node-reference

name	node-reference
description	Common ComfyUI node types and workflow patterns. Use when suggesting nodes or explaining workflows.

Common Node Types Reference

This reference helps you suggest appropriate nodes for user needs.

Loaders & Models

• CheckpointLoaderSimple: Loads SD model (outputs: MODEL, CLIP, VAE)
• LoraLoader: Adds LoRA to model (inputs: MODEL, CLIP)
• VAELoader: Loads separate VAE
• ControlNetLoader: Loads ControlNet models

Conditioning (Prompts)

• CLIPTextEncode: Positive/negative prompts (input: CLIP, text)
• ConditioningCombine: Combines multiple conditionings
• ConditioningSetArea: Area conditioning for inpainting

Latents

• EmptyLatentImage: Creates blank latent (specify width/height)
• VAEEncode: Image to latent (input: VAE, IMAGE)
• VAEDecode: Latent to image (input: VAE, LATENT)
• LatentUpscale: Upscale latents

Sampling

• KSampler: Standard sampler (inputs: MODEL, LATENT, positive, negative)
• KSamplerAdvanced: More control over sampling
• SamplerCustom: Custom sampling pipeline

Image Processing

• LoadImage: Load from disk
• SaveImage: Save to disk
• ImageScale: Resize images
• ImageUpscaleWithModel: AI upscaling
• ImageBatch: Combine images into batch

Utilities

• PrimitiveNode: Store constants/values
• Reroute: Clean up connections
• Note: Add notes/comments

Common Workflows

Important: This section is a conceptual reference only. Do not apply or generate workflows from these patterns unless you have followed the workflow-guardrails skill and verified installed nodes and models.

Basic txt2img: CheckpointLoaderSimple → KSampler → VAEDecode → SaveImage ↓ CLIPTextEncode (positive) CLIPTextEncode (negative) EmptyLatentImage

img2img: CheckpointLoaderSimple → KSampler → VAEDecode → SaveImage LoadImage → VAEEncode ↗

Common Widget Names

Use these with setNodeWidgetValue. Call getWorkflowInfo with includeNodeDetails: true to confirm exact names.

• KSampler: seed, steps (number), cfg (number), sampler_name (string: "euler", "euler_ancestral", "dpmpp_2m", etc.), scheduler (string: "normal", "karras", "exponential", etc.), denoise (number: 0.0–1.0)
• EmptyLatentImage: width (number), height (number), batch_size (number)
• CLIPTextEncode: text (string) — use fillPromptNode for convenience
• SaveImage: filename_prefix (string)
• KSamplerAdvanced: add_noise ("enable"/"disable"), noise_seed, steps, cfg, sampler_name, scheduler, start_at_step, end_at_step, return_with_leftover_noise ("disable"/"enable")
• ImageScale: upscale_method (string), width (number), height (number), crop (string)

Prompt Writing Guide

When filling CLIPTextEncode text widgets:

Positive prompt structure: subject, style/medium, quality modifiers, lighting/mood

• Example: "a fluffy orange cat sitting on a windowsill, digital painting, highly detailed, warm afternoon sunlight"

Negative prompt terms: things to avoid in the generation

• Example: "blurry, low quality, deformed, ugly, watermark, text, oversaturated"

Tips:

• Be specific and descriptive for positive prompts
• Separate concepts with commas
• Quality terms like "masterpiece, best quality, highly detailed" can help
• For negative, list common artifacts to avoid