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fal-enqueue

Queue a model for processing with required inputs. Monitor progress with fal-get-status and fetch output with fal-get-result.

Instructions

Enqueue a model. The model is enqueued using the fal.run endpoint. You need to check the status of the model using the fal-get-status tool, then get the result using the fal-get-result tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelIdYes
inputNo

Implementation Reference

  • The tool handler function for 'fal-enqueue'. It extracts modelId and input from args, then calls client.enqueue().
    async (args) => {
        const modelId = (args as any)?.modelId ?? (args as any)?.arguments?.modelId;
        const input = (args as any)?.input ?? (args as any)?.arguments?.input;
        const output = await client.enqueue(modelId as any, input);
        return { content: [{ type: 'text', text: toText(output) }] };
    },
  • The enqueue() method on FalClient that sends a POST request to the queue endpoint (queue.fal.run).
    async enqueue(modelId: string, body: unknown): Promise<unknown> {
        const endpointId = this._normalizeModelId(modelId);
        const url = `${this.QUEUE_BASE}/${endpointId}`;
        return await this._postJson(url, body);
    }
  • Registration of the 'fal-enqueue' tool via server.tool(), including its Zod schema (modelId: z.string(), input: z.unknown()) and description.
    server.tool(
        'fal-enqueue',
        'Enqueue a model. The model is enqueued using the fal.run endpoint. You need to check the status of the model using the fal-get-status tool, then get the result using the fal-get-result tool.',
        {
            modelId: z.string(),
            input: z.unknown(),
        },
        async (args) => {
            const modelId = (args as any)?.modelId ?? (args as any)?.arguments?.modelId;
            const input = (args as any)?.input ?? (args as any)?.arguments?.input;
            const output = await client.enqueue(modelId as any, input);
            return { content: [{ type: 'text', text: toText(output) }] };
        },
    );
  • Input schema for the fal-enqueue tool: modelId (string) and input (unknown).
    {
        modelId: z.string(),
        input: z.unknown(),
    },
Behavior2/5

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

No annotations are provided, so the description must fully convey behavioral traits. It only implies asynchronous execution and mentions the endpoint, but lacks details on idempotency, errors, rate limits, or return value.

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 extremely concise with two sentences, front-loading the main action and providing essential workflow instructions without extraneous words.

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 no output schema, the description should explain what the tool returns and fully cover the workflow. It partially does by mentioning status checking, but omits parameter details and does not clarify the return value or job identification.

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

Parameters1/5

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

With 0% schema description coverage, the description does not explain the two parameters ('modelId' and 'input'). The agent receives no guidance on what these parameters mean or how to use them, forcing reliance on the bare schema.

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 ('Enqueue a model') and mentions the underlying endpoint. However, it does not explicitly contrast with the sibling tool 'fal-run-sync' which likely offers synchronous execution, so differentiation is implicit.

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?

The description provides a workflow hint by instructing to check status and get result afterward, but it does not specify when to use this tool versus alternatives like 'fal-run-sync' or when not to use it.

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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