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ClawyPro

Clawy MCP Server

by ClawyPro

dart_disclosure

Search Korean corporate disclosures from DART/FSS to find filings by company code, name, or keyword for listed and unlisted companies.

Instructions

Search Korean corporate disclosures (DART/FSS). Find filings by company code, name, or keyword. Covers listed and unlisted Korean companies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
corp_codeNoDART corporation code (8 digits)
corp_nameNoCompany name (Korean or English)
keywordNoSearch keyword for disclosure title
bgn_deNoStart date (YYYYMMDD)
end_deNoEnd date (YYYYMMDD)
page_countNoResults per page (default 10, max 100)

Implementation Reference

  • The generic tool registration loop in src/index.ts uses the 'endpoint' property defined in the tool schemas (like src/tools/dart.ts) to execute requests via 'gatewayRequest'. The 'dart_disclosure' tool is registered here along with all other tools in 'allTools'.
    // Register all tools
    for (const tool of allTools) {
      server.tool(
        tool.name,
        tool.description,
        tool.inputSchema.shape,
        async (params) => {
          const method = tool.method || "POST";
          const result = await gatewayRequest(method, tool.endpoint, params as Record<string, unknown>);
    
          if (result.error) {
            return {
              content: [{ type: "text" as const, text: `Error (${result.status}): ${result.error}` }],
              isError: true,
            };
          }
    
          const text = typeof result.data === "string"
            ? result.data
            : JSON.stringify(result.data, null, 2);
    
          return {
            content: [{ type: "text" as const, text }],
          };
        },
      );
    }
  • Definition of the 'dart_disclosure' tool, including its schema, description, and the endpoint used for the API request.
    {
      name: "dart_disclosure",
      description: "Search Korean corporate disclosures (DART/FSS). Find filings by company code, name, or keyword. Covers listed and unlisted Korean companies.",
      inputSchema: z.object({
        corp_code: z.string().optional().describe("DART corporation code (8 digits)"),
        corp_name: z.string().optional().describe("Company name (Korean or English)"),
        keyword: z.string().optional().describe("Search keyword for disclosure title"),
        bgn_de: z.string().optional().describe("Start date (YYYYMMDD)"),
        end_de: z.string().optional().describe("End date (YYYYMMDD)"),
        page_count: z.number().optional().describe("Results per page (default 10, max 100)"),
      }),
      endpoint: "/v1/dart/disclosure",
    },
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool is for searching disclosures but doesn't cover key behavioral traits such as whether it's read-only or mutative, authentication requirements, rate limits, pagination behavior, or error handling. For a search tool with zero annotation coverage, this leaves critical information gaps.

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 concise and well-structured in two sentences, with no wasted words. It front-loads the core purpose and efficiently covers scope. However, it could be slightly improved by integrating more behavioral details without losing conciseness.

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 complexity of a search tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It lacks information on behavioral traits, usage guidelines, and output format, which are essential for effective tool invocation. The description does not compensate for the absence of structured data, leaving significant gaps.

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 description coverage is 100%, meaning all parameters are documented in the input schema. The description adds minimal value beyond this, mentioning search by 'company code, name, or keyword' which aligns with the schema but doesn't provide additional syntax, format details, or usage examples. The baseline score of 3 is appropriate when the schema does the heavy lifting.

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's purpose: 'Search Korean corporate disclosures (DART/FSS). Find filings by company code, name, or keyword.' It specifies the verb ('search'), resource ('Korean corporate disclosures'), and scope ('covers listed and unlisted Korean companies'). However, it doesn't explicitly differentiate from sibling tools like 'dart_financial' or other search tools, keeping it from a perfect score.

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. It mentions the scope ('covers listed and unlisted Korean companies') but doesn't specify use cases, prerequisites, or exclusions. With sibling tools like 'dart_financial' and other search tools present, this lack of comparative guidance is a significant gap.

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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