Squall Studio

Generate episode music

generate_episode_music

Generate a background music track for an episode. Requires the episode to already have an assembled video. Spends credits. Returns a job id — poll it with get_job.

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": {
      "episode_id": "<episode_id>",
      "idempotency_key": "<idempotency_key>"
    },
    "name": "generate_episode_music"
  }
}

Input Schema

Name	Required	Description
`prompt`	No	The music prompt for this track: genre, mood, instruments, tempo. It is saved as the project's music prompt, so later music uses it too. Without it, the project's saved prompt is used, or the general default.
`episode_id`	Yes	Episode id.
`idempotency_key`	Yes	Stable key identifying this generation request. Reuse the SAME key when retrying the same request — the original job is returned and no second charge is made. Use a NEW key when you deliberately want another generation.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedOct 30, 2026

addedInput schema / properties / prompt

Added value: +{
+  "description": "The music prompt for this track: genre, mood, instruments, tempo. It is saved as the project's music prompt, so later music uses it too. Without it, the project's saved prompt is used, or the general default.",
+  "maxLength": 4100,
+  "minLength": 1,
+  "type": "string"
+}

First observedSep 7, 2026

TDQS

A4.5/5.0

Behavior5/5

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

Beyond the annotations, the description discloses that the operation spends credits, requires an assembled video, and returns an asynchronous job id. Those are material behavioral details an agent needs before invoking a non-read-only generation tool.

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 short, front-loaded, and every sentence adds useful information. It moves from purpose to prerequisite to cost to follow-up action without wasted wording.

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?

For an asynchronous generation tool without an output schema, the description covers the essential context: prerequisite state, credit spending, return value as a job id, and the next step via get_job. The schema fills in parameter-level details such as idempotency behavior.

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 parameters are already fully documented in the input schema. The description adds no parameter-specific semantics beyond indicating that the tool is for an episode and produces a job.

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 verb and resource: generating a background music track for an episode. This clearly distinguishes it from sibling tools that generate scripts, images, clips, or locations.

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?

It gives important prerequisites and lifecycle guidance: the episode must already have an assembled video, the call spends credits, and the returned job id should be polled with get_job. It does not explicitly state when not to use it or compare it with other generation tools, so it falls short of a full 5.

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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