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synthesize_audio

Generate localized TTS audio in a target language using a selected voice and timed segments. Optionally mux a dubbed MP4 video with background music and original timing.

Instructions

Generate billed localized TTS (and optional dubbed video).

Args: language: Target language name (e.g. "French"). language_code: Target language code (e.g. "fr"). voice_id: Voice id from list_voices. segments: JSON array of {text, start_ms, end_ms, original?} objects. output_path: Path to write the WAV audio. keep_same_length: Stretch/compress speech to source timings. keep_background_music: Mix transcribed music bed when stem_id is set. stem_id: Optional bed stem from transcribe_audio. source_duration_ms: Original duration. source_transcript: Optional original transcript. video_id: Optional id from transcribe/register to mux MP4. video_output_path: Optional path for dubbed MP4 when video_id is set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stem_idNo
languageYes
segmentsYes
video_idNo
voice_idYes
output_pathYes
language_codeYes
keep_same_lengthNo
source_transcriptNo
video_output_pathNo
source_duration_msNo
keep_background_musicNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.3.0

TDQS

A3.9/5.0
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 that the operation is billed, that it can optionally mux video, and references dependent tools. However, it does not mention side effects like file overwriting, failure modes, or permission requirements, which would be valuable for a mutation-like tool.

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?

The description is front-loaded with the summary line, then lists all 12 parameters in a clean Args format. It is a bit lengthy but every line serves a purpose, avoiding fluff. The structure is easy to parse for an agent scanning for parameter semantics.

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

Completeness4/5

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

All parameters are covered with meaningful explanations, and the description references prerequisite tools (list_voices, transcribe_audio) which gives the agent enough context to assemble valid inputs. Since an output schema exists, return values do not need description. It is complete for a tool of this complexity.

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

Parameters4/5

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

The schema provides only titles with no descriptions (0% coverage), so the description's Args section adds substantial meaning. Each parameter is explained with context, including the exact JSON structure for segments and references to source tools. This fully compensates for the schema gap, though it could include example values.

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 opens with 'Generate billed localized TTS (and optional dubbed video)', which is a specific verb+resource statement. This clearly distinguishes it from sibling tools like translate, transcribe_audio, or remux_video, as it uniquely targets audio synthesis and dubbing.

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?

The description implies its use case through the parameter list (e.g., voice_id from list_voices, stem_id from transcribe_audio) but does not explicitly state when to choose this over alternatives or when not to use it. There is no exclusion guidance, leaving the agent to infer context from the domain.

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