compressor

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

No annotations are provided, so the description carries the full burden. It warns about the `normalize=True` behavior re-peaking audio to 0 dB and explains compression effects. Lacks mention of reversibility or destructive nature, but overall provides good behavioral context.

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 brief intro, usage guidelines, a warning, and an Args list. Every sentence adds value, and it is front-loaded with the core purpose. No wasted text.

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 (7 parameters, no output schema), the description covers purpose, usage, parameter semantics, and warnings comprehensively. An agent can correctly select and invoke this tool without additional context.

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 input schema has 0% description coverage, but the description includes an Args section explaining each of the 7 parameters (threshold_db, noise_floor_db, ratio, attack_time, release_time, normalize, use_peak) with defaults and usage context. Fully compensates for missing schema descriptions.

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 'Apply dynamic range compression. Evens out volume differences.' This is a specific verb+resource, and the description distinguishes it from related tools like `normalize` and `loudness_normalize` by providing usage guidance and warnings.

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 explicit when-to-use guidance for mastering vs. podcast/voice with recommended ratios and attack times. Also warns against using `normalize=True` for loudness control and suggests `loudness_normalize()` instead, offering clear alternatives.

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