image

name	image
description	AI image generation and editing. Text-to-image, style transfer, and logo generation. Powered by GPT Image 2 (via Codex CLI, no API key), Gemini, and FLUX. Triggers: generate image, create image, make image, draw, illustrate, logo, visual, picture.
allowed-tools	["Read","Write","Bash","AskUserQuestion","Agent","Glob"]

Image Generation — Babel Fish

Translating your thoughts into pictures. The Babel Fish handles all languages, including visual ones.

Boundaries

• MAY: generate images, save files, call image APIs
• MAY NOT: send images to external services or share outputs without explicit confirmation

Backends

Backend	When to Use	Key
GPT Image 2 via Codex CLI (gpt-image-2)	Default — strong prompt adherence, text in images, no API key	ChatGPT OAuth (codex login)
Gemini (gemini-3-pro-image-preview)	Style transfer with reference images, multi-turn iteration, 4K	GEMINI_API_KEY
FLUX via OpenRouter (black-forest-labs/flux.2-pro)	Artistic, stylised work	~/.claude/secrets/openrouter.json

Backend selection (ask first)

Before generating, ask via AskUserQuestion which backend to use — list the three above as options with GPT Image 2 first (default). Skip the question only when:

• The user already named a backend in their prompt ("use Gemini", "with FLUX", "via codex")
• The request forces a specific one:
  • Reference images for style matching → Gemini (the codex path does not accept reference images)
  • True native transparent background → Gemini, or codex with explicit gpt-image-1.5
  • 4K+ output above 3840px per edge → Gemini (codex caps at 3840)

Announce the chosen backend in one line before running so the user has clarity.

Requires: codex-cli >= 0.124.0-alpha.2 for GPT Image 2. Install: npm install -g @openai/codex@0.124.0-alpha.2.

Phase 0 — Understand

Gather before generating. Ask if unclear:

• Subject: what's in the image?
• Style: photorealistic, illustration, logo, watercolor, etc.
• Aspect ratio: 1:1 (default), 16:9, 9:16, 4:3, 3:2
• Resolution: 1K (default/fast), 2K (balanced), 4K (quality)
• Purpose: blog post, social media, UI asset, logo
• Output path: where to save (default: ./generated_image.jpg)

Phase 1 — Generate

GPT Image 2 via Codex (default)

Runs through codex's built-in image_gen tool — uses your ChatGPT OAuth, no API key, no per-image billing (counts against your ChatGPT plan limits).

plugins/babel-fish/skills/image/scripts/generate_image_codex.sh \
  --output ./output.png \
  --size 1024x1024 \
  --quality high \
  "your prompt here"

Constraints:

• Sizes: auto or WxH — max edge ≤ 3840px, edges multiples of 16, 655k–8.3M total pixels.
• Quality: low | medium | high | auto.
• Does not support background=transparent — use Gemini or ask codex for gpt-image-1.5 explicitly if true transparency is required.

Equivalent raw invocation (skip the wrapper for multi-variant riffs):

codex exec --skip-git-repo-check --sandbox workspace-write --full-auto \
  "Use your built-in image_gen tool to generate: <PROMPT>. After it returns, copy the file to <OUT_PATH> and print the path."

Gemini

import os
from google import genai
from google.genai import types

client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])

response = client.models.generate_content(
    model="gemini-3-pro-image-preview",
    contents=["Your refined prompt here"],
    config=types.GenerateContentConfig(
        response_modalities=["TEXT", "IMAGE"],
        image_config=types.ImageConfig(
            aspect_ratio="16:9",  # adjust per request
            image_size="1K",      # 1K | 2K | 4K
        ),
    ),
)

for part in response.parts:
    if part.text:
        print(part.text)
    elif part.inline_data:
        img = part.as_image()
        img.save("output.jpg")  # Gemini returns JPEG — always use .jpg

Critical: Gemini returns JPEG by default. Use .jpg extension. If PNG is needed, pass format="PNG" explicitly to img.save().

FLUX via OpenRouter

curl https://openrouter.ai/api/v1/images/generations \
  -H "Authorization: Bearer $(cat ~/.claude/secrets/openrouter.json | python3 -c 'import json,sys; print(json.load(sys.stdin)["api_key"])')" \
  -H "Content-Type: application/json" \
  -d '{"model": "black-forest-labs/flux.2-pro", "prompt": "your prompt", "n": 1}' \
  | python3 -c 'import json,sys,base64,urllib.request; d=json.load(sys.stdin); urllib.request.urlretrieve(d["data"][0]["url"], "output.png")'

Phase 2 — Review

Show the output path. Ask if it matches the intent and whether style, composition, or content needs adjusting.

Phase 3 — Iterate

If refinement is needed, use Gemini's multi-turn chat for continuity:

chat = client.chats.create(
    model="gemini-3-pro-image-preview",
    config=types.GenerateContentConfig(response_modalities=["TEXT", "IMAGE"])
)
response = chat.send_message("Create a logo for 'Acme'")
# save, then refine:
response = chat.send_message("Make the font bolder and add a blue gradient")

Adjust the prompt and regenerate until approved.

Phase 4 — Deliver

Save to the requested output path. Report:

• Final file path
• Model used
• Prompt that produced the result (for reproducibility)

Prompt Craft

• Specific beats vague: "a golden retriever in autumn leaves, warm light" not "a dog"
• Name the style: "watercolor illustration", "photorealistic", "flat vector logo"
• Specify light: "soft morning light", "dramatic shadows", "studio three-point lighting"
• Text in images: use Gemini Pro — put exact text in quotes, specify font style
• Logos: "clean sans-serif, black and white, [motif]" — Gemini handles this well