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generate_audio

Generate audio from a text description using ACE or Stable Audio models. Returns a prompt ID immediately; audio asset ID arrives upon completion.

Instructions

Generate audio from a text prompt — supports ACE Step 1.5 and Stable Audio 3 model families. Builds the appropriate workflow graph, filling unspecified parameters from your configured defaults (set_defaults / COMFYUI_DEFAULT_* / config file), auto-selecting local models when needed. Returns the prompt_id immediately; the resulting audio asset_id arrives in the completion notification. Requires a running ComfyUI with the corresponding model files installed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_familyYesAudio model family — determines which workflow template and model loaders to use
promptYesText description of the audio to generate (genre, mood, instruments, etc.)
durationYesAudio duration in seconds
seedNoSeed (omit to randomize)
stepsNoSampling steps
cfgNoCFG scale
samplerNoSampler name (e.g. euler, lcm, dpmpp_2m)
schedulerNoScheduler (e.g. normal, simple, karras)
filename_prefixNoOutput filename prefix (default: audio/ace_step or audio/stable_audio_3)
unetNoACE UNet model filename (in models/diffusion_models/); auto-selected if omitted
vaeNoACE VAE model filename (in models/vae/); auto-selected if omitted
clip_aNoPrimary text encoder filename (in models/text_encoders/); auto-selected if omitted
clip_bNoSecondary text encoder filename (in models/text_encoders/); auto-selected if omitted
lyricsNoLyrics or song structure description (ACE only — section-by-section breakdown)
languageNoLanguage code for prompt (ACE only, default: 'en')
musical_keyNoTarget musical key (ACE only, e.g. 'C major', 'E minor'; default: 'C major')
shiftNoModelSamplingAuraFlow shift parameter (ACE only, default: 3)
guidance_scaleNoText encoder guidance scale (ACE only, default: 0.85)
checkpointNoStable Audio 3 checkpoint filename (in models/checkpoints/); auto-selected if omitted
clipNoStable Audio CLIP encoder filename (in models/text_encoders/); auto-selected if omitted
negative_promptNoNegative prompt (Stable Audio 3 only; default: empty)
Behavior4/5

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

Despite no annotations, the description discloses key behaviors: it builds a workflow graph, fills unspecified parameters from defaults, auto-selects local models, returns prompt_id immediately, and delivers audio later via notification. This provides substantial transparency about the tool's asynchronous and dependency-managing nature.

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 consists of two well-organized sentences. The first states the core purpose and model families, and the second covers behavior and returns. No filler or redundancy; every sentence earns its place.

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 tool's complexity (21 parameters, no output schema), the description covers essential aspects: model families, default handling, async return, and prerequisites. It could mention potential errors or limitations, but it adequately covers the main workflow and outcomes.

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?

With 100% schema coverage, the baseline is 3. The description adds value by explaining that unspecified parameters are filled from configured defaults and that local models are auto-selected, which applies to many parameters (unet, vae, etc.). This overarching behavior enhances understanding beyond individual 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 clearly states 'Generate audio from a text prompt' and specifies supported model families (ACE Step 1.5, Stable Audio 3), differentiating it from sibling tools like generate_image. The verb 'generate' and resource 'audio' are specific and unambiguous.

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

Usage Guidelines4/5

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

It explicitly mentions prerequisites ('Requires a running ComfyUI with the corresponding model files installed') and explains default parameter handling. While it doesn't list alternatives, the sibling tools are in different domains (image, workflow), so no conflict. The context is clear enough for an agent to decide when to use this tool.

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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