comfyui-workflow-builder

mckruz/comfyui-expert · updated May 5, 2026

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$npx skills add https://github.com/mckruz/comfyui-expert --skill comfyui-workflow-builder
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summary

Translates natural language requests into executable ComfyUI workflow JSON. Always validates against inventory before generating.

skill.md

ComfyUI Workflow Builder

Translates natural language requests into executable ComfyUI workflow JSON. Always validates against inventory before generating.

Workflow Generation Process

Step 1: Understand the Request

Parse the user's intent into:

  • Output type: Image, video, or audio
  • Source material: Text-only, reference image(s), existing video
  • Identity method: None, zero-shot (InstantID/PuLID), LoRA, Kontext
  • Quality level: Draft (fast iteration) vs production (maximum quality)
  • Special requirements: ControlNet, inpainting, upscaling, lip-sync

Step 2: Check Inventory

Read state/inventory.json to determine:

  • Available checkpoints → select best match for task
  • Available identity models → determine which methods are possible
  • Available ControlNet models → enable pose/depth control if available
  • Custom nodes installed → verify all required nodes exist
  • VRAM available → optimize settings accordingly

Step 3: Select Pipeline Pattern

Based on request + inventory, choose from:

Pattern When Key Nodes
Text-to-Image Simple generation Checkpoint → CLIP → KSampler → VAE
Identity-Preserved Image Character consistency + InstantID/PuLID/IP-Adapter
LoRA Character Trained character + LoRA Loader
Image-to-Video (Wan) High-quality video Diffusion Model → Wan I2V → Video Combine
Image-to-Video (AnimateDiff) Fast video, motion control + AnimateDiff Loader + Motion LoRAs
Talking Head Character speaks Image → Video → Voice → Lip-Sync
Upscale Enhance resolution Image → UltimateSDUpscale → Save
Inpainting Edit regions Image + Mask → Inpaint Model → KSampler

Step 4: Generate Workflow JSON

ComfyUI workflow format:

{
  "{node_id}": {
    "class_type": "{NodeClassName}",
    "inputs": {
      "{param_name}": "{value}",
      "{connected_param}": ["{source_node_id}", {output_index}]
    }
  }
}

Rules:

  • Node IDs are strings (typically "1", "2", "3"...)
  • Connected inputs use array format: ["source_node_id", output_index]
  • Output index is 0-based integer
  • Filenames must match exactly what's in inventory
  • Seed values: use random large integer or fixed for reproducibility

Step 5: Validate

Before presenting to user:

  1. Every class_type exists in inventory's node list
  2. Every model filename exists in inventory's model list
  3. All required connections are present (no dangling inputs)
  4. VRAM estimate doesn't exceed available VRAM
  5. Resolution is compatible with chosen model (512 for SD1.5, 1024 for SDXL/FLUX)

Step 6: Output

If online mode: Queue via comfyui-api skill If offline mode: Save JSON to projects/{project}/workflows/ with descriptive name

Workflow Templates

Basic Text-to-Image (FLUX)

{
  "1": {
    "class_type": "LoadCheckpoint",
    "inputs": {"ckpt_name": "flux1-dev.safetensors"}
  },
  "2": {
    "class_type": "CLIPTextEncode",
    "inputs": {"text": "{positive_prompt}", "clip": ["1", 1]}
  },
  "3": {
    "class_type": "CLIPTextEncode",
    "inputs": {"text": "{negative_prompt}", "clip": ["1", 1]}
  },
  "4": {
    "class_type": "EmptyLatentImage",
    "inputs": {"width": 1024, "height": 1024, "batch_size": 1}
  },
  "5": {
    "class_type": "KSampler",
    "inputs": {
      "seed": 42,
      "steps": 25,
      "cfg": 3.5,
      "sampler_name": "euler",
      "scheduler": "normal",
      "denoise": 1.0,
      "model": ["1", 0],
      "positive": ["2", 0],
      "negative": ["3", 0],
      "latent_image": ["4", 0]
    }
  },
  "6": {
    "class_type": "VAEDecode",
    "inputs": {"samples": ["5", 0], "vae": ["1", 2]}
  },
  "7": {
    "class_type": "SaveImage",
    "inputs": {"filename_prefix": "output", "images": ["6", 0]}
  }
}

With Identity Preservation (InstantID + IP-Adapter)

Extends basic template by adding:

  • Load reference image node
  • InstantID Model Loader + Apply InstantID
  • IPAdapter Unified Loader + Apply IPAdapter
  • FaceDetailer post-processing

See references/workflows.md for complete node settings.

Video Generation (Wan I2V)

Uses different loader chain:

  • Load Diffusion Model (not LoadCheckpoint)
  • Wan I2V Conditioning
  • EmptySD3LatentImage (with frame count)
  • Video Combine (VHS)

See references/workflows.md Workflow 4 for complete settings.

VRAM Estimation

Component Approximate VRAM
FLUX FP16 16GB
FLUX FP8 8GB
SDXL 6GB
SD1.5 4GB
InstantID +4GB
IP-Adapter +2GB
ControlNet (each) +1.5GB
Wan 14B 20GB
Wan 1.3B 5GB
AnimateDiff +3GB
FaceDetailer +2GB

Common Mistakes to Avoid

  1. Wrong output index: CheckpointLoader outputs [model, clip, vae] at indices [0, 1, 2]
  2. CFG too high for InstantID: Use 4-5, not default 7-8
  3. Wrong resolution for model: FLUX/SDXL=1024, SD1.5=512
  4. Missing VAE: FLUX needs explicit VAE (ae.safetensors)
  5. Wrong model in wrong loader: Diffusion models need LoadDiffusionModel, not LoadCheckpoint

Reference Files

  • references/workflows.md - Detailed node-by-node templates
  • references/models.md - Model files and paths
  • references/prompt-templates.md - Model-specific prompts
  • state/inventory.json - Current inventory cache
how to use comfyui-workflow-builder

How to use comfyui-workflow-builder on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add comfyui-workflow-builder
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/mckruz/comfyui-expert --skill comfyui-workflow-builder

The skills CLI fetches comfyui-workflow-builder from GitHub repository mckruz/comfyui-expert and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/comfyui-workflow-builder

Reload or restart Cursor to activate comfyui-workflow-builder. Access the skill through slash commands (e.g., /comfyui-workflow-builder) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.569 reviews
  • Luis Shah· Dec 24, 2024

    comfyui-workflow-builder is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Carlos Johnson· Dec 20, 2024

    Keeps context tight: comfyui-workflow-builder is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kofi Jackson· Dec 20, 2024

    We added comfyui-workflow-builder from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Yuki Gill· Dec 20, 2024

    Keeps context tight: comfyui-workflow-builder is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Chaitanya Patil· Dec 16, 2024

    Keeps context tight: comfyui-workflow-builder is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Jin Gupta· Nov 15, 2024

    Solid pick for teams standardizing on skills: comfyui-workflow-builder is focused, and the summary matches what you get after install.

  • Dev Martin· Nov 11, 2024

    comfyui-workflow-builder has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Kofi Kim· Nov 11, 2024

    comfyui-workflow-builder has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Piyush G· Nov 7, 2024

    comfyui-workflow-builder has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Oct 26, 2024

    Solid pick for teams standardizing on skills: comfyui-workflow-builder is focused, and the summary matches what you get after install.

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