Generate music / sound

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

The annotations already declare non-read-only, non-idempotent, open-world, non-destructive behavior, so the description's main added value is disclosing the async job model and the job_id return. It also warns that durations, lyrics, and instrumental support vary by model, which is genuinely useful behavioral context. It omits any mention of credit cost or billing consequences for a paid generation call, which is the most important missing behavior for an agent deciding whether to invoke it.

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?

Three sentences, front-loaded with the verb and resource, then prerequisites, then the return value. The parenthetical model list is dense but earns its place by signaling which backends are in play. Minor waste in restating the force_instrumental constraint already present in the schema.

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 10-parameter, no-output-schema generation tool, the description covers the essentials: what it produces, that it is async, the job_id return, and where to find model constraints. It falls short on cost/credit implications and on the meaning of several optional parameters, but the core call-and-poll contract is complete.

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?

With only 50% schema description coverage across 10 parameters, the description partially compensates by explaining that durations, lyrics, and instrumental options are model-dependent and must be checked via carpe_model_details. However, voice, speed, extra, and lyrics_prompt receive no semantic explanation in either place, and the nested 'extra' object is entirely opaque. The guidance adds real meaning for a few parameters but does not close the coverage gap.

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 uses a specific verb ("Queue") and names the concrete resources produced: music, sound effects, and long-form speech, plus the model families involved. An agent can immediately tell this is an asynchronous generation endpoint rather than a status, listing, or pricing tool. It does not, however, disambiguate itself from the sibling carpe_tts even though it explicitly claims TTS v3-v4 coverage, which leaves a real overlap for the agent to resolve.

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 gives concrete workflow guidance: read per-model constraints via carpe_model_details first, and poll results with carpe_music_status. That is a clear prerequisite-and-follow-up chain rather than implied usage. What is missing is any when-not guidance, particularly when to prefer carpe_tts over this tool for speech, or when the router route should be chosen over carpe.

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