comfy-debug-preview

ComfyUI debug & preview

Inspect values mid-graph without changing them. Read / log / visualize / time / report. Nothing in this skill mutates the data flow — these nodes either pass through unchanged (Preview Bridge, TimerNodeKJ) or are pure sinks (ShowText, CConsoleAny).

The split:

Pack	Niche
comfyui-custom-scripts (pysssss)	ShowText — display text in node widget UI
comfyui_essentials	DisplayAny, ConsoleDebug, DebugTensorShape, BatchCount
comfyui-kjnodes	PreviewImageOrMask, FastPreview, VRAM_Debug, TimerNodeKJ, Sleep, Get(Image|Mask|Latent)SizeAndCount
ComfyUI-Crystools	CConsoleAny, CConsoleAnyToJson, CUtilsStatSystem (CPU/GPU/RAM monitor), CImageLoadWithMetadata, CMetadataExtractor, CMetadataCompare
bjornulf_custom_nodes	ShowFloat, ShowInt, ShowStringText, ShowJson, ImageDetails, VideoDetails
comfyui-dream-project	DreamStringToLog, DreamIntToLog, DreamFloatToLog, DreamJoinLog, DreamLogFile
comfyui_yvann-nodes	FloatsVisualizer (render a float array as a histogram image)
comfyui-impact-pack	Preview Bridge (Image) / Preview Bridge (Latent) — tee inspection while passing through
comfyui-easy-use	easy showAnything, easy showLoaderSettingsNames, imageCount, imagesCountInDirectory

When to Use This Skill

Use this skill when...	Use instead when...
Inspecting a value mid-graph without changing it (show/log/preview nodes)	Extracting metadata from a finished output file -> comfy-metadata
Checking VRAM/CPU/timing during a run	Computing the value being displayed -> comfy-math-strings

Sources of truth

• custom_nodes/comfyui-custom-scripts/py/show_text.py — pysssss ShowText
• custom_nodes/comfyui_essentials/misc.py — DisplayAny, ConsoleDebug, DebugTensorShape
• custom_nodes/comfyui-kjnodes/nodes/nodes.py — VRAM_Debug, TimerNodeKJ, Sleep, Get*SizeAndCount, FastPreview, PreviewImageOrMask
• custom_nodes/ComfyUI-Crystools/crystools/nodes_*.py — CConsoleAny*, CUtilsStatSystem, metadata nodes

Show-this-value decision

Value type	Best node	Why
STRING (short)	pysssss ShowText	Renders in the node widget; auto-resizes; persists in workflow JSON
STRING (long / multiline)	bjornulf ShowStringText or pysssss ShowText	Both wrap text; ShowText truncates after ~10 lines but expands on hover
ANY (don't know the type)	essentials DisplayAny or easy showAnything	Coerces to STRING and renders
FLOAT / INT	bjornulf ShowFloat / ShowInt	Specific formatters; cleaner display than DisplayAny
JSON / dict / list	bjornulf ShowJson or Crystools CConsoleAnyToJson	Pretty-prints with indentation
Tensor (latent / image) shape	essentials DebugTensorShape	Logs (B, C, H, W) to console; doesn't display in node UI
Float curve over a batch	yvann FloatsVisualizer	Renders the array as a histogram image
Console log (no widget)	essentials ConsoleDebug, Crystools CConsoleAny, dream DreamStringToLog	Output to server stdout/log only — invisible in editor; useful for batch jobs
Image (tee with passthrough)	impact Preview Bridge	Pass-through + preview in one node — see the data, keep the chain
Image (just preview, no passthrough)	ComfyUI core PreviewImage or kjnodes PreviewImageOrMask	The kjnodes variant auto-detects whether the input is image or mask

Where the display goes

• Node-widget UI (visible in the workflow editor): ShowText, ShowFloat, ShowInt, ShowStringText, ShowJson, DisplayAny, easy showAnything. These render INSIDE the node's body, expanding the node to fit the value.
• Server log / console (journalctl -u comfyui.service on this install): ConsoleDebug, DebugTensorShape, CConsoleAny, DreamStringToLog. No editor display — use these for batch jobs running headless via comfy run.
• On-disk log file: DreamLogFile appends to a configurable file path; useful for cross-queue tracking.
• Visible as image preview: PreviewImageOrMask, FastPreview, FloatsVisualizer. The preview shows in the standard preview pane.

