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capture_camera_output

Capture depth, segmentation, normals, or motion vectors from a simulated camera in Isaac Sim. Specify the camera's prim path and output type to retrieve data as metadata, artifact, or inline bytes.

Instructions

Capture a typed RTX camera annotator output.

Args: prim_path: Prim path of the camera. output_type: depth, distance_to_image_plane, semantic_segmentation, instance_segmentation, instance_id_segmentation, normals, or motion_vectors. output_path: Optional explicit .npy path for artifact mode. return_mode: metadata, artifact, or inline. Defaults to artifact. inline_max_bytes: Maximum raw bytes allowed in inline mode. Maximum is 4 MiB.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prim_pathNo/World/Camera
command_idNo
output_pathNo
output_typeNodepth
return_modeNoartifact
idempotency_keyNo
inline_max_bytesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does reveal meaningful non-obvious behavior: output_path is for artifact mode, inline_max_bytes caps inline mode at 4 MiB, and return_mode defaults to artifact. However, it does not explain side effects of artifact mode, what metadata mode returns, or any failure conditions, so coverage is partial.

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 compact and front-loaded with the core purpose, then presents parameters as a tight list. Each listed parameter earns its place with a concrete detail, with no filler or redundancy. It loses a point mainly for not being structured into behavioral prose.

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?

The description is reasonably complete for the main capture workflow given that an output schema exists, so return values are covered elsewhere. But two schema parameters are undocumented, and there is no context on output modes or artifact side effects, which matters more because no annotations are present.

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 description must compensate. It adds value for 5 of 7 parameters: prim_path, output_type with allowed values, output_path purpose, return_mode options/default, and inline_max_bytes cap. It omits command_id and idempotency_key entirely, leaving those two params unexplained.

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 uses a specific verb and resource ('Capture a typed RTX camera annotator output') and enumerates the distinct output types (depth, segmentation, normals, motion_vectors), which makes its scope clear. It does not explicitly differentiate from sibling tools like capture_image, but the term 'typed annotator output' plus the listed modes is enough to set it apart.

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?

No guidance is given about when to use this tool versus alternatives such as capture_image, read_artifact, or get_artifact_info. The description covers parameter mechanics but says nothing about selection criteria or exclusions.

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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