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Download a completed voice conversion

download_voice_conversion_output

Use after get_voice_conversion says the job is complete and the user wants the cleaned or standard output. Each download uses the source audio's duration from the account's conversion-download minutes. If the exact file was downloaded before, ask before retrying and then set confirmRepeat true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindYesPrefer cleaned unless the user specifically asks for standard RVC.
eventIdNo
conversionIdYes
confirmRepeatNoOnly true after the user explicitly confirms downloading the same artifact again.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
acceptedYes
downloadUrlYes
downloadCountYes
secondsChargedYes

TDQS

A4.5/5.0
Behavior5/5

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

The description reveals a non-obvious side effect: each download consumes source-audio duration from the account's conversion-download minutes. It also discloses the duplicate-file behavior and the need to set confirmRepeat true, which is meaningful behavioral context beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences, each carrying necessary information: usage precondition, billing side effect, and duplicate retry rule. No redundant or filler content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a download operation with an output schema and annotations already present, the description covers the key context: when to call, what cost is incurred, and how to handle duplicate downloads. It provides enough behavioral and procedural context for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already describes kind and confirmRepeat, and the description reinforces confirmRepeat's purpose. However, with only 50% schema description coverage, conversionId and eventId remain largely undocumented by both the schema and the description. The description adds some value but does not fully compensate for those gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Download'), a specific resource ('completed voice conversion output'), and the exact trigger condition ('Use after get_voice_conversion says the job is complete'). This makes the tool's purpose distinct from the sibling creation and status-checking tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear when-to-use guidance: only after the job is complete and the user wants cleaned or standard output. It also specifies the duplicate-download protocol. It does not explicitly name an alternative to use when the job is still running, but that is strongly implied by the precondition.

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

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TDQS

A4.1/5.0
Disambiguation5/5

Each tool targets a distinct resource-action pair (training vs image training vs conversion vs requirements/quote/start/download). The consistent 'training' vs 'image_training' qualifiers prevent overlap between the two domains.

Naming Consistency5/5

All tools follow a clear verb_noun snake_case pattern (create_, get_, list_, quote_, start_, download_). The parallel naming for voice training and image training (e.g., create_training_job vs create_image_training_job) is predictable and consistent.

Tool Count4/5

18 tools is slightly above the typical 3-15 range, but each tool serves a necessary step in the training/conversion workflows (requirements, quote, create, start, poll, download). The count is justified by the server covering both voice and image training plus conversion.

Completeness4/5

The full lifecycle for training and conversion is covered: requirements gathering, quoting, job creation, upload, start, status checks, and output download. Minor gaps exist, such as no cancel/delete job operations and no dedicated list for image training jobs, but these are workable.

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