Counts and sizes

Need	Node	Outputs
Image batch (B, H, W)	kjnodes GetImageSizeAndCount	width, height, batch_count
Mask (B, H, W)	kjnodes GetMaskSizeAndCount	width, height, batch_count
Latent (B, C, H, W)	kjnodes GetLatentSizeAndCount	width, height, batch_count
Just N (batch size)	essentials BatchCount	int
Image batch count (easy-use variant)	easy imageCount	int
Count image files in a directory	easy imagesCountInDirectory	int (with offset/limit)
Image file's metadata	bjornulf ImageDetails	width, height, channels, format, mode
Video file's metadata	bjornulf VideoDetails	width, height, fps, duration, codec

Get*SizeAndCount is the canonical choice — it emits w/h/batch as separate INTs that you can wire to math nodes or display.

System telemetry

For figuring out what's eating VRAM / CPU / RAM mid-graph:

Node	What it reports	When called
Crystools CUtilsStatSystem	CPU %, RAM used/total, GPU VRAM used/total (per-card)	Re-polls every time its output is consumed
kjnodes VRAM_Debug	One-shot VRAM snapshot to console	When the node executes
kjnodes TimerNodeKJ	Wall-clock elapsed time between start/end of a section	When the end node executes
kjnodes Sleep	Pauses execution for N seconds (throttling, not telemetry)	When executed

Per-section timing

                ┌─► TimerNodeKJ (start) ──────► (just a pass-through tag)
                │
upstream value ─┤
                │   (do stuff in between)
                │
                └─► TimerNodeKJ (end) ──► duration_seconds (FLOAT)
                                              │
                                              ▼
                                  bjornulf `ShowFloat`
                                  or DreamFloatToLog

Wire the same TimerNodeKJ id on both sides — the node remembers the start timestamp keyed by its instance and emits a duration on the "end" port.

Preview Bridge and the ExecutionBlocker pitfall

Impact's Preview Bridge (Image) / Preview Bridge (Latent) are the workhorse "see this and pass it through" nodes. Wire an image in, get the same image out, plus a preview in the editor.

Critical pitfall: Preview Bridge silently consumes ExecutionBlocker sentinels. If a path through the bridge gets blocked upstream, the bridge:

1. Shows nothing in the preview (no error, no indicator).
2. Does NOT propagate the blocker downstream — it converts the blocked path into a "no-op pass-through" of nothing.

Consequence: if you tee Preview Bridge off a path that may be blocked (e.g. behind an easy blocker), the downstream consumer of the bridge's output silently sees a None — not a blocker — and either errors with a type mismatch or proceeds with garbage.

Workaround: when blockers may appear in the path, use kjnodes FastPreview downstream of the bridge — FastPreview passes sentinels through correctly. Or branch the preview off BEFORE the blocker, not after.

Metadata extraction

For lightweight in-graph metadata reads (read PNG-embedded workflow JSON during a workflow run):

Node	Use
Crystools CImageLoadWithMetadata	Load image + emit its image.info PNG metadata as JSON
Crystools CMetadataExtractor	Pull a specific key from a metadata blob
Crystools CMetadataCompare	Diff two metadata blobs and report differences
bjornulf ImageDetails	Read width/height/format from any image — doesn't surface workflow JSON

For batch / cross-output-directory analysis ("which prompt produced all these images?", "scan output/ and find runs that used model X"), use the dedicated comfy-metadata skill — it covers the full range of metadata sources (PNG tEXt, WebP EXIF Make/Model, MP4 container, kijai WanVideoWrapper's comment blob, VHS metadata, .latent safetensors) and the scripts/scanners for batch inspection.

The Crystools nodes here are for inline metadata reads as part of a workflow's logic; comfy-metadata is for offline analysis.

Counter-pattern: timing/profiling vs the wrong layer

If a workflow is slow and you want to find the slow node:

• ✅ Use TimerNodeKJ around suspected sections.
• ✅ Use CUtilsStatSystem to log VRAM through the run.
• ✅ Check the ComfyUI server log (journalctl -u comfyui.service) — every node logs its execution time at the end of the run.
• ❌ Don't add Sleep "to give the GPU time" — it doesn't help, ComfyUI is synchronous within a queue.

For deep model-level profiling (CUDA timelines, sageattn vs flash attention comparisons, kernel-level), this skill is the wrong layer — consult the model-family skill (e.g. wan for radial sage attention discussion).

Recipes

"Why is my prompt different from what I typed?"

