sound_effect

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

With no annotations, the description carries the full burden and discloses almost nothing behavioral: it does not say whether audio is returned inline, saved to disk, or by URL; whether it is asynchronous; or what latency/cost to expect. The only behavioral signal is that generation is driven by a text description.

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 short sentence, front-loaded with the core concept and no filler. It is arguably too terse rather than verbose, which is a completeness issue rather than a conciseness one.

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 5-parameter generative tool with no annotations and no output schema, the description is a fragment: it omits what the tool returns, where output goes, and any operational constraints. An agent would still need to guess at the invocation contract.

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 80%, so the schema already documents loop, text, filename, and prompt_influence, which sets the baseline at 3. The description adds no parameter meaning beyond the examples of sound effect types, which loosely inform the text prompt but nothing more.

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 noun phrase 'A sound effect from a description' clearly identifies the resource (text-prompt-driven audio generation) and the examples (stingers, whooshes, ambience, applause) pin down the domain, distinguishing it from compose_music and text_to_speech. However, no verb is stated (generate/create) and no sibling is named as an alternative, so it falls short of the 5-level specificity.

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?

There is no when-to-use guidance and no routing versus siblings like compose_music (music) or text_to_speech (speech), which are the likely confusions for an audio-generation tool. The example list implies scope but does not state exclusions or conditions.

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