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nv_list_models

Discover which AI models are available on your NVIDIA account. Filter by capability code, vision, reasoning, or embedding to find the right model.

Instructions

List models available on the account, tagged by capability.

Args: category: optional filter, e.g. "code", "vision", "reasoning", "embedding". refresh: bypass the 1-hour catalog cache.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refreshNo
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does mention the 1-hour catalog cache and the refresh parameter to bypass it, which is useful. However, it does not describe other potential side effects, permissions, or output characteristics, leaving some gaps for a tool with no safety annotations.

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 exceptionally concise: one declarative sentence for the purpose followed by a tight list of parameters. It is front-loaded and contains no extraneous words.

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?

The tool has an output schema, so return values are already covered. The two optional parameters are clearly explained, and the cache behavior is mentioned. For a simple listing tool, the description covers all necessary context without being verbose.

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

Parameters5/5

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

The input schema provides no descriptions for the parameters, but the description fully compensates by explaining 'category' as an optional filter with concrete examples and 'refresh' as a cache bypass. This adds meaningful semantics beyond the schema's bare names and types.

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's purpose with the verb 'List', the resource 'models', and the scope 'available on the account, tagged by capability'. This distinguishes it from sibling tools like nv_route or nv_call, making the purpose unambiguous.

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 provides clear context for when to use the tool: listing models, optionally filtered by category, with a refresh option. However, it does not name alternatives or specify exclusions, so it lacks the explicit 'when-not-to-use' guidance that would earn a 5.

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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