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auto_audiobook_mastering

Master audiobooks to ACX/Audible specs automatically: applies DC offset, HPF, noise reduction, compression, and loudness normalization. Runs in background, returns job_id for monitoring.

Instructions

ONE-CLICK AUDIOBOOK MASTERING: ACX/Audible compliant processing. Runs in background — returns a job_id immediately. Use check_pipeline_status to monitor.

Pipeline: DC offset > HPF 80Hz > noise reduction 12dB > compression 2.5:1 > RMS -20dB > peak cap -3.5dB Meets ACX requirements: RMS -23 to -18 dB, peaks below -3 dB (capped at -3.5 for safety margin), noise floor below -60 dB.

Args: remove_noise: Apply noise reduction using first 0.5s as noise profile. Default: True

IMPORTANT: If remove_noise is True, the first 0.5 seconds should be room tone / silence. DO NOT call this again if a pipeline is already running — use check_pipeline_status instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
remove_noiseNo
Install Server

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses async execution, immediate job_id, the full DSP pipeline (DC offset, HPF, noise reduction, compression, RMS, peak cap), ACX target values, and a concurrency warning. It stops short of stating whether the source audio is modified in place or where the finished audio is written.

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 is dense but well organized: purpose, async behavior, pipeline, ACX specs, parameter, and warnings. Every sentence carries actionable information and there is no filler.

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?

For an async tool with no output schema and no annotations, it covers the pipeline, compliance targets, parameter semantics, monitoring path, and concurrency. The main omissions are what audio it acts on (current selection/project) and how the finalized mastered audio is delivered after the job completes.

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?

The schema only provides a bare boolean with a default; the description adds real meaning by explaining 'Apply noise reduction using first 0.5s as noise profile,' reinforcing the default, and adding the crucial prerequisite that the first 0.5s must be room tone or silence when remove_noise is true.

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 'ONE-CLICK AUDIOBOOK MASTERING: ACX/Audible compliant processing,' which specifies the verb (mastering), the resource (audiobook), and the compliance target. This clearly distinguishes it from music-mastering and editing siblings.

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 says the job runs in the background, to monitor via check_pipeline_status, and includes a strong when-not: 'DO NOT call this again if a pipeline is already running — use check_pipeline_status instead.' It also states the room-tone prerequisite for remove_noise. It doesn't enumerate alternatives for other mastering types, but the audiobook-specific scope is unambiguous.

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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