Edit images on RunComfy — this skill is a smart router that matches the user's intent to the right edit model in the RunComfy catalog. Picks Nano Banana Edit (batch up to 20, identity-preserving default), OpenAI GPT Image 2 Edit (multilingual in-image text rewrite, multi-ref composition, layout prec

Image Edit — Pro Pack on RunComfy [runcomfy.com](https://www.runcomfy.com/?utm source=skills.sh&utm medium=skill&utm campaign=image edit) · [Nano Banana Edit](https://www.runcomfy.com/models/google/nano banana 2/edit?utm source=skills.sh&utm medium=skill&utm campaign=image edit) · [GPT Image 2 Edit](https://www.runcomfy.com/models/openai/gpt image 2/edit?utm source=skills.sh&utm medium=skill&utm campaign=image edit) · [Flux Kontext](https://www.runcomfy.com/models/blackforestlabs/flux 1 kontext pro/image to image?utm source=skills.sh&utm medium=skill&utm campaign=image edit) · [Z Image Inpaint](https://www.runcomfy.com/models/tongyi mai/z image/turbo/inpainting?utm source=skills.sh&utm medium=skill&utm campaign=image edit) · [GitHub](https://github.com/agentspace so/runcomfy skills/tree/main/image edit) 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. Pick the right model for the user's intent User intent Model Why Batch edit 1–20 images consistently (SKU gallery, A/B variants) Nano Banana Edit Up to 20 input images per call; locked aspect/resolution for series Swap background, preserve subject identity Nano Banana Edit Strong identity preservation under "keep X unchanged" prompts Localized object removal / addition with spatial language ("the left object", "upper right corner") Nano Banana Edit Honors directional spatial scope Multilingual / non Latin in image text rewrite (Japanese kana, Cyrillic, Arabic) GPT Image 2 Edit Strongest in class for multilingual typography Multi reference composition (subject from img1, scene from img2, palette from img3) GPT Image 2 Edit Numbered refs route cues correctly Layout precise repositioning ("move headline from top right to bottom center") GPT Image 2 Edit Directional language honored at layout level Identity preservation across translated headline variants GPT Image 2 Edit Same source asset → many language variants, identity stable Single shot precise local edit ("she's now holding an orange umbrella") Flux Kontext Pro Single ref single instruction, high fidelity preservation Mask driven object removal (cables, watermarks, distractions) Z Image Turbo Inpaint Mask required, strength tunable, edge consistent Mask driven region replacement (full background swap with mask) Z Image Turbo Inpaint High strength + clean mask = clean replacement Default if unspecified Nano Banana Edit Most flexible, supports both single and batch 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 Field Type Required Default Notes prompt string yes — Lead with preservation goals, end with the change. image urls array yes — 1–20 publicly fetchable HTTPS URLs. number of images int no 1 1–4 outputs per call. aspect ratio enum no auto auto follows input; lock for batch consistency. resolution enum no 1K 0.5K / 1K / 2K / 4K . output format enum no png png / jpeg / webp . seed int no — Reproducibility. enable web search bool no false Web grounded edits (extra latency). Invoke Batch (lock aspect + resolution): 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 Field Type Required Default Notes prompt string yes — Edit instruction; lead with preservation. images string[] yes — Up to 10 HTTPS URLs. First is primary; rest are auxiliary. size enum no auto auto , 1024 1024 , 1024 1536 , 1536 1024 . Only these. Invoke Multilingual text rewrite: Multi ref composition: 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) Field Type Required Notes prompt string yes One declarative edit instruction. image string yes Single source image URL. aspect ratio enum no Pick from supported W:H values. seed int no Reproducibility. Single image only — no array. For multi image flows, use Route 1 (Nano Banana Edit). Invoke 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 Field Type Required Notes prompt string yes What to fill / replace; preservation constraints for the unmasked surround. image string yes Source image URL. mask image string yes Grayscale mask URL (white = inpaint, black = preserve). strength float no 0.3–0.6 retouching, 0.7–1.0 full replacement. control scale float no 0.6–0.9 typical. aspect ratio enum no W:H output ratio. seed int no Reproducibility. Invoke Object removal (low strength): Region replacement (high strength): Prompting tips A mask URL is required — grayscale, white = inpaint region, black = preserve. Slight blur on mask edges (1–3px) blends better than sharp binary. Strength by intent : 0.3–0.5 for retouching / cleanup, 0.6–0.7 for object replacement with style match, 0.8–1.0 for full region replacement. Name what stays outside the mask in the prompt: "preserve rooflines and sky gradient" , "match brick pattern and mortar tone" . Spatial labels still help even though the mask defines the region: "the left shelf" , "upper right quadrant" . Limitations Each route inherits its model's limits. Nano Banana: 1–20 inputs, 1–4 outputs. GPT Image 2 Edit: up to 10 refs, 4 fixed sizes. Flux Kontext: single ref. Z Image Inpaint: mask required. No multi route blending. This skill picks one model per call. Brand specific overrides — if the user named a specific model, route to the corresponding brand skill ( gpt image edit , flux kontext , nano banana edit ) for fuller treatment. Exit codes code meaning 0 success 64 bad CLI args 65 bad input JSON / schema mismatch 69 upstream 5xx 75 retryable: timeout / 429 77 not signed in or token rejected Full reference: [docs.runcomfy.com/cli/troubleshooting](https://docs.runcomfy.com/cli/troubleshooting?utm source=skills.sh&utm medium=skill&utm campaign=image edit). How it works The skill picks one of Nano Banana Edit / GPT Image 2 Edit / Flux Kontext Pro / Z Image Turbo Inpaint based on user intent and invokes runcomfy run <model id with the matching JSON body. The CLI POSTs to the Model API, polls the request, fetches the result, and downloads any .runcomfy.net / .runcomfy.com URL into output dir . Ctrl C cancels the remote request before exit. Security & Privacy Token storage : runcomfy login writes the API token to ~/.config/runcomfy/token.json with mode 0600 (owner only read/write). Set RUNCOMFY TOKEN env var to bypass the file entirely in CI / containers. Input boundary : the user prompt is passed as a JSON string to the CLI via input . The CLI does NOT shell expand the prompt; it transmits the JSON body directly to the Model API over HTTPS. No shell injection surface from prompt content. Third party content : image / mask / video URLs you pass are fetched by the RunComfy model server, not by the CLI on your machine. Treat external URLs as untrusted; image based prompt injection is a known risk for any image edit / video edit model. Outbound endpoints : only model api.runcomfy.net (request submission) and .runcomfy.net / .runcomfy.com (download whitelist for generated outputs). No telemetry, no callbacks. Generated file size cap : the CLI aborts any single download 2 GiB to prevent disk fill from a malicious or runaway model output.

image-edit