effect_notch_filter

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

No annotations are present, so the description must convey behavior. It explains parameters and defaults but does not mention whether the effect is destructive, applies to selection only, or whether it's undoable. Significant gaps for a mutation tool.

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?

Two concise sentences that front-load the purpose and then detail parameters with defaults. No wasted words.

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?

Does not mention selection context (e.g., applies to selected audio) or any output, but for a simple effect this may be implicitly understood. Lacks a bit of practical workflow guidance.

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 description explains both parameters beyond the schema: frequency is the center frequency, q is sharpness with a note that higher values give narrower notches. This adds meaningful context and covers the entire parameter set.

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?

Clearly states the verb 'Remove' and the resource 'specific frequency' using a notch filter, with a concrete example (50/60Hz hum). This distinguishes it from other effects like equalization or high-pass filters.

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?

Provides an example use case (removing mains hum) which implies when to use, but does not explicitly mention alternatives or when not to use, leaving some ambiguity relative to sibling effects.

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