Skip to main content
Glama

lawmadi-os

by io.github.peter120525-cmd

generate_document

사용자의 사실관계로 한국 법률 문서 초안을 작성합니다(고소장·소장·내용증명·답변서·합의서·법률의견서 등). 초안의 모든 조문·판례 인용은 ask와 동일한 fail-closed law.go.kr 검증을 거칩니다. 유효한 doc_type 키는 list_document_types로 먼저 확인하세요. / Draft a Korean legal document from the user's facts. Every statute/precedent citation in the draft goes through the same fail-closed law.go.kr verification as ask. Use list_document_types first for valid doc_type keys.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoDefault ko.
contextYesThe user's facts/situation the document must be built from.
doc_typeYesDocument type key from list_document_types (e.g. 'complaint').
extra_instructionsNoOptional extra drafting instructions.

Schema Changelog

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

  1. Added

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the burden. It discloses that citations go through fail-closed law.go.kr verification and that invalid doc_type should be avoided by checking via list_document_types味的, but does not mention output format, potential errors, or edge cases. Adequate but not rich.

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?

Description is two bilingual sentences, front-loaded with purpose and crucial verification info. No fluff, efficient, though the bilingual repetition doubles length without adding new content.

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 4 simple params, no output schema, and no annotations, the description covers the key usage pattern (check doc_type) and informs about verification behavior. It lacks details on return format but that's minor given the tool's simplicity.

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?

Schema coverage is 100% with param descriptions, so baseline is 3. The description adds the crucial dependency on doc_type keys (from list_document_types) but does not elaborate on context, lang, or extra_instructions beyond schema. Neutral.

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 the tool drafts Korean legal documents from user facts, enumerating types (고소장·소장·내용증명 etc.), and distinguishes it from siblings like ask and list_document_types by specifying its unique drafting function.

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?

It explicitly instructs to use list_document_types first to obtain valid doc_type keys, giving clear context for proper usage. It does not mention when not to use this tool versus alternatives, but the drafting purpose is distinct enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All lawmadi-os toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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