normalize

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

No annotations provided, so description must carry the burden. It clearly warns that normalization can boost quiet audio and provides examples of potential damage. However, it does not mention whether the operation is destructive or reversible, which is minor given the context of audio editing tools.

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?

Well-structured with a warning block, bullet-point guidelines, and parameter descriptions. Every sentence adds value; no fluff. Front-loaded with key warning and purpose.

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?

Given the tool's complexity (audio normalization), the description covers purpose, warnings, usage guidelines, and all parameters exhaustively. No output schema exists, but the tool modifies audio directly, so return value explanation is unnecessary.

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?

Schema has 0% description coverage, but the description compensates fully. It explains each parameter's purpose, range (peak_level_db: -60 to 0), default values, and specific use cases (e.g., stereo_independent for unbalanced recordings).

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 'Normalize the selected audio to a target peak level,' specifying the verb and resource. It distinguishes itself from sibling tools like 'loudness_normalize' by focusing on peak level normalization, but does not explicitly name alternatives, missing a slight opportunity for differentiation.

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?

Excellent guidance: explains when to use (e.g., 'Safe general-purpose level'), warns against inappropriate use on raw audio, and provides explicit preconditions ('ALWAYS check current audio levels first'). Also gives numerical target recommendations based on context.

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