Skip to main content
Glama

search_usd

Search the NVIDIA USD asset library by text description and load the best matching 3D asset into the scene.

Instructions

Search the NVIDIA USD asset library by text description, then load the best match.

Args: text_prompt: Text description of the 3D asset to search for. target_path: Prim path for the loaded result. position: [x, y, z] world position. scale: [sx, sy, sz] scale factors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scaleNo
positionNo
command_idNo
target_pathNo/World/my_usd
text_promptYes
idempotency_keyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

A3.9/5.0
Behavior3/5

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

No annotations exist, so the description must disclose side effects itself. It does state that the tool does more than search by saying 'then load the best match', alerting the agent to a scene-modifying action. However, it does not explain whether loading replaces an existing prim, what happens if no match is found, or whether a stage must already be open.

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?

One functional sentence plus a terse arg list with no filler. The core behavior is front-loaded and every line earns its place.

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?

For a tool that searches and then mutates a scene, the description is reasonably complete but missing important context: what happens on no match, whether target_path must exist or is auto-created, and the role of the undocumented command_id and idempotency_key parameters. The output schema helps with return values, but operational gaps remain.

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

Parameters3/5

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

Schema description coverage is 0%, so the args section must add meaning. It usefully explains text_prompt, target_path, position, and scale. However, two schema parameters, command_id and idempotency_key, receive no description at all, leaving their purpose to inference from names.

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 names a specific verb-resource pair: searching the NVIDIA USD asset library and loading the best match. This distinguishes it from generic loader or asset tools by tying the operation to a text description. It is immediately actionable.

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 clearly implies the right use case: the user has a text description and wants a matching asset loaded. It does not explicitly contrast with siblings like load_usd or spawn_nvidia_asset, but the intended context is evident without exclusion or alternative guidance.

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

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Tim0320/IsaacSim-MCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server