Comfyui Workflow

Universal ComfyUI workflow executor with 33+ workflow templates. Self-describing — use --inspect on ANY workflow to discover inputs and outputs automatically. Works with local ComfyUI, Windows Portable via WSL, or remote servers.

ComfyUI Workflows — Agent Usage Guide

⚠️ READ-ONLY WARNING: The scripts in this skill (comfy_run.py, comfy_api.py) are production-validated and must not be modified. They handle 33+ workflow JSONs with complex LiteGraph→API conversion, subgraph expansion, bypass resolution, and multi-format output downloading. Any modification risks breaking all workflows. Only read and use the scripts — never edit them.

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Requirements

Before using this skill, ensure your environment meets these requirements:

Requirement	Details
Python	3.10 or higher
pip packages	websocket-client, requests
ComfyUI server	Must be running before executing workflows
Token	Required if ComfyUI has authentication enabled

Install Python dependencies:

bash

pip install websocket-client requests

Configuration Options

Variable	Description	Default
COMFY_HOST	ComfyUI server address	127.0.0.1:8188
COMFY_WORKFLOW_DIRS	Additional workflow directories	(none)

Credentials

Credential	Required	Source
ComfyUI Token	Only if auth enabled	ComfyUI settings page

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Personal Configuration Required

Before using this skill, ensure these items are configured for your environment:

Item	Description	Where to Configure
comfy_host	Your ComfyUI server address	scripts/config.json or COMFY_HOST env
ComfyUI server	Must be running before executing workflows	Start manually
Model paths	Your local model directories	MODELS_INVENTORY.md (for reference)
Token	ComfyUI authentication token	Get from ComfyUI settings
Workflow files	Your own workflow JSON files	workflows/ directory (see note below)

Quick Setup

1. Start ComfyUI

Start your ComfyUI server manually before executing any workflows. The skill expects ComfyUI to be running at the configured host.

2. Configure Connection

Create scripts/config.json:

json

{
  "comfy_host": "127.0.0.1:8188",
  "workflow_dirs": []
}

Or set environment variables:

bash

export COMFY_HOST="127.0.0.1:8188"

3. Install Dependencies

bash

pip install websocket-client requests

4. Add Your Workflows

Place workflow JSON files in workflows/ directory, organized by category:

text

workflows/
├── Image-Text/
│   ├── workflow1.json
│   └── workflow2.json
├── Image-Edit/
│   └── ...
└── Video/
    └── ...

Shell Variables (use in all commands)

bash

VENV=python3  # or path to your venv
SCRIPT=/path/to/comfyui-workflow-skill/scripts/comfy_run.py

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End-to-End Workflow (Steps 0–5)

Step 0 — Ensure ComfyUI Is Running

Start ComfyUI manually. Verify it's accessible at http://127.0.0.1:8188.

Step 1 — List Available Workflows

bash

$VENV $SCRIPT --list

Step 2 — Inspect the Workflow

bash

$VENV $SCRIPT -w "workflow_name" --inspect

Step 3 — Prepare Inputs

bash

--prompt "your prompt"           # Text prompts
--image /path/to/image.jpg       # Image inputs
--audio /path/to/audio.wav       # Audio inputs
--video /path/to/video.mp4       # Video inputs
--width 1024 --height 1024       # Resolution
--steps 50 --cfg 4.0 --seed 42   # Sampler settings
--override '{"node_id": {"key": value}}'  # Advanced overrides

Step 4 — Execute

bash

$VENV $SCRIPT -w "workflow_name" --prompt "..." -o /tmp

Step 5 — Collect Outputs

Outputs are saved to the -o directory with auto-generated prefixes.

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CLI Reference

text

Usage: comfy_run.py [-w WORKFLOW] [options]

Modes:
  --list              List all available workflows
  --inspect           Human-readable input/output inspection
  --inspect-json      Machine-readable JSON inspection
  --dry-run           Print API JSON without executing
  --queue             Submit to queue and return immediately
  --status [IDs...]   Check queue state

Input customization:
  --prompt, -p TEXT        Positive prompt
  --negative, -n TEXT      Negative prompt
  --image, -i PATH [...]   Input image(s)
  --audio, -a PATH [...]   Input audio file(s)
  --video, -v PATH [...]   Input video file(s)

Generation settings:
  --width, -W INT          Output width
  --height, -H INT         Output height
  --steps INT              Sampling steps
  --cfg FLOAT              CFG scale
  --seed INT               Random seed

Advanced:
  --override JSON          Node input overrides
  --config PATH            YAML/JSON config file
  --server HOST:PORT       ComfyUI server
  --output-dir, -o PATH    Output directory
  --output-prefix TEXT     Output filename prefix
  --no-ensure              Skip auto-starting ComfyUI
  --no-validate            Skip input validation

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Troubleshooting

Problem	Fix
Workflow not found	Use --list to see available workflows
NO OUTPUTS generated	Run --inspect to check required inputs
Cannot reach ComfyUI	Ensure ComfyUI is running at configured host
Image file not found	Use absolute paths, verify with ls -la
GPU out of memory	Reduce resolution or steps

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Knowledge Cache Pattern

MODELS_INVENTORY.md and WORKFLOWS_SUMMARY.md serve as the agent's persistent knowledge base for the user's actual ComfyUI setup. Use them to cache learned information across sessions:

⚠️ DO NOT REFERENCE THE EXAMPLE CONTENT: The default content in these files describes sanitized example workflows that will NOT work. Agents MUST update them with the user's actual data before relying on them. Using outdated example data will cause workflow failures.

Initial Setup (First Time)

When the user first provides their own workflow files:

1. Clean the example content — Remove the sanitized example entries from both files
2. Populate with user's data — Run --inspect on each workflow, document findings in WORKFLOWS_SUMMARY.md
3. Inventory models — Scan user's model directories, update MODELS_INVENTORY.md with their actual models

Ongoing Maintenance

• After using a new workflow → Add its documentation to WORKFLOWS_SUMMARY.md
• After downloading models → Update MODELS_INVENTORY.md status
• When learning model-specific quirks → Document tips/tricks in the relevant section

Session Workflow

text

1. Read MODELS_INVENTORY.md → know available models
2. Read WORKFLOWS_SUMMARY.md → know workflow capabilities
3. Select appropriate workflow without re-inspecting
4. If new workflow discovered → document it for future sessions

This pattern lets the agent skip repeated discovery and work efficiently with cached knowledge.

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Reference Documents

Document	Purpose
MODELS_INVENTORY.md	Knowledge cache — user's installed models, status, paths
WORKFLOWS_SUMMARY.md	Knowledge cache — workflow capabilities, settings, tips
references/prompting-guide.md	Prompt anatomy, model-specific strategies
references/maintenance.md	Code structure, debugging
references/architecture.md	Design principles