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list_avatars

List saved avatars to reuse identical faces across videos, passing the avatar name or ID to generation tools.

Instructions

List the user's SAVED avatars — reusable face identities, the visual equivalent of cloned voices. Free, no tokens. Returns [{id, name, image, voice}] where voice is the avatar's default cloned-voice name (may be empty). A saved avatar is a stored front-facing head-and-shoulders portrait that recurs IDENTICALLY across videos. Use it instead of describing a face in words: pass the avatar's NAME as avatar to generate_talking_avatar (reuses the exact same face every time, no per-call drift), or pass avatar:<id> as face_swap_video.face_image_url. Saved avatars are created in the avots app / Telegram (a generated talking-avatar can be saved) or via create_avatar.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the return structure, the meaning of the `voice` field, and how avatars are created. It implies a read-only operation with no side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is detailed but front-loads the core purpose. It could be slightly more concise, but every sentence adds value. The structure is logical.

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?

Given the absence of an output schema, the description fully explains the return format and the concept of saved avatars. It covers what the tool does, what the output means, and how to use it downstream.

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?

There are no parameters, so the baseline is 4. The description adds value by explaining the output structure and usage, which is sufficient.

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 clearly states the tool lists the user's saved avatars, defines what a saved avatar is, and explains its purpose as a reusable face identity. It distinguishes from siblings by showing how the output is used with generate_talking_avatar and face_swap_video.

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?

The description explains when to use the tool (to retrieve avatars for reuse) and provides explicit guidance on how to use the returned data. It mentions 'Free, no tokens' but does not explicitly state when not to use it; however, the context is clear.

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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