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await_result

Read-onlyIdempotent

Wait for an async job to finish and return its result in ONE call — no manual polling loop. Pass the requestId + jobType from an async tool (generate_video, animate_image, generate_3d_model, transcribe_audio, epub_to_audiobook, ai_call). If your MCP client opened the request with 'Accept: text/event-stream', this streams live progress (notifications/progress) while it waits, then returns the final result; otherwise it does a single status check and returns immediately (call again until status='COMPLETED'). For long jobs it waits up to ~4 minutes per call, then returns status='IN_PROGRESS' with timed_out=true — call again with the same requestId to keep waiting. Equivalent to check_job_status + get_job_result combined. Free; no payment.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobTypeYesMust match the async tool that returned requestId.
requestIdYesThe requestId returned by the async tool.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / jobType / enum
      Previous value: -[
      -  "video",
      -  "video-image",
      -  "video-fal-standard",
      -  "video-fal-pro",
      -  "image-3d",
      -  "transcription",
      -  "transcribe-translate",
      -  "epub-audiobook",
      -  "ai-call"
      -]New value: +[
      +  "video",
      +  "video-image",
      +  "video-fal-standard",
      +  "video-fal-pro",
      +  "image-3d",
      +  "transcription",
      +  "transcribe-translate",
      +  "translate-epub",
      +  "epub-audiobook",
      +  "ai-call"
      +]
  2. Changed1 schema field changed
    • changedInput schema / properties / jobType / enum
      Previous value: -[
      -  "video",
      -  "video-image",
      -  "video-fal-standard",
      -  "video-fal-pro",
      -  "image-3d",
      -  "transcription",
      -  "epub-audiobook",
      -  "ai-call"
      -]New value: +[
      +  "video",
      +  "video-image",
      +  "video-fal-standard",
      +  "video-fal-pro",
      +  "image-3d",
      +  "transcription",
      +  "transcribe-translate",
      +  "epub-audiobook",
      +  "ai-call"
      +]
  3. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly and idempotent annotations, the description adds substantial behavioral detail: streaming vs. one-shot status check, the ~4 minute wait limit, timed_out=true behavior, and the fact that it is free with no payment. No contradiction with annotations.

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?

The description is dense but well-structured: the core purpose is front-loaded, followed by streaming behavior, timeout behavior, and equivalence to siblings. The final 'Free; no payment' is slightly extraneous but not harmful, and each sentence contributes useful operational detail.

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 absence of an output schema and the asynchronous nature of the tool, the description covers the key return states (COMPLETED, IN_PROGRESS with timed_out), streaming behavior, and retry semantics. It does not detail failure statuses, but the overall guidance is sufficient for correct invocation.

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 coverage is 100%, so the baseline is 3. The description adds value by tying requestId/jobType to specific async tool names and clarifying that jobType must match the tool that returned the requestId, which helps the agent choose the right enum value.

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 states a specific action: wait for an async job and return its result in one call, explicitly avoiding a manual polling loop. It distinguishes itself from the sibling tools by naming its relation to check_job_status and get_job_result as a combined equivalent.

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?

It clearly states the required inputs (requestId + jobType), lists the async tools that produce them, and explains the two modes depending on the Accept header. It also gives explicit retry guidance for long jobs, so an agent knows exactly how to use it and when to call again.

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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