generate_sfx

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

With no annotations, the description fully discloses the asynchronous behavior (returns job_id immediately), the polling mechanism via check_jobs, engine defaults (ElevenLabs), and parameter-specific behavior (e.g., prompt_influence, loop semantics). It also includes the return value shape, including error case.

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 well-structured with a summary line, async note, parameter list, and return value description. It uses bullet points and examples without unnecessary verbosity, and every sentence contributes useful information.

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?

Despite having no output schema or annotations, the description covers the full lifecycle: what the tool does, how to use parameters, async workflow, and expected return values. It is complete for a generation tool with 7 parameters.

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%, and the description compensates fully by explaining every parameter: prompt with examples, duration range, loop behavior, prompt_influence scale, model override, engine override, and format defaults. This adds critical meaning beyond the bare schema.

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 clearly states 'Generate a sound effect' and specifies the subtypes (one-shot, ambience, seamless loop), distinguishing it from sibling tools like generate_music or generate_speech. The verb and resource are specific and unambiguous.

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 gives clear context for use (e.g., 'great for ambience/BGM beds') and workflow guidance (poll with check_jobs), but it does not explicitly state when not to use this tool or mention alternatives. However, the tool's scope is well-defined by its name and description.

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