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render_audio

Generate audio — a voice line, a sound effect, ambience or a music bed. SPENDS CREDITS. The prompt is sent to the provider VERBATIM. Returns a job id; call get_generation to follow it. The resulting URL can be passed into render_video as an audio reference on models that accept one. Some models TRANSFORM media instead of generating (upscale, remove-bg, face-swap): they take NO prompt at all. Call list_models first and read prompt ('required'|'optional'|'none') and requires — for prompt:'none' models omit prompt and pass the source media instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
audioNoNative audio. Omit to use the model default (usually on).
modelYesModel id from list_models, e.g. dreamina-seedance-2-ref. Required — there is no default.
aspectNoOnly values list_models reports for this model.
audiosNoReference media. Each entry is either a plain URL, or {name, url} so the prompt can address it as @name — the server renumbers those to the @Image1/@Video1 form the provider reads, in the order given, so you never count positions yourself.
imagesNoReference media. Each entry is either a plain URL, or {name, url} so the prompt can address it as @name — the server renumbers those to the @Image1/@Video1 form the provider reads, in the order given, so you never count positions yourself.
promptNoSent to the provider VERBATIM — nothing rewrites it. Provider flags parsed out of prompt text (--seed, --cf, --wm) survive, so they work here. Omit entirely for models whose list_models.prompt is 'none' (upscale, remove-bg) — they take no text.
run_idNoOptional. Your id for this agent run (1–64 of A-Z a-z 0-9 . _ : -). Stored on every job of the run so they can be found and filed together later. Use the same value for every call of one run.
videosNoReference media. Each entry is either a plain URL, or {name, url} so the prompt can address it as @name — the server renumbers those to the @Image1/@Video1 form the provider reads, in the order given, so you never count positions yourself.
projectNoOptional. A Drama Studio film id in the workspace being charged: the finished generation is added to that film's media pool (videos on its timeline, images/audio as references). Workspace generations only; checked before any credit is spent.
durationNoSeconds. Only values list_models reports for this model.
workspaceNoOptional. The workspace to generate in. Only a workspace API key (Settings → Developer) can spend a workspace — this may only repeat that key's workspace id; omit it and the key's own scope is used. A personal key or a sign-in token stays personal (passing a workspace is refused).
resolutionNoOnly values list_models reports for this model.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Annotations only cover safety flags (readOnly=false, destructive=false, idempotent=false, openWorld=true); the description adds the material behavior an agent must know: it SPENDS CREDITS, the prompt reaches the provider VERBATIM, provider flags (--seed, --cf, --wm) survive parsing, and the call returns a job id rather than finished audio.

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?

Front-loaded with purpose, credit cost, and the get_generation follow-up, and nearly every sentence carries operational information. It is dense and somewhat long with heavy capitalization, and the 'upscale, remove-bg, face-swap' examples are visually-oriented transforms that sit oddly in an audio tool, mildly blunting the sentence's value.

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 12-parameter, no-output-schema, credit-spending mutation tool, it covers the essentials: cost, verbatim provider transmission, async job id + follow-up tool, model-driven prompt requirements, and cross-tool reuse of the result. Nothing needed to invoke it correctly is missing.

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 the baseline is 3, but the description adds real semantics the schema lacks: the prompt/source-media trade-off driven by list_models.prompt, the fact that `model` is required with no default, and the credit-spend implication of the call. It explains how `prompt` must be omitted rather than merely describing its type.

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?

Opens with a specific verb and resource ('Generate audio') and immediately enumerates the output kinds (voice line, sound effect, ambience, music bed). It also differentiates itself from siblings render_video/render_image and from non-generating models (upscale, remove-bg, face-swap), so an agent can place it in the family without opening a schema.

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?

Gives explicit preconditions and follow-up: 'Call list_models first and read `prompt` ... and `requires`', 'omit `prompt` and pass the source media instead' for prompt:'none' models, and 'call get_generation to follow it'. It also names the downstream route ('URL can be passed into render_video as an audio reference on models that accept one').

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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