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job_status

Check the status of async web data jobs like crawls using the job ID. Monitor progress and completion for data gathering tasks.

Instructions

Check the status of an async job (e.g. crawl). Costs 0 credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesJob ID returned by crawl or other async endpoints

Implementation Reference

  • The handler for the 'job_status' tool. It takes a job_id parameter and fetches the job status via apiGet, returning the result as JSON content.
    server.tool(
      "job_status",
      "Check the status of an async job (e.g. crawl). Costs 0 credits.",
      { job_id: z.string().describe("Job ID returned by crawl or other async endpoints") },
      async ({ job_id }) => jsonResult(await apiGet(`/jobs/${job_id}`))
    );
  • Input schema for 'job_status' tool using Zod: defines job_id as a required string parameter with a description.
    { job_id: z.string().describe("Job ID returned by crawl or other async endpoints") },
  • src/index.ts:159-164 (registration)
    Registration of the 'job_status' tool with the MCP server, including name, description, schema, and handler function.
    server.tool(
      "job_status",
      "Check the status of an async job (e.g. crawl). Costs 0 credits.",
      { job_id: z.string().describe("Job ID returned by crawl or other async endpoints") },
      async ({ job_id }) => jsonResult(await apiGet(`/jobs/${job_id}`))
    );
  • Helper function apiGet that performs HTTP GET requests to the SearchClaw API with timeout handling and error management.
    async function apiGet(path: string, params?: Record<string, string>) {
      const url = new URL(`${API_BASE}${path}`);
      if (params) {
        for (const [key, value] of Object.entries(params)) {
          url.searchParams.set(key, value);
        }
      }
      const controller = new AbortController();
      const timeout = setTimeout(() => controller.abort(), 30000);
      try {
        const response = await fetch(url.toString(), { headers, signal: controller.signal });
        if (!response.ok) {
          const text = await response.text();
          throw new Error(`SearchClaw API error ${response.status}: ${text}`);
        }
        return response.json();
      } finally {
        clearTimeout(timeout);
      }
    }
  • Helper function jsonResult that formats API responses as MCP text content with JSON serialization.
    function jsonResult(data: unknown) {
      return { content: [{ type: "text" as const, text: JSON.stringify(data, null, 2) }] };
    }
Behavior4/5

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

With no annotations provided, the description carries the full burden and adds valuable behavioral context: it specifies that the tool 'Costs 0 credits', which is a key operational detail not inferable from the schema. However, it lacks information on rate limits, error handling, or response format.

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?

The description is front-loaded with the core purpose and includes only essential additional information ('Costs 0 credits'). It consists of two concise sentences with zero waste, making it highly efficient and easy to parse.

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 the tool's low complexity (1 parameter, no output schema, no annotations), the description is reasonably complete: it covers purpose, usage context, and a key behavioral trait (cost). However, it could benefit from details on output format or error cases to be fully comprehensive.

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 schema description coverage is 100%, so the parameter 'job_id' is fully documented in the schema. The description adds minimal semantics by referencing 'Job ID returned by crawl or other async endpoints', but this largely repeats the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 verb ('Check') and resource ('status of an async job'), with specific examples ('e.g. crawl') that help distinguish it from sibling tools like 'crawl' or 'extract'. It precisely defines what the tool does without being tautological.

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?

The description implicitly indicates when to use this tool—for checking async job status—by referencing jobs returned by 'crawl or other async endpoints', but it does not explicitly state when not to use it or name alternatives among siblings. This provides clear context without exclusions.

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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