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korean-law-alio-mcp

korean-law-alio-mcp

by scvcoder
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Hybrid

get_nlrc_decision_text

Retrieve the complete text of a Korean labor relations commission decision using its unique serial number.

Instructions

[노동위] 노동위 결정문 전문.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "get_nlrc_decision_text"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYes결정문 일련번호 (검색 결과에서 획득)
apiKeyNo법제처 Open API 인증키(OC). 사용자가 제공한 경우 전달

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It only states the tool fetches text, omitting whether it is read-only, requires an API key (though schema mentions it), or any side effects. This is insufficient for safe invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but lacks structure (e.g., no bullet points or additional context). It serves the minimal purpose but does not earn extra points for efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of output schema and annotations, and the presence of many sibling tools, the description is too brief. It does not explain the return format, how to obtain the id, or any edge cases, leaving the agent with insufficient context for correct invocation.

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 has 100% description coverage, with clear Korean explanations for both parameters. The tool description adds no additional meaning beyond the schema, so a baseline score of 3 is appropriate.

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 retrieves the full text of a Labor Commission decision ([노동위] 노동위 결정문 전문). This verb+resource combination is specific and, combined with the tool name, distinguishes it from siblings that handle other decision types (e.g., get_acr_decision_text). However, it does not explicitly contrast with similar tools.

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 provides no guidance on when to use this tool versus alternatives like get_acr_decision_text or search_nlrc_decisions. There is no mention of prerequisites or typical use cases, leaving the agent to infer from the name alone.

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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