# Gpt Image Edit

> >

- **Type:** Skill
- **Install:** `agentstack add skill-agentspace-so-runcomfy-agent-skills-gpt-image-edit`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [agentspace-so](https://agentstack.voostack.com/s/agentspace-so)
- **Installs:** 0
- **Category:** [Content & Media](https://agentstack.voostack.com/c/content-and-media)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [agentspace-so](https://github.com/agentspace-so)
- **Source:** https://github.com/agentspace-so/runcomfy-agent-skills/tree/main/gpt-image-edit
- **Website:** https://www.runcomfy.com

## Install

```sh
agentstack add skill-agentspace-so-runcomfy-agent-skills-gpt-image-edit
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# GPT Image Edit — Pro Pack on RunComfy

[runcomfy.com](https://www.runcomfy.com/?utm_source=skills.sh&utm_medium=skill&utm_campaign=gpt-image-edit) · [Edit endpoint](https://www.runcomfy.com/models/openai/gpt-image-2/edit?utm_source=skills.sh&utm_medium=skill&utm_campaign=gpt-image-edit) · [Text-to-image sibling](https://www.runcomfy.com/models/openai/gpt-image-2/text-to-image?utm_source=skills.sh&utm_medium=skill&utm_campaign=gpt-image-edit) · [GitHub](https://github.com/agentspace-so/runcomfy-skills/tree/main/gpt-image-edit)

OpenAI **GPT Image 2 — `/edit` endpoint** (ChatGPT Images 2.0 image-to-image) on the **RunComfy Model API**. Strongest in its class at preserving identity through targeted edits and rewriting embedded text in any script (Latin, kana, CJK, Cyrillic, Arabic).

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

## When to pick this model (vs siblings)

| You want | Use |
|---|---|
| Edit multilingual / embedded text in image | **GPT Image Edit** |
| Identity preservation through translated headline variants | **GPT Image Edit** |
| Layout-precise edit (move headline, swap CTA, etc.) | **GPT Image Edit** |
| Up to 10 reference images | **GPT Image Edit** |
| Batch up to 20 images consistently | Nano Banana Edit |
| Single-shot precise local edit, source-fidelity-first | Flux Kontext |
| Generate from scratch with GPT Image 2 | sibling [`gpt-image-2`](../gpt-image-2) skill |
| Batch SKU galleries with stable identity | Nano Banana Edit |

## Prerequisites

1. **RunComfy CLI** — `npm i -g @runcomfy/cli`
2. **RunComfy account** — `runcomfy login` opens a browser device-code flow.
3. **CI / containers** — set `RUNCOMFY_TOKEN=` instead of `runcomfy login`.

## Endpoints + input schema

### `openai/gpt-image-2/edit`

| Field | Type | Required | Default | Notes |
|---|---|---|---|---|
| `prompt` | string | yes | — | Edit instruction. Lead with preservation, end with the change. |
| `images` | string[] | yes | — | **Up to 10** publicly-fetchable HTTPS URLs. First is primary; rest are auxiliary. |
| `size` | enum | no | `auto` | `auto` (preserve input), `1024_1024` (1:1), `1024_1536` (2:3 portrait), `1536_1024` (3:2 landscape). |

`size=auto` preserves the input ratio — strongly recommended unless the edit explicitly changes framing.

## How to invoke

**Single-ref preservation edit:**

```bash
runcomfy run openai/gpt-image-2/edit \
  --input '{
    "prompt": "Keep the person'\''s face, pose, and brand mark unchanged. Replace the background with a soft warm-grey studio sweep and a gentle floor shadow.",
    "images": ["https://.../portrait.jpg"]
  }' \
  --output-dir 
```

**Multilingual text rewrite (preserve everything except the headline):**

```bash
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 as before.",
    "images": ["https://.../poster-en.jpg"]
  }' \
  --output-dir 
```

**Multi-ref composition:**

