symflow-mcp

sym_transform

Creates 15- or 30-second TikTok clips from product videos and photos, adding a voice-over in 11 languages. Returns a jobId.

Instructions

"Video refresh": Symphony cuts new TikTok-ready clips (15 or 30 s) from the user's own product videos (each ≥ 15 s) and photos, with a voice-over in one of 11 languages (ar de en es fr id ms vi th ja pt). 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>",
      "productName": "<productName>"
    },
    "name": "sym_transform"
  }
}

Input Schema

Name	Required	Description
`dryRun`	No
`folder`	No
`images`	No	product photos
`videos`	Yes	source videos ≥ 15 s
`seconds`	No
`language`	No
`productName`	Yes
`productDescription`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 20, 2026

TDQS

A3.5/5.0

Behavior3/5

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

With no annotations, the description carries the behavioral burden. It discloses the core behavior (cutting clips, voice-over, returning jobId) and useful constraints (minimum video length, language list). But it does not mention that the operation is asynchronous, that credits may be consumed, or what jobId means beyond being a returned identifier.

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 entire description is one tight, front-loaded sentence with the key action first and all essential constraints compressed into parentheses. The language list is compact and the final sentence on jobId is necessary. No filler.

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?

For an 8-parameter media tool with no output schema and no annotations, the description is too sparse: it omits the meaning of critical parameters (dryRun, folder, productName, productDescription) and does not explain the expected job workflow or how to retrieve the result. An agent could call it with required fields but not know the effects of the optional ones.

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

Parameters2/5

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

Schema coverage is only 25% (videos and images have path/URL descriptions), so the description must compensate. It adds meaning for seconds and language by enumerating valid values, but leaves dryRun, folder, productName, and productDescription unexplained, making it hard for an agent to correctly fill all parameters.

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 names a specific operation ('Symphony cuts new TikTok-ready clips'), specifies source material (product videos ≥ 15 s and photos), output durations (15/30 s), voice-over language set, and the return value (jobId). This clearly differentiates it from siblings like sym_dub or sym_editor, which do different media operations.

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 the use case ('Video refresh') and conditions such as videos ≥15 s and supported languages, so an agent can infer when it might apply. However, it never explicitly says when to prefer this over sym_dub, sym_avatar_video, or sym_editor, nor states any exclusions, which is a notable gap with so many siblings.

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