audio_waveform

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 discloses the output (an image), the source type (local path or URL), and the split_channels behavior. However, it does not mention potential limitations (e.g., unsupported formats, network requirements) or side effects beyond rendering, and it does not explicitly state that the operation is non-destructive. Adequate but not rich.

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 sentences of purpose followed by a clean Args list. No redundant or filler content. The most important information (what it does, when to use) is front-loaded, and the parameter definitions are compact and scannable. Every sentence earns its place.

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 simple tool with 4 parameters and no output schema, the description covers the essential aspects: purpose, usage context, and parameter semantics. It does not specify the image format or error behaviors, but these are minor given the tool's simplicity. An agent can call it correctly without further information.

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 description coverage is 0%, so the Args section in the description is the only documentation for parameters. It explains each of the 4 parameters with type, default, and meaning (e.g., 'width: Image width in px (default 1024)'). This fully compensates for the empty schema and adds significant value beyond the bare schema properties.

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 states a specific verb ('Render') and resource ('audio waveform') with a clear output ('image the model can see'). It also lists concrete use cases (spotting silence, clipping, loudness structure, speech vs music), making it distinct from siblings like audio_info or audio_convert. No tautology; purpose is immediately apparent.

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 phrase 'Useful for...' explicitly describes when to use the tool, giving context for silence detection, clipping analysis, etc. However, it does not mention alternatives or when not to use it, leaving some inference to the agent. Still, the use-case list is strong enough to guide selection.

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