troubleshooting

troubleshooting is a skill for Claude Code, Codex from sandyup/comfyui-mcp. It costs 28 tokens per session (4,795 once invoked), scanned A, original, MIT.

A guide for diagnosing failed ComfyUI image-generation workflows, including out-of-memory errors, missing nodes, data-type mismatches, and black outputs.

In plain words
What is it for?
Use it when a ComfyUI run stops with an error, runs out of GPU memory, cannot find a node or model, or produces a black image.
Why use it?
It gives a structured way to find the failing node, inspect logs and execution history, check input requirements, and confirm that required model files exist.

Skill for Claude CodeCodex

Part of the comfy plugin — 32 skills, 11 commands, 4 agents, 2 hooks shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/sandyup/comfyui-mcp/troubleshooting
Any agent
npx skills add sandyup/comfyui-mcp --skill troubleshooting
Clone the repo
git clone --depth 1 https://github.com/sandyup/comfyui-mcp

Made for: Claude Code, Codex.

Or install comfy, the plugin that ships this one along with the rest of its 32 skills, 11 commands, 4 agents, 2 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for troubleshooting

README.md
[![agentmods](https://agentmods.dev/badge/skills/sandyup/comfyui-mcp/troubleshooting.svg)](https://agentmods.dev/skills/sandyup/comfyui-mcp/troubleshooting)
Your own site
<a href="https://agentmods.dev/skills/sandyup/comfyui-mcp/troubleshooting"><img src="https://agentmods.dev/badge/skills/sandyup/comfyui-mcp/troubleshooting.svg" alt="Measured on agentmods" height="20"></a>
Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,795 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00028 $0.04795
Opus 5 $0.00014 $0.02397
Sonnet 5 $0.00006 $0.00959
Haiku 4.5 $0.00003 $0.00479

Measured 4d ago against content hash d70c4b4aefbd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

troubleshooting scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugin/skills/troubleshooting/SKILL.md · 493 lines

How it starts

The opening of the file, as written. The whole thing — 493 lines — stays where its author put it; the contents beside it link to each section on GitHub.

ComfyUI Troubleshooting Guide

Render completes but looks WRONG (artifacts, wrong subject/pose/color, a ControlNet/mask/LoRA not taking, a refiner degrading it)? That's not an error — use the debug-render skill (read_skill("debug-render")): localize the bad stage with run-to-node (panel_run to_node_id) by previewing intermediate steps. This guide is for runs that fail with an error/OOM/missing node.

Error Diagnosis Strategy

When a workflow fails, follow this systematic approach:

  1. Get the error: Use get_history to retrieve the execution result with full traceback
  2. Check logs: Use get_logs with keyword filters like "error", "warning", "traceback"
  3. Identify the failing node: The history response includes the node_id and node_type that failed
  4. Cross-reference inputs: Use get_node_info to verify the failing node's expected input schema
  5. Check models: Use list_local_models to verify all referenced model files exist

Out of Memory (OOM)

Error Pattern

torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate X MiB.
GPU 0 has a total capacity of 24.00 GiB of which X MiB is free.

Or:

RuntimeError: CUDA error: out of memory

Root Cause

The GPU does not have enough VRAM to hold the model weights, intermediate tensors, and latent images simultaneously. Common triggers:

  • High resolution images (2048x2048+)
  • Multiple models loaded simultaneously
  • FP32 precision models on limited VRAM
  • Video generation (LTXV, AnimateDiff) with many frames
  • Large batch sizes

Fixes (in order of preference)

  1. Reduce resolution: Drop to the model's native resolution (512 for SD 1.5, 1024 for SDXL/Flux)
  2. Use FP8/FP16 quantized models: FP8 Flux models use ~8GB vs ~24GB for FP16
    • Search for FP8 variants: search_models("flux fp8") or search_models("sdxl fp8")
  3. Launch flags (the VRAM ladder): offload aggressively via ComfyUI CLI flags —
    • --lowvram — offload text encoders / model parts to CPU
    • --novram — extreme offload; the go-to for long video (LTX 2 / WAN) OOM
    • --cache-none — cache nothing (lowest RAM/VRAM); combine with --novram
    • --reserve-vram N — reserve N GB so the GPU stops spilling into slow shared VRAM (Windows); typical 24
    • --disable-smart-memory — force offload to RAM when a run gets stuck / intermittently OOMs
    • Full matrix + recipes: comfyui-launch-flags
  4. Free VRAM between generations: ComfyUI should auto-manage, but restarting clears leaked memory
  5. Use tiled VAE decoding: For high-resolution images, tile the VAE decode step
    • Node: VAEDecodeTiled instead of VAEDecode
    • Breaks the image into tiles, decodes each separately, and stitches them together
  6. Reduce batch size: Set batch_size to 1 in EmptyLatentImage
  7. Avoid multiple models: Don't load two full checkpoints simultaneously — use one checkpoint and LoRAs instead
  8. For LTXV/video: Always use FP8 quantized video models on 24GB cards

Read the full file on GitHub · 493 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 493 lines · 28 tokens per session scan A d70c4b4aefbd

Subscribe to this mod's changes

troubleshooting is a skill published in the GitHub repository sandyup/comfyui-mcp (1 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 4,795 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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