noise_reduction

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

With no annotations, the description carries the full burden of behavioral disclosure. It does warn about audible artifacts above 20 dB and explains parameter trade-offs, which is useful. However, it does not state whether the operation destructively modifies the selected audio, whether it is undoable, or what happens if the required noise profile has not been captured.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is efficiently structured: main action first, mandatory precondition second, risk warning third, and a clean Args list last. Every sentence adds operational value, and the formatting makes the prerequisite and defaults easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple three-parameter effect tool with no output schema, the description covers invocation order, parameter semantics, defaults, and risk guidance. It is only missing a bit of context about post-conditions, such as whether the selected audio is replaced or rendered and what error occurs if the noise profile precondition is not satisfied.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides only parameter titles and defaults with zero description coverage. The description's Args block fully compensates by explaining each parameter's meaning, units, allowed range, and default, plus practical guidance for the dB parameter. This is exactly the semantic enrichment the schema lacks.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Apply noise reduction') and the target resource ('the selected audio'), making the tool's purpose obvious. It is easily distinguishable from siblings like click_removal or effect_repair by its name and focus, though it does not explicitly contrast itself with those alternatives.

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

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

It gives explicit workflow ordering: call get_noise_profile first, select the audio, then call this tool. It also provides practical dB ranges for different cleanup scenarios. It stops short of a 5 because it does not explicitly say when not to use this tool versus alternatives like click_removal or auto_cleanup_audio.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.