Kuro

Change a video's voice

change_video_voice

Replace the speech voice in an owned clip with an ElevenLabs voice, saving a new generation using account entitlements. Pass exactly one of voice_id or subject (a Subject with an ElevenLabs voice). get_generation waits for the result.

Input Schema

TableJSON Schema

Name	Required	Description
`source`	Yes
`subject`	No	A Subject's name or id with a bound ElevenLabs voice.
`voice_id`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`message`	Yes
`generation`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 21, 2026

addedOutput schema / properties / generation / properties / ready_in_seconds
```
Added value: +{
+  "type": [
+    "number",
+    "null"
+  ]
+}
```

changedOutput schema / properties / generation / required

Previous value: -[
-  "generation_id",
-  "kind",
-  "status",
-  "model",
-  "prompt",
-  "aspect_ratio",
-  "refined_from",
-  "caption_style",
-  "output_url",
-  "credits_cost",
-  "error",
-  "vendor_phase",
-  "stalled",
-  "created_at",
-  "app_url"
-]New value: +[
+  "generation_id",
+  "kind",
+  "status",
+  "model",
+  "prompt",
+  "aspect_ratio",
+  "refined_from",
+  "caption_style",
+  "output_url",
+  "credits_cost",
+  "error",
+  "vendor_phase",
+  "stalled",
+  "ready_in_seconds",
+  "created_at",
+  "app_url"
+]

First observedOct 15, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations declare non-destructive, non-read-only, non-idempotent, closed-world. The description goes further by disclosing that a NEW generation is produced (originals preserved), that account entitlements/credits are consumed, and that the operation is asynchronous with get_generation as the wait mechanism. It omits any statement about failure modes or whether the source clip is consumed.

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 sentences, each earning its place: what it does, the input constraint, the follow-up. The core action is front-loaded with no 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?

An output schema exists, so return values needn't be described, and the async polling path is covered via get_generation. Remaining gaps are the meaning of the two source variants and any permission/ownership requirement for the clip, which are minor but real for a mutation tool.

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

Parameters4/5

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

Schema coverage is only 33%: 'subject' has a description but 'source' and 'voice_id' do not. The description compensates by stating the mutual-exclusivity constraint between voice_id and subject (not encoded in the schema) and defining subject as 'a Subject with an ElevenLabs voice'. It does not explain the two source variants (upload vs generation) that the anyOf offers.

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?

States a specific verb and resource ('Replace the speech voice in an owned clip'), names the voice provider (ElevenLabs), and specifies the output artifact ('saving a new generation'). This is clearly distinguishable from siblings like cast_voice (binds a voice to a Subject) and generate_voiceover (creates speech from scratch).

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?

It gives a hard selection rule for the two optional inputs ('Pass exactly one of voice_id or subject') and points at get_generation for waiting, but never states when to choose this tool over cast_voice or generate_voiceover, nor any prerequisite about the clip being owned. Usage is implied rather than guided.

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

All Kuro tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?