Skip to main content
Glama

Start RVC training

start_training

Use this only after the source audio was successfully PUT to the upload URL returned by create_training_job. Starts the private cloud RVC training job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
linksYes
epochsNo
statusYes
uploadYes
etaTextNo
messageNo
artifactsYes
createdAtNo
expiresAtNo
modelNameNo
startedAtNo
updatedAtNo
completedAtNo
currentEpochNo
durationSecondsNo
estimatedCompletionAtNo
estimatedRemainingSecondsNo

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already indicate write operation (readOnlyHint=false) and non-destructiveness. The description adds the context of starting training after upload, but does not disclose other behaviors like asynchronicity, potential long execution time, response format, or error conditions. It provides adequate but not rich behavioral context beyond annotations.

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

Conciseness3/5

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

The description is a single sentence, which is concise, but it omits necessary parameter explanation and behavioral details. Conciseness is valued, but not at the cost of essential information. It could be slightly expanded without losing efficiency.

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

Completeness2/5

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

Given the tool has only one parameter and an output schema that is not described, the description should cover prerequisites (mentioned), response semantics (missing), error possibilities, and async behavior. The context of starting a training job implies possible long-running or queued execution, but no such detail is provided. The description is insufficient for complete understanding.

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

Parameters1/5

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

The schema description coverage is 0%, so the description carries the full burden of explaining the only parameter (jobId). However, the description never explicitly states that jobId is the ID returned by create_training_job. It only implies this by referencing the upload URL from create_training_job. An agent would benefit from a clear statement like 'The jobId returned by create_training_job.' This omission fails to add meaning beyond the bare schema.

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 clearly states the verb ('Starts') and the resource ('the private cloud RVC training job'), distinguishing it from sibling tools like create_training_job (which prepares the job) and get_training_job (which checks status). It is specific and immediately informative.

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

Usage Guidelines5/5

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

The description explicitly says 'Use this only after the source audio was successfully PUT to the upload URL returned by create_training_job,' providing a clear precondition and referencing the correct sibling tool. This tells the agent exactly when and after what step to invoke this tool.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources