/comfyui-node-datatypes
ComfyUI data types - IMAGE, LATENT, MASK, CONDITIONING, MODEL, CLIP, VAE, AUDIO, VIDEO, 3D types, widget types, and custom types. Use when working with ComfyUI tensors, model types, or defining input/output data types.
$ npx -y skills add jtydhr88/comfyui-custom-node-skills --skill comfyui-node-datatypes --agent claude-codeHow it fires
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/comfyui-node-datatypes
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ComfyUI data types - IMAGE, LATENT, MASK, CONDITIONING, MODEL, CLIP, VAE, AUDIO, VIDEO, 3D types, widget types, and custom types. Use when working with ComfyUI tensors, model types, or defining input/output data types.
SKILL.md
comfyui-node-datatypes.SKILL.mdname: comfyui-node-datatypes
description: ComfyUI data types - IMAGE, LATENT, MASK, CONDITIONING, MODEL, CLIP, VAE, AUDIO, VIDEO, 3D types, widget types, and custom types. Use when working with ComfyUI tensors, model types, or defining input/output data types.
ComfyUI Data Types
ComfyUI uses specific data types for node inputs and outputs. Understanding tensor shapes and data formats is essential.
Complete Type Reference
Tensor/Data Types
| Type | V3 Class | Format | Description | |---|---|---|---| | IMAGE | `io.Image` | `torch.Tensor [B,H,W,C]` float32 0-1 | Batch of RGB images | | MASK | `io.Mask` | `torch.Tensor [H,W]` or `[B,H,W]` float32 0-1 | Grayscale masks | | LATENT | `io.Latent` | `{"samples": Tensor[B,C,H,W] or [B,C,T,H,W], "noise_mask"?: Tensor, "batch_index"?: list[int], "type"?: str}` | Latent space (4D image / 5D video) | | CONDITIONING | `io.Conditioning` | `list[tuple[Tensor, PooledDict]]` | Text conditioning with pooled outputs | | AUDIO | `io.Audio` | `{"waveform": Tensor[B,C,T], "sample_rate": int}` | Audio data | | VIDEO | `io.Video` | `VideoInput` ABC | Video data (abstract base class) | | SIGMAS | `io.Sigmas` | `torch.Tensor` 1D, length steps+1 | Noise schedule | | NOISE | `io.Noise` | Object with `generate_noise()` | Noise generator | | LORA_MODEL | `io.LoraModel` | `dict[str, torch.Tensor]` | LoRA weight deltas | | LOSS_MAP | `io.LossMap` | `{"loss": list[torch.Tensor]}` | Loss map | | TRACKS | `io.Tracks` | `{"track_path": Tensor, "track_visibility": Tensor}` | Motion tracking data | | WAN_CAMERA_EMBEDDING | `io.WanCameraEmbedding` | `torch.Tensor` | WAN camera embeddings | | LATENT_OPERATION | `io.LatentOperation` | `Callable[[Tensor], Tensor]` | Latent transform function | | TIMESTEPS_RANGE | `io.TimestepsRange` | `tuple[int, int]` | Range 0.0-1.0 | | DICT | `io.Dict` | `dict` | Generic dictionary | | ARRAY | `io.Array` | `list` | Generic list/array |
Model Types (opaque, typically pass-through)
| Type | V3 Class | Python Type | |---|---|---| | MODEL | `io.Model` | `ModelPatcher` | | CLIP | `io.Clip` | `CLIP` | | VAE | `io.Vae` | `VAE` | | CONTROL_NET | `io.ControlNet` | `ControlNet` | | CLIP_VISION | `io.ClipVision` | `ClipVisionModel` | | CLIP_VISION_OUTPUT | `io.ClipVisionOutput` | `ClipVisionOutput` | | STYLE_MODEL | `io.StyleModel` | `StyleModel` | | GLIGEN | `io.Gligen` | `ModelPatcher` (wrapping Gligen) | | UPSCALE_MODEL | `io.UpscaleModel` | `ImageModelDescriptor` | | BACKGROUND_REMOVAL | `io.BackgroundRemoval` | `BackgroundRemovalModel` (e.g. BiRefNet) | | LATENT_UPSCALE_MODEL | `io.LatentUpscaleModel` | Any | | SAMPLER | `io.Sampler` | `Sampler` | | GUIDER | `io.Guider` | `CFGGuider` | | HOOKS | `io.Hooks` | `HookGroup` | | HOOK_KEYFRAMES | `io.HookKeyframes` | `HookKeyframeGroup` | | MODEL_PATCH | `io.ModelPatch` | Any | | AUDIO_ENCODER | `io.AudioEncoder` | Any | | AUDIO_ENCODER_OUTPUT | `io.AudioEncoderOutput` | Any | | PHOTOMAKER | `io.Photomaker` | Any | | POINT | `io.Point` | Any | | FACE_ANALYSIS | `io.FaceAnalysis` | Any | | BBOX | `io.BBOX` | Any | | SEGS | `io.SEGS` | Any |
