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noise_reduction

Reduce background noise from an audio selection using a noise profile. Control reduction strength, sensitivity, and frequency smoothing to minimize artifacts.

Instructions

Apply noise reduction to the selected audio. You MUST call get_noise_profile first on a region of pure noise, then select the audio you want to clean, then call this.

WARNING: Values above 20 dB risk audible artifacts (warbling, metallic sound). Use 6-12 dB for gentle cleanup, 12-20 dB for moderate noise. Only exceed 20 dB for extremely noisy recordings where some artifact trade-off is acceptable.

Args: noise_reduction_db: Amount of noise reduction in dB (0-48). Default: 12 sensitivity: How sensitive the detection is (0-24). Default: 6 frequency_smoothing: Number of frequency smoothing bands (0-12). Default: 3

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sensitivityNo
noise_reduction_dbNo
frequency_smoothingNo
Behavior4/5

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

With no annotations, the description discloses behavior: it applies noise reduction, parameter effects, and artifact risks. However, it does not explicitly state whether the action is destructive or undoable, though that is implied.

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 action and prerequisite, then a warning, then parameter details. It is somewhat verbose but every sentence adds value; could be slightly more concise.

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 no output schema and no annotations, the description is highly complete: it covers prerequisite, parameter details, risk warnings, and usage patterns, leaving no critical gaps for agent invocation.

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 input schema has 0% description coverage, but the description compensates fully by explaining each parameter: noise_reduction_db (range, default, risk), sensitivity, and frequency_smoothing, with recommended values.

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 'Apply noise reduction to the selected audio', specifying the verb and resource. It distinguishes itself from sibling tools like get_noise_profile and other effects by detailing the prerequisite and unique function.

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?

Explicitly instructs to call get_noise_profile first and select audio before using. Provides clear dB ranges (6-12 gentle, 12-20 moderate, >20 with caution) and warns about artifacts, offering strong usage guidance.

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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