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

With no annotations, the description carries the full burden and does well: it discloses dispatch to Modal AI workers, varying credit costs, file deletion after processing, audit trail via task list, and data retention reference. This exceeds typical transparency.

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?

The description is front-loaded with the core function and then adds necessary cost and privacy caveats. It's longer than a one-liner but every sentence adds distinct useful information; however, some pricing details could be considered ancillary.

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 zero-parameter processing tool with no output schema, the description covers purpose, execution backend, billing, retention, and eligibility. It could be more complete by stating how processed files are returned, but the essential context is present.

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 is empty, so there are no parameters to document. The description compensates by explaining the high-level input (videos and audio) and cost drivers (model, file size), satisfying the 0-parameter baseline.

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 opens with a clear verb-object statement: 'Automatically remove silent gaps from videos and audio.' This precisely identifies the function and distinguishes it from sibling tools like audio enhancer or video trimmer.

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?

It provides clear operational context: AI Studio run, credits per run, and credit limitations ('Day Pass and welcome credits do not include AI Studio'). It does not explicitly contrast with alternative tools, but the context is strong enough for an agent to know when invoking this tool is appropriate.

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