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by ai.galatic
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Generate music video

generate_music_video

Make a music video for a generated track. Spends Galatic.AI credits. Returns a job id; poll get_job_status with kind "music_video".

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": {
      "taskId": "<taskId>",
      "audioId": "<audioId>",
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "generate_music_video"
  }
}

Input Schema

NameRequiredDescriptionDefault
authorNo
taskIdYes
audioIdYes
contextYesExplain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
llm_modelYesThe exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
domainNameNo
conversation_idNoPass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Adds value beyond annotations by disclosing the credit cost and the async job-id return contract plus the polling path — none of which the annotations convey. It does not say whether the operation can be cancelled or what happens to prior videos, but the key cost and async behavior are covered.

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?

Three short sentences: purpose, cost, and follow-up contract. The most decision-relevant information (what it does, that it costs credits) is front-loaded with no filler.

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?

No output schema exists, and the description correctly explains the return (a job id) and how to poll it, which is the crucial missing piece for an async tool. However, with 7 parameters and only 43% schema coverage, four parameters — including the required taskId and audioId — remain unexplained, leaving the agent guessing at required inputs.

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 description coverage is only 43%, and the description never explains taskId, audioId, author, or domainName. The phrase "for a generated track" hints that audioId is required, but the essential identifiers are undocumented in both places, so the description fails to compensate for the coverage gap.

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?

States a specific verb and resource ("Make a music video") and scopes it to "a generated track," which separates it from standalone generate_video. It doesn't explicitly contrast with generate_video or extend_video by name, so sibling differentiation is implied rather than stated.

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

Usage Guidelines4/5

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

Gives clear operating context: it consumes credits and is asynchronous, and it names the exact follow-up action (poll get_job_status with kind "music_video"). It offers no explicit exclusions versus generate_video/extend_video, so the agent must infer which media tool to pick.

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

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