Generate images with GPT Image 2 (ChatGPT Images 2.0) inside Claude Code, using your existing ChatGPT Plus or Pro subscription — no separate OpenAI access, no per-image billing. Supports text-to-image, image-to-image editing, style transfer, and multi-reference composition via the local Codex CLI. T

🪞 GPT Image 2 — Image Generation via Your ChatGPT Subscription [agentspace.so](https://agentspace.so/?utm source=skills.sh&utm medium=skill&utm campaign=gpt image 2) · [GitHub](https://github.com/agentspace so/agent skills/tree/main/gpt image 2) Generate images with GPT Image 2 (ChatGPT Images 2.0) inside your agent, using your existing ChatGPT Plus or Pro subscription — no separate OpenAI access, no Fal or Replicate tokens, no per image billing. Text to image, image to image editing, style transfer, and multi reference composition. Runs entirely through the local codex CLI you're already logged into. Heads up — this skill requires a ChatGPT Plus or Pro subscription plus the Codex CLI installed locally. If you have neither, you can use GPT Image 2 in the browser via RunComfy instead — hosted, no ChatGPT subscription or local install needed (RunComfy account required): Text to image: [runcomfy.com/models/openai/gpt image 2/text to image](https://www.runcomfy.com/models/openai/gpt image 2/text to image) Image edit (i2i): [runcomfy.com/models/openai/gpt image 2/edit](https://www.runcomfy.com/models/openai/gpt image 2/edit) The rest of this document covers the local Codex CLI flow for agents whose user has a ChatGPT subscription. ![GPT Image 2 example — flat color lobster repainted as a 1950s ukiyo e woodblock print](https://raw.githubusercontent.com/agentspace so/agent skills/main/gpt image 2/gallery/d ukiyoe.png) Example output: a plain flat color icon repainted via ref in ukiyo e style — composition preserved, rendering swapped, period appropriate red seal added by the model unprompted. When to trigger Trigger when the user explicitly asks for GPT Image 2 via their ChatGPT subscription, for example: "use GPT Image 2" / "use gpt image 2" / "use ChatGPT Images 2.0" "use Image 2" / "image 2 this" attached a reference image and asked to remix / edit / restyle it Do not auto trigger for a plain "generate an image" request if the user didn't specify this route. If they did specify it, do not silently fall back to HTML mockups, screenshots, or a different image model. How to invoke A single bash script handles everything: runs codex exec with the right flags, then decodes the generated image from the persisted session rollout. Text to image: Image to image (reference flag is repeatable for multi reference composition): Optional: timeout sec 300 (default 300). Default behavior Pass the user's prompt through raw. Do not translate, polish, or add style modifiers unless the user asked for it. Choose the output path. Default to ./image <YYYYMMDD HHMMSS .png in the current working directory if the user didn't specify. Deliver the image. After the script succeeds, display / attach the output file. Do not stop at "done, see path X". Text heavy layouts are fine. Image 2 handles infographics and timeline prompts well. Do not preemptively warn just because a prompt has a lot of text. Hard constraints Do not switch routes without permission. If the user said "use GPT Image 2", do not substitute DALL·E, Midjourney, an HTML mockup, or a manual screenshot workflow. Do not rewrite the prompt unless asked. Do not imply this skill works without a local codex login and a valid ChatGPT subscription with image generation entitlement. Prerequisites 1. codex CLI installed — brew install codex or see [openai/codex](https://github.com/openai/codex). 2. Logged in with a ChatGPT plan that includes Image 2 — codex login . 3. python3 on PATH (ships with macOS; apt install python3 on Linux). This skill does not grant image generation capability on its own. It exposes the capability the user already has through their ChatGPT subscription. Exit codes code meaning 0 success — output path printed on stdout 2 bad args 3 codex or python3 CLI missing 4 ref file does not exist 5 codex exec failed (auth? network? model?) 6 no new session file detected 7 imagegen did not produce an image payload (feature not enabled, quota, or capability refused) On failure, name the layer in one sentence instead of dumping the full stderr at the user. How it works The codex CLI reuses the logged in ChatGPT session and exposes an imagegen tool (gated behind the image generation feature flag). The script: 1. snapshots ~/.codex/sessions/ before the run 2. runs codex exec enable image generation sandbox read only ... (with i <file for each reference image) 3. diffs the sessions directory, then invokes scripts/extract image.py to scan every new rollout JSONL for a base64 image payload (PNG / JPEG / WebP magic header match) 4. decodes the largest matching blob and writes it to out Two non obvious flags other wrappers get wrong on codex cli 0.111.0+: enable image generation is required ; the feature is still under development and off by default. ephemeral must not be used — ephemeral sessions aren't persisted, so the image payload has nowhere to live. Data handling The script is narrowly scoped on purpose: It reads only session rollout files created by its own codex exec invocation. The sessions directory is snapshotted before the call and diffed after, so any prior ~/.codex/sessions/ files (which may contain unrelated Codex conversations) are never touched, read, or transmitted. It writes only two kinds of file: the output PNG at the caller's out path, and short lived mktemp logs that are auto deleted on exit via a trap. No environment variables are read. No credentials are requested. No other paths under ~/.codex/ are accessed. No network calls leave this skill. The only outbound traffic is the one made by the codex CLI itself (to OpenAI, using the user's existing ChatGPT login) — this skill does not add endpoints, telemetry, or callbacks. What this skill is not Not a direct OpenAI API client. Not a capability grant — it depends on the user's working Codex CLI login. Not a multi tenant service (one call per invocation; concurrent calls are serialized by the filesystem snapshot diff).

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