Generate or edit artwork with built-in Codex image gen, especially transparent PNG ornaments, game sprites, emblems, and UI graphics. Use when the user requests
复制下面这句话,粘贴给 Claude Code、Codex、Cursor 等 AI 编程工具,它会读取安装说明并在你确认后完成安装。
请阅读 https://ai.atlankj.com/install/asset/gh-codex-gpt-image-2-5-flare-fdae55ef2c4a ,按照其中的说明把「codex-gpt-image-2-5-flare」安装到你(当前 AI 工具)中。执行前先告诉我将运行的命令和写入的位置,等我确认。
查看 AI 将读取的安装说明正在读取 GitHub 原文…
内容来自 GitHub 原始文件,由原作者维护。在 GitHub 查看
Use the built-in Codex image-generation tool for the artwork. “GPT 2.5 Flare” is this workflow's requested name, not proof of a selected model. The current built-in tool does not expose a model selector. State that limitation briefly when relevant; never invent a model argument or report an unverified model as fact.
Specify the asset's purpose, visual style, materials, silhouette, orientation, padding, transparent openings, and placement. Request dimensions or aspect ratio in the prompt when the tool has no dedicated parameter, then verify what it actually returns.
For an isolated transparent asset, include:
Create ONE isolated [asset] as a PNG with genuine alpha transparency. [Describe materials, colors, lighting, texture, and art direction.] Composition: [orientation, silhouette, padding, occupied area, and empty area]. Everything outside the object and every opening between its parts must be transparent. No painted checkerboard, solid backdrop, scene, floor, or rectangular shadow. Keep any glow confined to the artwork. No text, logo, watermark, or extra objects unless explicitly requested.
Adapt the constraints to the request; do not ban backgrounds, text, shadows, or glows when they are intentional.
Two useful compositions for ornate game UI:
Use the currently exposed image_gen.imagegen tool (available in functions orchestration as tools.image_gen__imagegen). Follow its live schema and media-return instructions. Do not substitute an image API, CLI, external provider, or hand-drawn SVG when the user requests built-in generation. If the built-in tool is unavailable, explain the blocker rather than silently switching providers.
view_image first and use referenced_image_paths.num_last_images_to_include only when needed for a target without a local path, choosing the smallest number that includes all targets. Never send both reference mechanisms.model, size, or output-path arguments. Do not infer the actual model from the skill name or prompt.Current functions-mode example for a new image:
// @exec: {"yield_time_ms": 120000, "max_output_tokens": 1500}
const result = await tools.image_gen__imagegen({ prompt: "Your complete asset prompt" });
generatedImage(result);
Inspect the generated image visually. Check silhouette, clipping, negative space, material quality, unwanted text, and fidelity to references. RGBA mode alone does not prove transparency: the alpha channel could still be fully opaque.
Run the bundled read-only helper using the absolute path of this skill's script and the returned image paths:
python3 /path/to/codex-gpt-image-2-5-flare/scripts/inspect_png.py --require-transparency /path/to/generated.png
The helper requires Pillow and reports actual format, mode, dimensions, byte count, SHA-256, alpha range, transparent/partial/opaque pixel percentages, and visible bounds. It rejects non-PNG files; --require-transparency also rejects fully opaque or entirely invisible images. It never edits or converts pixels.
These measurements do not prove the intended holes are transparent. Inspect the artwork against the consuming background or a checkerboard preview, especially enclosed gaps. If transparency or composition is wrong, use a built-in image edit with the original as a reference. Do not silently chroma-key a flat background, paint over it, or substitute a vector asset.
object-fit: contain where appropriate. Mirrored corner elements can share one texture.Show the native generated image or a verified integrated preview. Link the usable PNG files and saved prompts, state any material limitation, and report validation and commit results when applicable. Do not claim a requested size, transparency, integration, or model selection without checking it.