List available avatars for auto-mode videos (the stock catalogue plus the account's own avatars). Stock avatars are grouped by person, each with a looks array — pass a looks[].avatar_id (or an owned avatar's id) as avatar_id in create_auto_video. Use search/limit to keep responses small.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max avatars to return (default 20). | |
| gender | No | ||
| search | No | Filter avatars by name. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses that stock avatars are 'grouped by person, each with a `looks` array', and mentions key fields. It does not mention side effects or rate limits, but as a read-only list operation, this is adequate. The structural detail adds value beyond a generic 'list avatars'.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose, and contains no fluff. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with 3 optional params and no output schema. The description explains how the output feeds into another tool (create_auto_video), which is valuable context. It does not detail the full return structure, but for a list tool, this is reasonably complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67% (two of three parameters have descriptions). The description adds meaning by explaining how search and limit are used to keep responses small. It does not mention gender, but the enum provides clarity. Overall, the description complements the schema well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'List available avatars for auto-mode videos'. It specifies the resource (avatars) and the verb (list). It also distinguishes from siblings by mentioning the connection to create_auto_video and the structure of stock vs owned avatars.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly explains when to use this tool (to obtain avatars for auto-mode videos) and how to use the results: 'pass a looks[].avatar_id (or an owned avatar's id) as `avatar_id` in create_auto_video'. It also advises on parameter use: 'Use `search`/`limit` to keep responses small'.
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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Each tool has a clear, distinct purpose. There is no overlap between tools like check_account and check_configuration, or between the two create video modes. All list tools target different entities, and the remaining tools serve unique roles (estimate credits, get video, wait for video, render preview).
All tool names follow a consistent verb_noun pattern in snake_case, such as check_account, create_auto_video, list_models. This makes it easy to predict tool names and understand their purpose.
With 13 tools, the number is well-scoped for a video generation API. It covers setup, account management, creation (two modes), credit estimation, retrieval, listing of various resources, and video waiting. No tool feels redundant or missing.
The tool surface covers the core workflow well: configuration check, account info, video creation (both auto and manual), credit estimation, retrieval, and listing. However, there are no tools for updating or deleting videos, nor for managing resources beyond listing (e.g., creating avatars or brand kits). These are minor gaps.
