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Aetherwave Studio

Aetherwave Studio

Official
by AetherWave-Studio
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TypeScript
Remote

Master an audio track (AI mastering)

aetherwave_master_audio

Master your audio track by providing a public URL and selecting a preset. Returns a lossless WAV file matched to your distribution target.

Instructions

Submits an audio file for AI mastering and returns the mastered URL synchronously (route polls the Python service internally; expect 30s-5min). Useful as a final polish step after music generation. Cost: 20 credits per track. Producer, Mogul, and Ultimate plans get mastering free. Output is WAV (~50MB per 3-minute track, lossless for redistribution). Pick a preset to steer the mastering style; call aetherwave_list_master_presets for the full live list (12 presets including streaming, loud, gentle, hip_hop, edm, pop, rock, lofi, rnb, acoustic, cinematic, podcast). Each preset has a target LUFS value so you can match the distribution target.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "audioUrl": "<audioUrl>",
      "preset": "<preset>"
    },
    "name": "aetherwave_master_audio"
  }
}

Input Schema

NameRequiredDescriptionDefault
audioUrlYesPublic URL to the source audio file (MP3 or WAV).
presetYesMastering preset name. Must be one of: 'streaming', 'loud', 'gentle', 'hip_hop', 'edm', 'pop', 'rock', 'lofi', 'rnb', 'acoustic', 'cinematic', 'podcast'. Call aetherwave_list_master_presets for full metadata (target LUFS, description, tags).
trackTitleNoOptional title for the mastered output (used in gallery row label).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.6

TDQS

A4.6/5.0
Behavior5/5

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

The description adds substantial behavioral detail beyond annotations: synchronous polling ('route polls the Python service internally; expect 30s-5min'), cost ('20 credits per track'), free plan tiers, and output specifics ('WAV (~50MB per 3-minute track, lossless for redistribution)'). These are critical operational facts not present in 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 front-loaded with the core purpose and then packs in relevant operational details (timing, cost, output, presets). While it is long, every sentence carries useful information, though it could be tightened slightly without losing 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 tool with no output schema and 3 parameters, the description is remarkably complete: it covers synchronous behavior, latency, cost, free plans, output format and size, lossless quality, and preset guidance with a pointer to a sibling tool for the live list. The agent has enough context to invoke it correctly.

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 baseline is 3. The description adds meaning by explaining that the preset 'steer[s] the mastering style' and that each preset's target LUFS lets you 'match the distribution target,' which goes beyond the schema's mere enumeration. However, much of the parameter detail is redundant with the 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 first sentence clearly states the action and resource: 'Submits an audio file for AI mastering and returns the mastered URL synchronously.' It distinguishes the tool from siblings by positioning it as a 'final polish step after music generation' and by referencing aetherwave_list_master_presets for preset selection.

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?

Provides clear context by stating it is 'Useful as a final polish step after music generation,' which implies when to use. It also gives practical constraints like audio URL requirements, expected wait time, and cost, but does not explicitly name alternatives or state when not to use.

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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