effect_notch_filter

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

With no annotations, the description carries full burden. It explains the Q factor behavior ('Higher = narrower notch') but fails to disclose whether the operation is destructive, applies to the current selection or entire track, or produces side effects.

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 with the purpose front-loaded, followed by an Args section. Every sentence earns its place with zero redundancy.

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 2-parameter audio effect without output schema, the description is adequately complete. Minor gap regarding scope (selection vs. track-wide application) prevents a perfect score.

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?

Despite 0% schema description coverage, the text fully compensates by documenting both parameters with units (Hz), valid ranges (0.1-20), semantic meaning ('sharpness'), and default rationale ('US mains hum').

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 tool 'Remove[s] a specific frequency (e.g. 50/60Hz hum) with a notch filter' — providing a specific verb, resource, and concrete example that distinguishes it from sibling filters like high_pass or low_pass.

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?

The example of '50/60Hz hum' provides implied usage context for mains interference removal, but lacks explicit guidance on when to prefer this over alternatives like effect_equalization or high_pass_filter, and mentions no prerequisites.

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