Image Edit

Image Edit — Pro Pack on RunComfy

runcomfy.com · Nano Banana Edit · GPT Image 2 Edit · Flux Kontext · Z-Image Inpaint · GitHub

Image edit, intent-routed. This skill doesn't lock you to one model — it picks the right edit model in the RunComfy catalog based on what the user actually wants: batch identity-preservation, multilingual text rewrite, single-shot precise edit, or mask-driven region replacement.

npx skills add agentspace-so/runcomfy-skills --skill image-edit -g

Pick the right model for the user's intent

The agent reads this table, classifies the user's intent, and picks the matching subsection below.

Prerequisites

1. RunComfy CLI — npm i -g @runcomfy/cli
2. RunComfy account — runcomfy login.
3. CI / containers — set RUNCOMFY_TOKEN=<token>.

Route 1: Nano Banana Edit — default for general edit + batch

Model: google/nano-banana-2/edit

Schema

Invoke

runcomfy run google/nano-banana-2/edit \
  --input '{
    "prompt": "Keep the subject identity, pose, and clothing unchanged. Convert the background into a rainy neon cyberpunk street.",
    "image_urls": ["https://.../portrait.jpg"]
  }' \
  --output-dir <absolute/path>

Batch (lock aspect + resolution):

runcomfy run google/nano-banana-2/edit \
  --input '{
    "prompt": "Replace the watermark in the bottom-right with the text \"AURA\" in clean white sans-serif. Keep everything else exactly as in the input.",
    "image_urls": ["https://.../sku-1.jpg", "https://.../sku-2.jpg", "https://.../sku-3.jpg"],
    "aspect_ratio": "1:1",
    "resolution": "1K"
  }' \
  --output-dir <absolute/path>

Prompting tips

• Preservation first: "Keep [identity / pose / brand / framing] unchanged." Then state the change.
• Spatial scope: "background only", "the left object", "upper-right quadrant" — concrete locations honored.
• Batch consistency: lock aspect_ratio and resolution across the batch.
• Iterate small: split compound edits into multiple shorter passes.

Route 2: GPT Image 2 Edit — multilingual text + multi-ref composition

Model: openai/gpt-image-2/edit

Schema

Invoke

Multilingual text rewrite:

runcomfy run openai/gpt-image-2/edit \
  --input '{
    "prompt": "Keep the photograph, layout, and brand mark exactly as in the input. Replace only the in-image headline. The new headline reads \"今日のおすすめ\" in bold Japanese kana, same position and font weight.",
    "images": ["https://.../poster-en.jpg"]
  }' \
  --output-dir <absolute/path>

Multi-ref composition:

runcomfy run openai/gpt-image-2/edit \
  --input '{
    "prompt": "Compose subject from image 1 into the room from image 2. Match the lighting and color palette of image 2. Keep image 1 subject identity unchanged.",
    "images": ["https://.../subject.jpg", "https://.../room.jpg"]
  }' \
  --output-dir <absolute/path>

Prompting tips

• Quote in-image text exactly. Name the script for non-Latin: "Japanese kana", "Cyrillic", "Arabic right-to-left".
• Number multi-refs: "subject from image 1, lighting from image 2".
• Directional layout language: "move the headline from top-right to bottom-center", "replace the watermark in the bottom-right".
• `size: "auto"` preserves input ratio — recommended unless the edit changes framing.

Route 3: Flux Kontext Pro — single-shot precise local edit

Model: blackforestlabs/flux-1-kontext/pro/edit

Schema (minimal)

Single image only — no array. For multi-image flows, use Route 1 (Nano Banana Edit).

Invoke

runcomfy run blackforestlabs/flux-1-kontext/pro/edit \
  --input '{
    "prompt": "Keep the person'\''s face, pose, and clothing unchanged. Add an orange umbrella in her left hand and a slight smile.",
    "image": "https://.../portrait.jpg"
  }' \
  --output-dir <absolute/path>

Prompting tips

• One declarative instruction. "She is now holding an orange umbrella and smiling" — imperative, single change.
• Preservation first. Lead with "Keep [unchanged elements]" then state the change.
• Iterate small. Compound edits drift on a single pass; split into sequential passes.

Route 4: Z-Image Turbo Inpaint — mask-driven precise region edit

Model: tongyi-mai/z-image/turbo/inpainting

Schema