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createAmbiance

Produce a looping background ambiance soundscape from a text description, such as "windy forest at dusk" or "busy tavern interior". The job result is a single audio result containing a URL. The description field is required and duration is capped at 10 seconds (0 means auto-pick based on the description). Credits are held when the job is accepted and refunded if it fails or is cancelled. Use this for continuous, atmospheric background loops; use createSoundEffect for short discrete sound effects, createMusic for musical pieces, and createAudioTransform to remix an existing audio sample. Pass an optional request_id to tag the result so you can locate it later via listGenerations (type audio). Async generation job: returns {id, status} - poll getApiJob (job and credit contract: see the server instructions).

Credits: This endpoint consumes 2 credits per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestBodyYesPayload for generating a seamless looping ambiance soundscape from a text description

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / requestBody / properties / request_id / description
      Previous value: -"Optional client-provided identifier, unique per request. Re-sending the same request_id returns the existing job instead of generating again. Also usable with the results endpoint."New value: +"Optional client-provided identifier, unique per request. Re-sending the same request_id returns the existing job instead of generating again. Also usable as the request_id filter of listGenerations."
  2. Changed6 schema fields changed
    • removedInput schema / properties / requestBody / properties / augment_prompt / default
      Removed value: -true
    • changedInput schema / properties / requestBody / properties / augment_prompt / description
      Previous value: -"Augment the prompt behind the scenes. Disable to have more control."New value: +"Augment the prompt behind the scenes. Disable to have more control. Default: true."
    • removedInput schema / properties / requestBody / properties / duration / default
      Removed value: -0
    • changedInput schema / properties / requestBody / properties / duration / description
      Previous value: -"Duration in seconds. Use 0 for automatic duration based on the description."New value: +"Duration in seconds. Use 0 for automatic duration based on the description. Default: 0."
    • removedInput schema / properties / requestBody / properties / loop / default
      Removed value: -true
    • changedInput schema / properties / requestBody / properties / loop / description
      Previous value: -"Generate an ambiance that loops seamlessly."New value: +"Generate an ambiance that loops seamlessly. Default: true."
  3. Changed1 schema field changed
    • addedInput schema / properties / requestBody / properties / loop
      Added value: +{
+  "default": true,
+  "description": "Generate an ambiance that loops seamlessly.",
+  "example": true,
+  "type": "boolean"
+}
  4. Changed1 schema field changed
    • changedInput schema / properties / requestBody / properties / request_id / description
      Previous value: -"Optional client-provided identifier for this request. Use this to retrieve results later via the results endpoint."New value: +"Optional client-provided identifier, unique per request. Re-sending the same request_id returns the existing job instead of generating again. Also usable with the results endpoint."
  5. Added

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden, and it does so thoroughly. It discloses async behavior (returns {id, status} and requires polling getApiJob), credit handling (credits held on acceptance, refunded on failure/cancellation, 2 credits per call), duration cap, and request_id idempotency semantics. These are genuine behavioral insights beyond the schema.

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 about six sentences and packs in purpose, constraints, credit behavior, sibling routing, request_id guidance, and async polling instructions. It is front-loaded with the core purpose and only slightly verbose in the closing credit note, which is acceptable given the tool's complexity.

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 complex async generation tool with no output schema, the description covers everything an agent needs: what it generates, input requirements, duration cap, credit cost and refund policy, result shape, polling mechanism, idempotency, and sibling tool routing. No critical gap is apparent.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds minimal parameter-level context beyond the schema: it restates that description is required, summarizes duration 0 as auto-pick, and notes request_id can be used to locate results via listGenerations. This is helpful but largely redundant with the detailed schema descriptions.

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 opens with a specific verb and resource: 'Produce a looping background ambiance soundscape from a text description,' with concrete examples. It also names sibling tools (createSoundEffect, createMusic, createAudioTransform) and explains what each is for, making the tool's distinct purpose immediately clear.

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?

Explicit guidance is given: 'Use this for continuous, atmospheric background loops; use createSoundEffect for short discrete sound effects, createMusic for musical pieces, and createAudioTransform to remix an existing audio sample.' It also clarifies required inputs, duration limits, request_id tagging, and async polling, leaving little ambiguity about when and how to invoke.

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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