아웃 시 이 키가 특히 중요합니다. / 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). 전문가 답변은 2크레딧이라 타임아웃 시 이 키가 특히 중요합니다. / 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

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly states it is slower than `ask`, is Pro-only, requires a Pro credit pack (balance alone insufficient), charges 2 credits, and refuses non-Pro callers without charge. It also discloses idempotent behavior in the parameter description. This is excellent transparency beyond the schema.

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 compact, written in bilingual format (Korean and English), and front-loads the core purpose. It includes important caveats but avoids fluff. Slight redundancy from bilingual repetition, but the structure is clear and every sentence adds essential insight.

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?

Given that the tool has no output schema and complex multi-parameter behavior, the description and schema together are fairly complete. It covers the invocation semantics, error conditions (non-Pro refusal), credit cost, and idempotency. Minor gap: it doesn't describe the detailed response content or how to handle timeouts besides idempotency key, but it's adequate.

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?

The input schema has high coverage (100%) with detailed descriptions for each parameter. The description adds value by explaining the Pro requirement and credit cost, and the idempotency_key parameter description includes additional behavioral context (never charged twice, replays stored answer). This goes beyond a baseline 3, but since schema is already thorough, it doesn't reach 5.

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 it performs expert mode legal analysis with a deeper, verification pipeline for detailed, deeply-cited answers. It specifies the main action (run full verification pipeline) and resource (legal analysis), and explicitly contrasts with sibling `ask`, which helps distinguish it.

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 explicitly states when to use it (when deeper, more detailed answers are needed) and when not to (for non-Pro users, use `ask` instead). It also clarifies the Pro plan requirement and that non-Pro callers are refused without charge, which is critical usage 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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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