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get_nlrc_decision_text

Retrieve the full text of a Korean National Labor Relations Commission decision by providing its serial number.

Instructions

[노동위] 노동위 결정문 전문.

Input Schema

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

Implementation Reference

  • Tool registration: registers 'get_nlrc_decision_text' with its schema and handler function in the tool registry.
    {
      name: "get_nlrc_decision_text",
      description: "[노동위] 노동위 결정문 전문.",
      schema: getNlrcDecisionTextSchema,
      handler: getNlrcDecisionText
    },
  • Schema definition for get_nlrc_decision_text input: requires 'id' (string) and optional 'apiKey' (string) via baseTextSchema.
    export const getNlrcDecisionTextSchema = z.object(baseTextSchema);
    export type GetNlrcDecisionTextInput = z.infer<typeof getNlrcDecisionTextSchema>;
  • Handler function for get_nlrc_decision_text. Delegates to getCommitteeDecisionText with target='nlrc' and committeeName='중앙노동위원회 결정문'.
    export async function getNlrcDecisionText(
      apiClient: LawApiClient,
      args: GetNlrcDecisionTextInput
    ): Promise<{ content: Array<{ type: string, text: string }>, isError?: boolean }> {
      return getCommitteeDecisionText(apiClient, args, "nlrc", "중앙노동위원회 결정문");
    }
  • Core helper getCommitteeDecisionText: fetches full decision text from the lawService.do API, parses JSON, and formats the output with basic info, judgment, summary, reasoning, referenced statutes, and full text.
    async function getCommitteeDecisionText(
      apiClient: LawApiClient,
      args: { id: string; apiKey?: string },
      target: string,
      committeeName: string
    ): Promise<{ content: Array<{ type: string, text: string }>, isError?: boolean }> {
      try {
        const responseText = await apiClient.fetchApi({
          endpoint: "lawService.do",
          target,
          type: "JSON",
          extraParams: { ID: args.id },
          apiKey: args.apiKey,
        });
    
        let data: any;
        try {
          data = JSON.parse(responseText);
        } catch (err) {
          throw new Error("Failed to parse JSON response from API");
        }
    
        const serviceKey = getServiceKey(target);
        if (!data[serviceKey]) {
          throw new Error(`${committeeName}을(를) 찾을 수 없거나 응답 형식이 올바르지 않습니다.`);
        }
    
        const decision = data[serviceKey];
    
        let output = `=== ${decision.사건명 || committeeName} ===\n\n`;
    
        output += `📋 기본 정보:\n`;
        output += `  사건번호: ${decision.사건번호 || "N/A"}\n`;
        output += `  결정일자: ${decision.결정일자 || "N/A"}\n`;
        output += `  결정유형: ${decision.결정유형 || "N/A"}\n`;
        if (decision.당사자) output += `  당사자: ${decision.당사자}\n`;
        if (decision.피심인) output += `  피심인: ${decision.피심인}\n`;
        output += `\n`;
    
        if (decision.주문) {
          output += `📌 주문:\n${decision.주문}\n\n`;
        }
    
        if (decision.결정요지 || decision.요지) {
          output += `📝 결정요지:\n${decision.결정요지 || decision.요지}\n\n`;
        }
    
        if (decision.이유) {
          output += `📄 이유:\n${decision.이유}\n\n`;
        }
    
        if (decision.참조조문) {
          output += `📖 참조조문:\n${decision.참조조문}\n\n`;
        }
    
        if (decision.결정내용 || decision.전문) {
          output += `📄 전문:\n${decision.결정내용 || decision.전문}\n`;
        }
    
        return {
          content: [{
            type: "text",
            text: truncateResponse(output)
          }]
        };
      } catch (error) {
        return formatToolError(error, `get_${target}_decision_text`);
      }
    }
  • Tool chain configuration: maps search_nlrc_decisions to get_nlrc_decision_text for automatic detail lookup from search results.
    search_nlrc_decisions: {
      detailTool: "get_nlrc_decision_text",
      detailParam: "id",
      idRegex: BRACKET_ID,
    },
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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