```bash
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 (face, pose, clothing) unchanged.",
    "images": ["https://.../subject.jpg", "https://.../room.jpg"]
  }' \
  --output-dir 
```

## Prompting — what actually works

**Lead with preservation goals.** Always: `"Keep [face / pose / clothing / brand / framing] unchanged."` Then state the change. The model honors what's stated up front.

**Multilingual text — quote the characters, name the script.** `"the headline reads \"コーヒー\" in bold Japanese kana"`, `"the label says \"АРОМА\" in Cyrillic, white on black"`, `"the right-margin caption reads \"تخفيض\" in Arabic right-to-left"`. Don't paraphrase — quote.

**Directional language for spatial edits.** Concrete spatial scopes work: `"move the headline from top-right to bottom-center"`, `"remove the leftmost object only"`, `"replace the watermark in the bottom-right corner"`.

**Multi-ref numbering.** When passing multiple `images`, refer to them by number: `"subject from image 1, lighting from image 2, color palette from image 3"`. The model routes cues correctly.

**Use `size: "auto"` to preserve input ratio.** Only override when the edit explicitly changes framing (e.g. cropping a 16:9 to 1:1).

**Anti-patterns:**
- Long compound edit instructions ("change A and B and C and D") → drift increases per added scope.
- Missing preservation goals → model subtly rewrites the face / brand / framing.
- Paraphrasing in-image text instead of quoting it → text comes out different.
- Asking for `size` outside the 3 fixed values + `auto` → 422.

## Where it shines

| Use case | Why GPT Image Edit |
|---|---|
| **Multilingual ad localization** | One source asset → many language variants of the same headline |
| **Brand-safe headline / CTA swaps** | Layout precision + preservation language hold the rest stable |
| **Multi-ref composition (subject from one, scene from another)** | Numbered refs route cues correctly |
| **Layout-precise repositioning** | Directional language ("top-right to bottom-center") honored |
| **Identity preservation across signage edits** | Strongest in class for face / brand preservation through targeted edits |

## Sample prompts (verified to produce strong results)

**Background swap with full preservation (page example):**

```
Turn the background into a bright minimal white-to-soft-gray studio
sweep with gentle floor shadow; add a large headline in-image that
reads "OPEN STUDIO" in a bold clean sans-serif, high contrast, centered;
keep the main person or product, pose, and face identity unchanged
```

**Multilingual variant:**

```
Keep the photograph, layout, lighting, and brand mark exactly as in the
input. Replace only the in-image headline.
The new headline reads "コーヒー" in bold Japanese kana, same position
and font weight as before.
```

**Multi-ref composition:**

```
Compose subject from image 1 into the kitchen from image 2.
Match the warm window light and color palette of image 2.
Keep subject identity (face, pose, clothing) from image 1 unchanged.
```

## Limitations

- **`size`: 3 fixed values + `auto`** — anything else 422s.
- **`images`: up to 10** — first is primary, rest are auxiliary cues.
- **Long compound prompts drift** — split into multiple passes when needed.
- **For batch consistency across many SKU images, Nano Banana Edit (up to 20) is better.**
- **Photorealism on portraits** — Nano Banana Pro wins head-to-head.

## 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=gpt-image-edit).

## How it works

The skill invokes `runcomfy run openai/gpt-image-2/edit` with a JSON body matching the schema. The CLI POSTs to `https://model-api.runcomfy.net/v1/models/openai/gpt-image-2/edit`, 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.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [agentspace-so](https://github.com/agentspace-so)
- **Source:** [agentspace-so/runcomfy-agent-skills](https://github.com/agentspace-so/runcomfy-agent-skills)
- **License:** MIT
- **Homepage:** https://www.runcomfy.com

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-agentspace-so-runcomfy-agent-skills-gpt-image-edit
- Seller: https://agentstack.voostack.com/s/agentspace-so
- Browse the marketplace: https://agentstack.voostack.com/browse

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