3D Types
| Type | V3 Class | Python Type | Description | |---|---|---|---| | MESH | `io.Mesh` | `MESH(vertices, faces)` | 3D mesh with vertices + faces tensors | | VOXEL | `io.Voxel` | `VOXEL(data)` | Voxel data tensor | | SPLAT | `io.Splat` | `SPLAT` | Gaussian splat data | | FILE_3D | `io.File3DAny` | `File3D` | Any supported 3D format | | FILE_3D_GLB | `io.File3DGLB` | `File3D` | Binary glTF | | FILE_3D_GLTF | `io.File3DGLTF` | `File3D` | JSON-based glTF | | FILE_3D_FBX | `io.File3DFBX` | `File3D` | FBX format | | FILE_3D_OBJ | `io.File3DOBJ` | `File3D` | OBJ format | | FILE_3D_STL | `io.File3DSTL` | `File3D` | STL format (3D printing) | | FILE_3D_USDZ | `io.File3DUSDZ` | `File3D` | Apple AR format | | FILE_3D_PLY | `io.File3DPLY` | `File3D` | PLY (point cloud / splat) | | FILE_3D_SPLAT | `io.File3DSPLAT` | `File3D` | .splat gaussian splat file | | FILE_3D_SPZ | `io.File3DSPZ` | `File3D` | Compressed splat (.spz) | | FILE_3D_KSPLAT | `io.File3DKSPLAT` | `File3D` | .ksplat format | | FILE_3D_SPLAT_ANY | `io.File3DSplatAny` | `File3D` | Any splat format | | FILE_3D_POINT_CLOUD_ANY | `io.File3DPointCloudAny` | `File3D` | Any point cloud format | | SVG | `io.SVG` | `SVG` | Scalable vector graphics | | LOAD_3D | `io.Load3D` | `Model3DDict` (see below) | 3D model with renders | | LOAD_3D_ANIMATION | `io.Load3DAnimation` | Same as Load3D | Animated 3D model | | LOAD3D_CAMERA | `io.Load3DCamera` | `CameraInfo` (see below) | 3D camera info | | LOAD3D_MODEL_INFO | `io.Load3DModelInfo` | `list[Model3DTransform]` | Per-model transforms (position/quaternion/scale) |
**Load3D.Model3DDict**: `{"image": str, "mask": str, "normal": str, "camera_info": CameraInfo, "recording"?: str, "model_3d_info"?: list[Model3DTransform]}`
**Load3DCamera.CameraInfo** (right-handed, Y-up, camera looks down -Z): required keys `position`, `target`, `zoom`, `cameraType` (`'perspective' | 'orthographic'`); optional keys `quaternion` (camera world rotation), `fov` (vertical, degrees, perspective only), `aspect`, `near`, `far`, `frustum` (orthographic only: `{left, right, top, bottom}`).
**Load3DModelInfo.Model3DTransform**: `{"position": dict, "quaternion": dict, "scale": dict}` in world space.
Widget Types (create UI controls)
| Type | V3 Class | Python Type | Description | |---|---|---|---| | INT | `io.Int` | `int` | Integer with min/max/step | | FLOAT | `io.Float` | `float` | Float with min/max/step/round | | STRING | `io.String` | `str` | Text (single/multi-line) | | BOOLEAN | `io.Boolean` | `bool` | Toggle with labels | | COMBO | `io.Combo` | `str` | Dropdown selection | | COMBO (multi) | `io.MultiCombo` | `list[str]` | Multi-select dropdown | | COLOR | `io.Color` | `str` (hex) | Color picker, default `#ffffff` | | COLORS | `io.Colors` | `list[str]` (hex) | Color palette (list of colors) | | BOUNDING_BOX | `io.BoundingBox` | `{"x": int, "y": int, "width": int
Read more
name: comfyui-node-datatypes description: ComfyUI data types - IMAGE, LATENT, MASK, CONDITIONING, MODEL, CLIP, VAE, AUDIO, VIDEO, 3D types, widget types, and custom types. Use when working with ComfyUI tensors, model types, or defining input/output data types.
ComfyUI Data Types
ComfyUI uses specific data types for node inputs and outputs. Understanding tensor shapes and data formats is essential.
