ComfyUI
SkillDev tools"Use ComfyUI as a modular AI content-creation engine: launch and
Available today. Use it from your connected AI after setup.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the ComfyUI skill
What this skill tells your AI
The instructions your AI receives, as published by vectorspacelab/arex-skill in skills/repositories/repo-skills/comfy-ui/SKILL.md and read by ahel’s review.
Use this repo skill when a user asks for help with ComfyUI workflows, automation, server/API usage, custom nodes, model folder configuration, backend/memory flags, or prompt graph debugging.
ComfyUI is a node-graph AI creation engine for image, video, audio, 3D, and model-tooling workflows. Treat it as an application/runtime with a Python launch script, HTTP/websocket APIs, a node registry, JSON prompt graphs, model-folder conventions, optional hosted API nodes, and hardware-sensitive backend behavior.
Start Here
- Identify the task surface: server/API automation, prompt graph execution, node authoring, or model/backend setup.
- If the user has a workflow JSON, decide whether it is API prompt JSON or UI workflow JSON before sending it to
/prompt. - If the user has a model-loading error, separate graph-node input issues from model search path/backend issues.
- If the user has a custom node problem, inspect mappings and node schemas before debugging prompt execution.
- If the user is exposing a server, make network, CORS, TLS, credential, and API-node choices explicit.
Routes
sub-skills/server-api/: launch ComfyUI, choose server-facing CLI flags, queue API prompt JSON over HTTP, monitor websocket progress, fetch history/output files, use app/user/model/assets routes, and troubleshoot server/API failures.sub-skills/workflow-execution/: validate and debug API prompt JSON, distinguish UI workflow exports from executable prompts, reason about graph links, caching, async/lazy execution, blueprints/templates, and inference failure boundaries.sub-skills/custom-nodes/: implement, scaffold, inspect, and troubleshoot custom nodes using classicINPUT_TYPESclasses,NODE_CLASS_MAPPINGS, hidden inputs, async validation, publiccomfy_apiAPIs, and API-provider nodes.sub-skills/models-config/: configure model folders andextra_model_paths.yaml, understand checkpoint/LoRA/VAE/controlnet categories, choose backend/VRAM flags, diagnose missing models, and reason about supported model families/quantization.
Common Decisions
- Launching locally: start local-only unless remote access is required:
python main.py --listen 127.0.0.1 --port 8188. - Submitting workflows: use API-format prompt JSON for
/prompt; normal UI workflow JSON contains canvas metadata and must be exported/converted first. - Getting outputs: queue with
/prompt, wait on/wsor poll/history/{prompt_id}, then download file outputs with/viewusing exact history metadata. - Using API nodes: pass hosted Comfy API credentials through request
extra_dataor hidden node credentials; never hardcode API keys in workflow JSON or scripts. - Model placement: put each model file in the category its loader node searches, or register shared paths through
extra_model_paths.yaml. - Backend failures: simplify to explicit CPU/CUDA/ROCm/MPS/DirectML flags, disable custom/API nodes while isolating startup failures, then re-enable pieces gradually.
Bundled References
references/troubleshooting.mdcovers cross-cutting install/import, launch, prompt, custom-node, model-path, backend, credential, and security failures.references/repo-provenance.mdrecords the source snapshot and evidence paths used to create this skill for future staleness checks.
Bundled Scripts
Most reusable scripts are owned by sub-skills because they operate on a specific surface:
sub-skills/server-api/scripts/comfy_api_client.py: validate, queue, wait for history, and download outputs through REST.sub-skills/server-api/scripts/comfy_websocket_monitor.py: queue and monitor websocket progress while ignoring binary preview frames by default.sub-skills/workflow-execution/scripts/validate_prompt_graph.py: structurally validate API prompt JSON without importing ComfyUI or loading models.sub-skills/custom-nodes/scripts/scaffold_custom_node.py: generate a safe starter custom node package.sub-skills/custom-nodes/scripts/inspect_node_definitions.py: statically inspect classic node mappings and common schema mistakes.sub-skills/models-config/scripts/validate_extra_model_paths.py: validateextra_model_paths.yamlshape and referenced directories.
Safety Notes
- Do not expose ComfyUI on a public interface with permissive CORS and no external authentication boundary.
- Do not run untrusted custom nodes or hosted API-node workflows without reviewing network, credential, and filesystem effects.
- Do not assume a workflow that validates structurally can execute: model files, node registry contents, optional dependencies, credentials, and backend hardware still matter.
- Do not embed local paths, API keys, generated output paths, or private server URLs in reusable workflows or scripts.
Signals
- GitHub stars
- 266
- Forks
- 21
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
comfy-ui- Source
- github.com/vectorspacelab/arex-skill