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Check fal.ai Queue Request Status

fal_check_status
Read-onlyIdempotent

Check the progress of a submitted AI generation request. Returns status (queued, in progress, completed); retrieve final output with fal_get_result when done.

Instructions

Check the status of a request previously submitted with fal_submit_request. Does NOT return the final output — once status is COMPLETED, call fal_get_result to fetch it.

Args:

  • model_id (string): The same model id used when submitting, e.g. "fal-ai/minimax/video-01"

  • request_id (string): The request_id returned by fal_submit_request

  • include_logs (boolean): Include runner logs (default: false)

  • response_format ('markdown' | 'json'): Output format (default: markdown)

Returns: Status object with fields: { "status": "IN_QUEUE" | "IN_PROGRESS" | "COMPLETED", "request_id": string, "queue_position": number, // present while IN_QUEUE "logs": array | null // present if include_logs=true }

Examples:

  • Use when: "Is my video ready yet?" -> check status, then fal_get_result if COMPLETED

  • Don't use when: you haven't submitted a request yet — use fal_submit_request first

  • Don't use when: you want the actual output — use fal_get_result after status is COMPLETED

Error Handling:

  • Returns "Not found (404)" if the request_id is wrong or the request has expired

  • Returns "Authentication failed" if FAL_KEY is missing or invalid

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_idYesThe fal.ai model/endpoint id, e.g. "fal-ai/flux/dev", "fal-ai/flux-pro/kontext", or "fal-ai/minimax/video-01". Find valid ids with fal_list_models or at https://fal.ai/models.
request_idYesThe request_id returned by fal_submit_request when the job was queued.
include_logsNoWhether to include runner logs in the response (default: false)
response_formatNoOutput format: 'markdown' for human-readable or 'json' for machine-readable (default: markdown)markdown
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context: it does not return output, must call fal_get_result when COMPLETED, and details error responses (404, auth failure). No contradictions.

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?

Well-structured with clear sections (Args, Returns, Examples, Error Handling). Every sentence adds value. Could be slightly more concise, but overall front-loaded and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple status-check tool, the description is fully complete: covers parameters, return object structure with fields and types, usage flow, error cases. No missing information needed for correct invocation.

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

Parameters5/5

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

Schema coverage is 100%, so baseline 3. The description adds significant value with examples for model_id, clarifies request_id purpose, includes default values and formatting options, and explains include_logs and response_format 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?

The description clearly states it checks the status of a previously submitted fal.ai request and explicitly says it does NOT return final output, distinguishing it from fal_submit_request and fal_get_result. The verb 'check' and resource 'status' are specific.

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

Usage Guidelines5/5

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

Provides explicit when-to-use ('when you have a request_id'), when-not-to-use ('haven't submitted yet', 'want actual output'), and alternatives (fal_submit_request, fal_get_result). The examples section reinforces this.

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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