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check_status

Check the status of a Fal.ai image generation request using its request ID to monitor progress and retrieve results.

Instructions

Check the status of a Fal.ai request

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYesThe request ID to check

Implementation Reference

  • Handler for the check_status tool. Parses input using CheckStatusSchema and returns a text response explaining that full status checking requires app_id and request_id, currently a stub implementation.
    case "check_status": {
      const params = CheckStatusSchema.parse(args);
      // For now, return a message about status checking
      // Fal.ai queue.status requires both app_id and request_id
      
      return {
        content: [
          {
            type: "text",
            text: "Status checking requires both app_id and request_id. Use the result from run_model or run_workflow which includes status information.",
          },
        ],
      };
    }
  • Zod schema for check_status tool input validation: requires request_id string.
    const CheckStatusSchema = z.object({
      request_id: z.string().describe("The request ID to check status for"),
    });
  • src/index.ts:192-205 (registration)
    Registration of the check_status tool in the list of tools returned by ListToolsRequestHandler, including name, description, and inputSchema matching the Zod schema.
    {
      name: "check_status",
      description: "Check the status of a Fal.ai request",
      inputSchema: {
        type: "object",
        properties: {
          request_id: {
            type: "string",
            description: "The request ID to check",
          },
        },
        required: ["request_id"],
      },
    },
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool checks status but doesn't explain what 'status' entails (e.g., pending, completed, failed), whether it's a read-only operation, potential rate limits, or error handling. This leaves significant gaps for an agent to understand how to use it effectively.

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 a single, direct sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded with the essential information, making it easy to parse and understand quickly.

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 lack of annotations and output schema, the description is incomplete. It doesn't cover what the tool returns (e.g., status details, error messages), behavioral aspects like idempotency or side effects, or how it integrates with sibling tools. For a status-checking tool in a workflow context, this leaves critical information missing.

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 the 'request_id' parameter clearly documented. The description adds no additional meaning beyond this, such as format examples or context about where to obtain the request ID. Given the high schema coverage, a baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.

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 action ('Check') and the resource ('status of a Fal.ai request'), making the purpose understandable. However, it doesn't differentiate this tool from potential siblings like 'run_model' or 'run_workflow' that might also involve status checking, leaving room for ambiguity in a multi-tool context.

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 doesn't mention prerequisites (e.g., needing a request ID from another operation), exclusions, or how it relates to sibling tools like 'run_model', which might handle status as part of its execution.

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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