symflow-mcp

sym_dub

Translate video speech into multiple languages with synthetic voice, optionally replace subtitles or sync lips. Returns a job ID for tracking.

Instructions

Dubbing: translate the speech of a video into other languages with a synthetic voice; options: replace burned-in subtitles, lip-sync (one visible speaker). Up to 20 videos per call. Returns jobId.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "videos": "<videos>",
      "targets": "<targets>"
    },
    "name": "sym_dub"
  }
}

Input Schema

Name	Required	Description
`dryRun`	No
`folder`	No
`source`	No	source language, default auto detect
`videos`	Yes	videos to dub
`lipsync`	No
`targets`	Yes	target languages as named by Symphony (English, Spanish, Japanese…)
`voiceId`	No
`replaceSubtitles`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 20, 2026

TDQS

A3.9/5.0

Behavior4/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses meaningful behavior: uses a synthetic voice, can replace burned-in subtitles, supports lip-sync for one visible speaker, caps the request at 20 videos, and returns a jobId. The jobId return value usefully implies asynchronous processing, though it does not explicitly state side effects on the original videos.

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?

The description is two sentences and front-loads the core purpose with a colon. Every clause adds value: the operation, available options, batch limit, and return value. There is no filler or redundancy.

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

Completeness3/5

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

For a tool with 8 parameters, no annotations, and no output schema, the description is reasonably informative but incomplete. It captures the main purpose, limits, and jobId return, but leaves several parameters unexplained and does not describe how to monitor or cancel the returned job, which matters given sibling tools like sym_status and sym_cancel.

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 coverage is only 38%, so the description must compensate for undocumented parameters. It adds meaning for videos ('Up to 20 videos per call'), lipsync ('one visible speaker'), and replaceSubtitles ('replace burned-in subtitles'). However, dryRun, folder, and voiceId receive no explanation in either the schema or the description, leaving important 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 starts with a specific verb and resource: 'Dubbing: translate the speech of a video into other languages with a synthetic voice.' It also names concrete options, making it easy to distinguish from sibling tools like sym_transform or sym_generate.

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 intended use is clearly implied by the description and name: use this when dubbing video speech into another language. However, it does not explicitly contrast with alternatives, state when not to use it, or mention prerequisites, so guidance is implied rather than direct.

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