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Generate a batch of audio assets

generate_audio_batch

Generate audio assets from a manifest, with multiple takes and sidecar metadata per asset, while refusing non-commercial model licences before generation.

Instructions

Generate every asset in a manifest, two takes each, with its sidecar. The manifest lists the prompt, the model, the parameters, the licence and the target loudness of each asset. The tool refuses a manifest that names a model with a non-commercial licence, so nothing that must not ship gets generated in the first place.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
onlyNoAsset names to generate; all of them by default.
countNoTakes per asset.
out_dirNoWhere to write the candidates.out/audio
manifestNoPath to a manifest JSON file.
manifest_jsonNoThe manifest itself, as JSON text, instead of a file. See the hf-assets://audio-manifest resource for the format.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
logYesWhat the engine printed while it worked.
filesYesEverything that was written.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses genuinely useful behavior beyond the schema: two takes per asset, a sidecar emitted per asset, and a hard refusal of non-commercial-licence models. It says nothing about overwrite behavior in out_dir, whether directories are created, or cost/rate implications of a batch job, so significant behavioral gaps remain.

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

Conciseness4/5

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

Three sentences, front-loaded with the core action and no redundancy. The closing clause ('so nothing that must not ship gets generated in the first place') is mildly rhetorical but still conveys the licence-gate rationale, so the cost is small.

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?

An output schema exists, so return values need no explanation. For a batch write tool with 100% schema coverage and a referenced manifest resource, the description supplies the missing pieces an agent needs: batch semantics, takes-per-asset, sidecar emission, and the licence gate.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds meaning about manifest contents (prompt, model, parameters, licence, target loudness) that the schema only gestures at via the hf-assets://audio-manifest resource, but it does not clarify the 'only', 'count', or 'out_dir' parameters beyond what the schema already says.

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

Purpose4/5

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

The description states a specific verb and resource ('Generate every asset in a manifest, two takes each, with its sidecar'), making the batch scope clear. It implicitly separates itself from the single-asset generate_audio sibling via 'every asset in a manifest', but never names or contrasts with any sibling explicitly, so it falls short of the 5 bar.

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

Usage Guidelines3/5

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

Usage context is implied rather than stated: a manifest implies batch generation, and the description gives one real precondition (manifests naming non-commercial-licence models are refused). There is no explicit 'use this instead of generate_audio when...' routing or any when-not guidance.

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