After all wildcard expansion, LoRA trigger autoload, and string manipulation, you want to see the literal STRING that hits the text encoder:

(your full prompt-assembly chain)
                │
                ▼
       (output STRING)
                │
       ┌────────┴────────┐
       │                 │
       ▼                 ▼
  CLIPTextEncode    ShowText (pysssss)

The ShowText widget will display the resolved prompt — visible in the editor after queue. Useful for catching wildcards that didn't resolve (__styles__ remained literal because the file was missing), or LoRA tags that came back empty.

Per-step time budget

You want to know how long each sampler in a 3-sampler chain takes:

LoadImage ─► TimerNodeKJ(start, id=t1) ─► Sampler#1 ─► TimerNodeKJ(end, id=t1) ─► dt1
                                              │              │
                                              │              ▼ DreamFloatToLog
                                              │
                                              └► TimerNodeKJ(start, id=t2) ─► Sampler#2 ─► …

Three Timer pairs, three durations logged. After the run, check the server log or the DreamLogFile output for a per-sampler breakdown.

VRAM watch during a long batch

LoadImage ──► CUtilsStatSystem ──► (continues to KSampler)
                    │
                    ▼ (writes a line per-poll to log)
              DreamStringToLog

CUtilsStatSystem polls VRAM on each evaluation. Wire its output through a logger so each queue tick records GPU state — easy to correlate OOMs with workflow position.

Surface batch counts before sampling

LoadImageBatchFromDir ──► IMAGE ───────► (downstream sampler)
                            │
                            ▼
                  GetImageSizeAndCount ──► width / height / batch_count
                                                          │
                                                          ▼
                                                   ShowInt

Before queuing a big batch, glance at the count to confirm you didn't accidentally load a directory of 500 images when you meant 5.

Gotchas

• ShowText updates AFTER queue completion, not live during the run. For mid-run display you need a console log (DebugTensorShape, CConsoleAny) plus tailing the server log.
• Preview Bridge swallows ExecutionBlocker — see above. Mitigations: tee off the path BEFORE any potential blocker, or use FastPreview downstream.
• CUtilsStatSystem only polls when its output is consumed. Wiring it to nothing means it never runs. Wire the output to a console logger or a ShowFloat to make it actually poll.
• DisplayAny truncates large strings to ~10 lines / ~1000 chars. For longer values use ShowStringText (bjornulf) which scrolls, or DreamStringToLog which writes to the server log without truncation.
• TimerNodeKJ start/end pairing: the id parameter must match between the start and end instances. Multiple Timer pairs with the same id cross-pollute their start times.
• Sleep is on the graph execution thread, not GPU. It blocks the entire queue, including unrelated parallel branches. Use only when intentionally throttling.
• FloatsVisualizer renders to image at fixed resolution — the output is an IMAGE, not a graph object. Wire it through PreviewImage to display.
• DreamLogFile opens the file in append mode each call — for high-frequency logging in a loop, file IO becomes the bottleneck. Use a console logger instead and tail the server log offline.
• Crystools metadata nodes operate on PNG image.info only — they don't read MP4/WebP/EXIF. For those, the offline comfy-metadata skill covers the full range.

Cross-refs

• comfy-math-strings — formatting numeric / string values before display (the math is in math-strings; the show is here).
• comfy-flow-control — Preview Bridge as a routing tee (flow-control's gotcha list also covers the blocker pitfall).
• comfy-metadata — deep metadata extraction across output directories: PNG tEXt / iTXt, WebP EXIF, MP4 container, kijai WanVideoWrapper / VHS comment blobs, .latent safetensors. When the question is "what produced this output file?" (offline / retrospective), reach for comfy-metadata. When the question is "what is this current image's PNG metadata?" (inline / live), use the Crystools nodes documented here.
• comfy-conditionals — easy showAnything on a BOOLEAN to confirm a predicate at queue time before trusting the branch decision.

Things this skill does NOT cover

• Offline / batch metadata analysis — → comfy-metadata.
• Performance profiling at the model layer (sageattn vs flash, KV cache, attention slicing) — → model-family skills (wan, z-image).
• Workflow-level reorganization to make a graph more debuggable (auto-layout, group cohesion) — → comfy-workflow-layout.
• Computing the values being displayed — → comfy-math-strings.
• The simplify user-level skill (review changed code) — that's a Claude Code agent skill, not a ComfyUI workflow skill.