Galatic.ai

Beat sync

beat_sync

Apply beat-synced effects to a video, firing the effect on the detected beats. frequency is a string such as "every", not a number. Omitted effect, strength and frequency take the defaults pulse, 0.3 and every. Spends Galatic.AI credits. Returns a job id; poll get_job_status with kind "beat_sync".

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": {
      "videoUrl": "<videoUrl>",
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "beat_sync"
  }
}

Input Schema

Name	Required	Description
`effect`	No	The visual effect on each beat. Default "pulse".
`endSec`	No	End of the section to process, in seconds.
`context`	Yes	Explain 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."
`startSec`	No	Start of the section to process, in seconds.
`strength`	No	How strong the effect is. Default 0.3.
`videoUrl`	Yes	URL of the video to process. Required.
`frequency`	No	How often detected beats trigger the effect. Default "every".
`llm_model`	Yes	The 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.
`conversation_id`	No	Pass 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.
`sourceGalleryItemId`	No	Library item id the video came from, when it is one of your library items.

Schema Changelog

Changes observed during successful MCP inspections.

Changed10 schema fields changedOct 27, 2026

addedInput schema / properties / effect / description

Added value: +"The visual effect on each beat. Default \"pulse\"."

addedInput schema / properties / effect / enum

Added value: +[
+  "pulse",
+  "zoom",
+  "both",
+  "flash",
+  "shake"
+]

addedInput schema / properties / endSec / description

Added value: +"End of the section to process, in seconds."

addedInput schema / properties / frequency / description

Added value: +"How often detected beats trigger the effect. Default \"every\"."

addedInput schema / properties / frequency / enum

Added value: +[
+  "every",
+  "alternate",
+  "strong"
+]

changedInput schema / properties / frequency / type
```
Previous value: -"number"New value: +"string"
```

addedInput schema / properties / sourceGalleryItemId / description

Added value: +"Library item id the video came from, when it is one of your library items."

addedInput schema / properties / startSec / description

Added value: +"Start of the section to process, in seconds."

addedInput schema / properties / strength / description

Added value: +"How strong the effect is. Default 0.3."

addedInput schema / properties / videoUrl / description

Added value: +"URL of the video to process. Required."

First observedOct 24, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Goes meaningfully beyond annotations by disclosing credit consumption, the asynchronous job-id return, and the exact polling path. Annotations already cover the safety profile (readOnly=false, destructive=false, idempotent=false), and the description adds cost and async-retrieval context. It stops short of saying whether the original video is replaced or whether repeated calls each spend credits, keeping it at 4.

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?

Four tightly packed sentences, front-loaded with the core action, followed by the parameter caveat, defaults, cost, and retrieval path. No sentence is filler.

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?

For a 10-parameter, credit-spending async job with no output schema, the description covers purpose, defaults, cost, and how to retrieve the result. It omits what the finished job produces (e.g., a new gallery item vs. replacement) and idempotency implications, which is a real but minor gap.

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?

With 100% schema description coverage and documented defaults/enums, the schema already carries parameter meaning. The description's warning that frequency is a string like "every", not a number, is a useful disambiguation, but it also restates defaults already present in the schema, so the net add is modest.

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?

Specific verb and resource: 'Apply beat-synced effects to a video, firing the effect on the detected beats.' An agent immediately knows this is a beat-driven effect render, not a generic video generator. It does not explicitly contrast with neighbors like generate_video or extend_video, so it lands at 4 rather than 5.

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 usage context is implied by the beat-effect purpose, and the post-call flow is spelled out ('poll get_job_status with kind "beat_sync"'). However, there is no explicit when-to-use versus alternatives or when-not-to-use guidance, so an agent must infer selection.

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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