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list_models

Discover and view all available AI models, including custom ones, for selection and management within the Open WebUI platform.

Instructions

List all available models including custom models.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists models, implying a read-only operation, but does not disclose any behavioral traits such as pagination, rate limits, authentication requirements, or what 'available' means in context. This leaves significant gaps in understanding how the tool behaves beyond its basic function.

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 a single, efficient sentence: 'List all available models including custom models.' It is front-loaded with the core action and resource, with no wasted words or redundant information. Every part of the sentence contributes directly to understanding the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 0 parameters, 100% schema coverage, and an output schema exists (which should describe return values), the description is minimally complete. However, it lacks behavioral context (e.g., how models are listed, any limitations), and with no annotations, it does not fully compensate for missing details. It is adequate but has clear gaps in providing a comprehensive understanding.

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?

The tool has 0 parameters, with 100% schema description coverage (since there are no parameters to describe). The description does not need to add parameter semantics, as there are none to explain. A baseline score of 4 is appropriate because the description adequately covers the tool's purpose without unnecessary parameter details.

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?

The description clearly states the tool's purpose: 'List all available models including custom models.' It specifies the verb ('List') and resource ('models'), and includes scope ('all available' and 'custom models'). However, it does not explicitly differentiate from sibling tools like 'get_model' or 'get_models_config', which might retrieve specific models or configurations, so it lacks full sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any context, prerequisites, or exclusions, such as comparing to 'get_model' for a single model or 'get_models_config' for configuration details. Without such guidance, users must infer usage from the tool name alone.

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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