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Lookup OTC Company

lookup_otc_ticker

Retrieve comprehensive OTC company data by ticker: CIK, SIC, financials, short interest, shell risk, and filing recency from SEC EDGAR and FINRA.

Instructions

Look up a single OTC-traded company by ticker symbol. Returns full company details including CIK, SIC code, financials (revenue, assets, net income), short interest, shell risk score, and filing recency score. Source: SEC EDGAR + FINRA.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesThe ticker symbol (e.g. ACME)

Implementation Reference

  • Handler function that looks up a single OTC company by ticker. Calls GET /api/v1/otc/{ticker}, handles 404 and other errors, returns company details as JSON.
      async ({ ticker }) => {
        const res = await apiGet<{ dataset: string; data: Record<string, unknown> }>(
          `/api/v1/otc/${encodeURIComponent(ticker.toUpperCase())}`,
        );
    
        if (!res.ok) {
          const msg =
            res.status === 404
              ? `Ticker ${ticker.toUpperCase()} not found in the OTC dataset.`
              : `API error (${res.status}): ${JSON.stringify(res.data)}`;
          return {
            content: [{ type: "text" as const, text: msg }],
            isError: res.status !== 404,
          };
        }
    
        return {
          content: [
            { type: "text" as const, text: JSON.stringify(res.data.data, null, 2) },
          ],
        };
      },
    );
  • Input schema using Zod: ticker is a required string of 1-10 letters.
    inputSchema: {
      ticker: z
        .string()
        .regex(/^[A-Za-z]{1,10}$/, "Ticker must be 1-10 letters")
        .describe("The ticker symbol (e.g. ACME)"),
    },
  • Tool registration via server.registerTool with name 'lookup_otc_ticker', including title, description, and input schema.
    server.registerTool(
      "lookup_otc_ticker",
      {
        title: "Lookup OTC Company",
        description:
          "Look up a single OTC-traded company by ticker symbol. Returns full company details " +
          "including CIK, SIC code, financials (revenue, assets, net income), short interest, " +
          "shell risk score, and filing recency score. Source: SEC EDGAR + FINRA.",
        inputSchema: {
          ticker: z
            .string()
            .regex(/^[A-Za-z]{1,10}$/, "Ticker must be 1-10 letters")
            .describe("The ticker symbol (e.g. ACME)"),
        },
      },
      async ({ ticker }) => {
        const res = await apiGet<{ dataset: string; data: Record<string, unknown> }>(
          `/api/v1/otc/${encodeURIComponent(ticker.toUpperCase())}`,
        );
    
        if (!res.ok) {
          const msg =
            res.status === 404
              ? `Ticker ${ticker.toUpperCase()} not found in the OTC dataset.`
              : `API error (${res.status}): ${JSON.stringify(res.data)}`;
          return {
            content: [{ type: "text" as const, text: msg }],
            isError: res.status !== 404,
          };
        }
    
        return {
          content: [
            { type: "text" as const, text: JSON.stringify(res.data.data, null, 2) },
          ],
        };
      },
    );
Behavior4/5

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

No annotations provided, so description carries full burden; it lists returned fields (CIK, SIC, financials, short interest, shell risk, filing recency) and sources, but lacks details on error handling, rate limits, or data freshness.

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

Conciseness5/5

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

Two sentences: first states purpose, second enumerates returned fields and sources. No fluff, front-loaded.

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?

No output schema; description lists key fields but may omit minor ones. Given moderate complexity and clear scope, it provides sufficient context for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 100% coverage for ticker parameter with pattern and description; description adds context that the ticker is for an OTC company and lists what is returned, adding value beyond schema.

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?

Clearly states action 'look up a single OTC-traded company by ticker symbol' and distinguishes from sibling tools like lookup_contract or lookup_label by specifying OTC domain and SEC/FINRA source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies use for single company lookup by ticker, but does not explicitly state when to use vs alternatives like query_otc_companies or how it differs from search_sec_companies.

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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