audio_analyze_masking

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description's 'Measure' verb is consistent with those. The description adds the computed metric details but no additional behavioral traits such as input constraints or processing side effects, so it stays at baseline.

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?

One sentence, front-loaded with the action verb, and every word contributes to defining the tool's function. No filler or redundant rephrasing.

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?

With a 100%-covered input schema, clear safety annotations, an output schema present, and a succinct purpose statement, nothing needed to call the tool correctly is missing. Return-value details are handled by the output schema, so the description does not need to explain them.

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 coverage is 100%, with all three parameters documented in the input schema. The description restates the vocal/instrument theme but adds no semantic detail beyond what the schema already provides, so the baseline 3 applies.

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 uses a specific verb ('Measure') and names concrete resources: per-band spectral overlap and vocal-minus-instrument level margins. This is distinct from generic siblings like audio_analyze_file and audio_compare_files because it identifies the exact masking-oriented metric computed.

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 description implies the tool is for diagnosing frequency masking between a vocal and an instrumental render, but it never states explicit when-to-use conditions or contrasts with related siblings such as mix_masking_recommendations or audio_compare_files. Context is clear, but exclusions and alternatives are left to inference.

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