law.go.kr이 제공하는 법정 서식·별표를 검색합니다 — 예: 특정 법률에 따른 신청서 서식. / Search official Korean statutory forms and appendix tables (별표·서식) served by law.go.kr.
| Name | Required | Description | Default |
|---|---|---|---|
| knd | No | Kind: 1 별표 · 2 서식 · 3 별지 · 4 별도 · 5 부록 (blank = all). | |
| limit | No | Max results (1-100, default 20). | |
| query | Yes | Form or statute name to search. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not mention behavioral traits such as read-only nature, potential rate limits, authentication requirements, or output behavior. The agent is left without explicit disclosure of side effects or access constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct, presented in two lines (Korean and English), with no redundant or extraneous content. It directly conveys the core purpose and an example without padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description should explain what the tool returns (e.g., list of forms, metadata, citations). It only mentions 'searches' without any indication of result format, pagination, or error handling, leaving the agent uninformed about expected outputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema descriptions for query, knd, and limit are present and clear. The description adds a contextual example of a query ('application form according to a specific law') which slightly enhances understanding, but it does not elaborate on the meaning of the knd enum values beyond the schema, so it adds limited incremental value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches official Korean statutory forms and appendix tables on law.go.kr, with a concrete example. This distinctly identifies the tool's purpose and differentiates it from sibling search tools that focus on statutes or other content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like lookup_statute or search. It lacks any indication of appropriate scenarios, limitations, or prerequisites, leaving the agent to infer usage from the tool's name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.
