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auto_audiobook_mastering

Process audio files to meet ACX/Audible audiobook standards with automated mastering, including noise reduction, compression, and level normalization.

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
Behavior4/5

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

With no annotations provided, the description carries full burden and succeeds well: it discloses async behavior ('runs in background — returns a job_id immediately'), details the complete processing pipeline (DC offset > HPF 80Hz > etc.), and specifies ACX compliance thresholds. Minor gap: does not explicitly clarify whether it modifies the source file or creates a new export.

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?

Every sentence earns its place: opens with value proposition, follows with async behavior, technical pipeline, compliance specs, parameter details, prerequisites, and usage restriction. Well front-loaded and appropriately detailed for the complexity of audio mastering.

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?

Given the high complexity (professional audio mastering with specific broadcast standards), single parameter, and lack of output schema, the description is complete. It explains return values (job_id), monitoring mechanism (check_pipeline_status), technical specifications, and operational constraints.

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 has 0% description coverage (only title and type). The description fully compensates by explaining the remove_noise parameter's function ('Apply noise reduction using first 0.5s as noise profile'), default value, and critical prerequisite about audio content requirements.

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 immediately states 'ONE-CLICK AUDIOBOOK MASTERING: ACX/Audible compliant processing' - a specific verb+resource combination. The ACX/Audible compliance reference clearly distinguishes this tool from sibling `auto_master_music` and other cleanup tools.

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?

Provides explicit when-not guidance ('DO NOT call this again if a pipeline is already running'), names the specific alternative tool to use instead ('use check_pipeline_status'), and states critical prerequisites ('If remove_noise is True, the first 0.5 seconds should be room tone / silence').

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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