Complete Type Reference
Tensor/Data Types
| Type | V3 Class | Format | Description | |---|---|---|---| | IMAGE | `io.Image` | `torch.Tensor [B,H,W,C]` float32 0-1 | Batch of RGB images | | MASK | `io.Mask` | `torch.Tensor [H,W]` or `[B,H,W]` float32 0-1 | Grayscale masks | | LATENT | `io.Latent` | `{"samples": Tensor[B,C,H,W] or [B,C,T,H,W], "noise_mask"?: Tensor, "batch_index"?: list[int], "type"?: str}` | Latent space (4D image / 5D video) | | CONDITIONING | `io.Conditioning` | `list[tuple[Tensor, PooledDict]]` | Text conditioning with pooled outputs | | AUDIO | `io.Audio` | `{"waveform": Tensor[B,C,T], "sample_rate": int}` | Audio data | | VIDEO | `io.Video` | `VideoInput` ABC | Video data (abstract base class) | | SIGMAS | `io.Sigmas` | `torch.Tensor` 1D, length steps+1 | Noise schedule | | NOISE | `io.Noise` | Object with `generate_noise()` | Noise generator | | LORA_MODEL | `io.LoraModel` | `dict[str, torch.Tensor]` | LoRA weight deltas | | LOSS_MAP | `io.LossMap` | `{"loss": list[torch.Tensor]}` | Loss map | | TRACKS | `io.Tracks` | `{"track_path": Tensor, "track_visibility": Tensor}` | Motion tracking data | | WAN_CAMERA_EMBEDDING | `io.WanCameraEmbedding` | `torch.Tensor` | WAN camera embeddings | | LATENT_OPERATION | `io.LatentOperation` | `Callable[[Tensor], Tensor]` | Latent transform function | | TIMESTEPS_RANGE | `io.TimestepsRange` | `tuple[int, int]` | Range 0.0-1.0 | | DICT | `io.Dict` | `dict` | Generic dictionary | | ARRAY | `io.Array` | `list` | Generic list/array |
Model Types (opaque, typically pass-through)
| Type | V3 Class | Python Type | |---|---|---| | MODEL | `io.Model` | `ModelPatcher` | | CLIP | `io.Clip` | `CLIP` | | VAE | `io.Vae` | `VAE` | | CONTROL_NET | `io.ControlNet` | `ControlNet` | | CLIP_VISION | `io.ClipVision` | `ClipVisionModel` | | CLIP_VISION_OUTPUT | `io.ClipVisionOutput` | `ClipVisionOutput` | | STYLE_MODEL | `io.StyleModel` | `StyleModel` | | GLIGEN | `io.Gligen` | `ModelPatcher` (wrapping Gligen) | | UPSCALE_MODEL | `io.UpscaleModel` | `ImageModelDescriptor` | | BACKGROUND_REMOVAL | `io.BackgroundRemoval` | `BackgroundRemovalModel` (e.g. BiRefNet) | | LATENT_UPSCALE_MODEL | `io.LatentUpscaleModel` | Any | | SAMPLER | `io.Sampler` | `Sampler` | | GUIDER | `io.Guider` | `CFGGuider` | | HOOKS | `io.Hooks` | `HookGroup` | | HOOK_KEYFRAMES | `io.HookKeyframes` | `HookKeyframeGroup` | | MODEL_PATCH | `io.ModelPatch` | Any | | AUDIO_ENCODER | `io.AudioEncoder` | Any | | AUDIO_ENCODER_OUTPUT | `io.AudioEncoderOutput` | Any | | PHOTOMAKER | `io.Photomaker` | Any | | POINT | `io.Point` | Any | | FACE_ANALYSIS | `io.FaceAnalysis` | Any | | BBOX | `io.BBOX` | Any | | SEGS | `io.SEGS` | Any |
3D Types
| Type | V3 Class | Python Type | Description | |---|---|---|---| | MESH | `io.Mesh` | `MESH(vertices, faces)` | 3D mesh with vertices + faces tensors | | VOXEL | `io.Voxel` | `VOXEL(data)` | Voxel data tensor | | SPLAT | `io.Splat` | `SPLAT` | Gaussian splat data | | FILE_3D | `io.File3DAny` | `File3D` | Any supported 3D format | | FILE_3D_GLB | `io.File3DGLB` | `File3D` | Binary glTF | | FILE_3D_GLTF | `io.File3DGLTF` | `File3D` | JSON-based glTF | | FILE_3D_FBX | `io.File3DFBX` | `File3D` | FBX format | | FILE_3D_OBJ | `io.File3DOBJ` | `File3D` | OBJ format | | FILE_3D_STL | `io.File3DSTL` | `File3D` | STL format (3D printing) | | FILE_3D_USDZ | `io.File3DUSDZ` | `File3D` | Apple AR format | | FILE_3D_PLY | `io.File3DPLY` | `File3D` | PLY (point cloud / splat) | | FILE_3D_SPLAT | `io.File3DSPLAT` | `File3D` | .splat gaussian splat file | | FILE_3D_SPZ | `io.File3DSPZ` | `File3D` | Compressed splat (.spz) | | FILE_3D_KSPLAT | `io.File3DKSPLAT` | `File3D` | .ksplat format | | FILE_3D_SPLAT_ANY | `io.File3DSplatAny` | `File3D` | Any splat format | | FILE_3D_POINT_CLOUD_ANY | `io.File3DPointCloudAny` | `File3D` | Any point cloud format | | SVG | `io.SVG` | `SVG` | Scalable vector graphics | | LOAD_3D | `io.Load3D` | `Model3DDict` (see below) | 3D model with renders | | LOAD_3D_ANIMATION | `io.Load3DAnimation` | Same as Load3D | Animated 3D model | | LOAD3D_CAMERA | `io.Load3DCamera` | `CameraInfo` (see below) | 3D camera info | | LOAD3D_MODEL_INFO | `io.Load3DModelInfo` | `list[Model3DTransform]` | Per-model transforms (position/quaternion/scale) |
**Load3D.Model3DDict**: `{"image": str, "mask": str, "normal": str, "camera_info": CameraInfo, "recording"?: str, "model_3d_info"?: list[Model3DTransform]}`
**Load3DCamera.CameraInfo** (right-handed, Y-up, camera looks down -Z): required keys `position`, `target`, `zoom`, `cameraType` (`'perspective' | 'orthographic'`); optional keys `quaternion` (camera world rotation), `fov` (vertical, degrees, perspective only), `aspect`, `near`, `far`, `frustum` (orthographic only: `{left, right, top, bottom}`).
**Load3DModelInfo.Model3DTransform**: `{"position": dict, "quaternion": dict, "scale": dict}` in world space.
Widget Types (create UI controls)
| Type | V3 Class | Python Type | Description | |---|---|---|---| | INT | `io.Int` | `int` | Integer with min/max/step | | FLOAT | `io.Float` | `float` | Float with min/max/step/round | | STRING | `io.String` | `str` | Text (single/multi-line) | | BOOLEAN | `io.Boolean` | `bool` | Toggle with labels | | COMBO | `io.Combo` | `str` | Dropdown selection | | COMBO (multi) | `io.MultiCombo` | `list[str]` | Multi-select dropdown | | COLOR | `io.Color` | `str` (hex) | Color picker, default `#ffffff` | | COLORS | `io.Colors` | `list[str]` (hex) | Color palette (list of colors) | | BOUNDING_BOX | `io.BoundingBox` | `{"x": int, "y": int, "width": int
A curated collection of agent skills (for Claude Code and OpenAI Codex) for developing ComfyUI custom nodes. These skills give the agent comprehensive knowledge of the ComfyUI node system, covering both the V3 (recommended) and V1 (legacy) APIs.
Repo: jtydhr88/comfyui-custom-node-skills
Other skills on comfyui-custom-node-skills.
- /comfyui-node-advanced
ComfyUI advanced node patterns - MatchType, Autogrow, DynamicCombo, node expansion, MultiType, wildcard inputs. Use when building complex nodes with dynamic inputs, type matching, or node expansion.
Open skill - /comfyui-node-basics
ComfyUI custom node fundamentals - V3 node structure, Schema, inputs/outputs, registration. Use when creating new ComfyUI custom nodes, defining node classes, or setting up a custom node project.
Open skill - /comfyui-node-frontend
ComfyUI frontend JavaScript extensions - hooks, widgets, sidebar tabs, commands, settings, toasts, dialogs. Use when adding UI features to custom nodes, creating custom widgets, or extending the ComfyUI frontend.
Open skill - /comfyui-node-inputs
ComfyUI node input types - INT, FLOAT, STRING, BOOLEAN, COMBO widgets, hidden inputs, optional inputs, lazy inputs, force_input. Use when configuring node inputs, adding widgets, or customizing input behavior.
Open skill - /comfyui-node-lifecycle
ComfyUI node execution lifecycle - caching, fingerprint_inputs/IS_CHANGED, validate_inputs/VALIDATE_INPUTS, check_lazy_status, execution order. Use when debugging execution, implementing caching control, input validation, or understanding execution flow.
Open skill - /comfyui-node-migration
ComfyUI V1 to V3 node migration - converting legacy nodes to the V3 API. Use when migrating existing custom nodes from V1 to V3, understanding differences between API versions, or modernizing node code.
Open skill

