Agent skill

Gpt Image 2 Skill

by Wangnov in Wangnov/gpt-image-2-skill

This skill should be used when the user asks to "generate an image", "create a logo", "draw an icon", "edit this photo", "change background to transparent", "remove background", "use GPT image"…

MITAuto-check passedMedia & Creative

Install Gpt Image 2 Skill

skills CLI
$ npx skills add Wangnov/gpt-image-2-skill --skill gpt-image-2-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Wangnov/gpt-image-2-skill gpt-image-2-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Wangnov/gpt-image-2-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/gpt-image-2-skill .claude/skills/gpt-image-2-skill && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
gpt-image-2-skill
GitHub stars
142
Token cost
~4.5k tokens
SKILL.md length
1,549 words
Files
15 (incl. scripts, references)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

This skill should be used when the user asks to "generate an image", "create a logo", "draw an icon", "edit this photo", "change background to transparent", "remove background", "use GPT image"…

  • Asks to generate an image
  • SKILL.md covers When to use this skill, Quick start, 本地 Codex 生图(2026-09-09 更新) and Image 2.5 与运行时能力边界, plus 8 more sections
  • Runs JavaScript scripts from its folder; calls node, npm and cargo; needs OPENAI_API_KEY
  • Edit this photo

What it does

Gpt Image 2 Skill is an agent skill from Wangnov/gpt-image-2-skill. This skill should be used when the user asks to "generate an image", "create a logo", "draw an icon", "edit this photo", "change background to transparent", "remove background", "use GPT image", "use Codex to draw", "用 GPT image 生成图片", "用 Codex 画图", "帮我生成一张图", "改成透明背景", "把这张图编辑一下", or any prompt-to-image or reference-image-edit task that benefits from a structured CLI returning JSON results and JSONL progress events. Supports OpenAI GPT Image models (via OPENAIAPIKEY or OpenAI-compatible base URL) and Codex…

Its SKILL.md is about 4.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 18 other files, including scripts and reference files (for example `agents/openai.yaml`, `evals/README.md` and `evals/evals.json`).

It sits in Media & Creative, covering Image generation. It works with OpenAI and Tauri. The repository describes itself as: GPT Image 2 Skill / CLI / Web / Desktop. The licence is MIT.

When your agent uses it

  • Asks to generate an image
  • Edit this photo
  • Change background to transparent
  • Remove background

Example prompts

  • “generate an image”
  • “create a logo”
  • “draw an icon”
  • “/gpt-image-2-skill”

Requirements

  • Node.js
  • A credential in OPENAI_API_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit 16fcc05. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (JavaScript), which the agent can run.

    Shell commands in SKILL.md call:

    • node
    • npm
    • cargo

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • developers.openai.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • OPENAI_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Gpt Image 2 Skill loads about 4.5k tokens when it runs, and up to ~18k if it reads all its reference files. Until then it costs about 187 tokens; SKILL.md has 1,549 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~187
When it runs · the whole SKILL.md, loaded when a task matches
~4.5k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~18k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Wangnov/gpt-image-2-skill at commit 16fcc05, republished under its MIT licence (© Wangnov). 1,549 words, ~4,487 tokens.

Download SKILL.mdSave it as .claude/skills/gpt-image-2-skill/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.
name
gpt-image-2-skill
description
This skill should be used when the user asks to "generate an image", "create a logo", "draw an icon", "edit this photo", "change background to transparent", "remove background", "use GPT image", "use Codex to draw", "用 GPT image 生成图片", "用 Codex 画图", "帮我生成一张图", "改成透明背景", "把这张图编辑一下", or any prompt-to-image or reference-image-edit task that benefits from a structured CLI returning JSON results and JSONL progress events. Supports OpenAI GPT Image models (via `OPENAI_API_KEY` or OpenAI-compatible base URL) and Codex `image_generation` (via `~/.codex/auth.json`, with an explicit supported orchestration model) under one command surface, with masks, custom sizes up to 4K, transparent backgrounds, and a raw request escape hatch.

Run image generation and editing through one CLI surface that hides provider differences. The Node wrapper at scripts/gpt_image_2_skill.cjs resolves an underlying Rust binary (env override → bundled Skill binary → installed binary → Tauri App bundled CLI → repo cargo run → cached release → bootstrap download) and forwards every flag. On glibc Linux, release bootstrap tries the GNU archive first and then the static musl archive as the sandbox fallback.

When to use this skill

  • Generate or edit an image and capture a structured result an agent can parse.
  • Switch between OPENAI_API_KEY, an OpenAI-compatible base URL, and Codex auth.json without changing command shape.
  • Respect shared provider config at $CODEX_HOME/gpt-image-2-skill/config.json so CLI, App, and Skill use the same default provider.
  • Need final transparent PNG deliverables, masks, custom sizes up to 4K, or raw request bodies.
  • Want live progress events (retries, multipart prep, Codex SSE) on stderr while the final JSON lands on stdout.

Quick start

Always pass --json so the result is machine-readable. Add --json-events when progress visibility matters.

bash
# 1. Confirm runtime + provider readiness
node scripts/gpt_image_2_skill.cjs --json config inspect
node scripts/gpt_image_2_skill.cjs --json doctor
node scripts/gpt_image_2_skill.cjs --json auth inspect

# 2. Generate a final transparent PNG deliverable
node scripts/gpt_image_2_skill.cjs --json --json-events \
  transparent generate --prompt "..." --out /tmp/asset.png \
  --size 2K --quality high

# 3. Generate a normal image (auto-selects provider; OpenAI first, then Codex)
node scripts/gpt_image_2_skill.cjs --json --json-events \
  images generate --prompt "..." --out /tmp/out.png \
  --format png --size 2K

# 4. Edit a reference image (OpenAI multipart)
node scripts/gpt_image_2_skill.cjs --json --json-events \
  images edit --prompt "..." --ref-image /tmp/in.png --out /tmp/out.png

# 5. Remove a controlled background from existing source images
node scripts/gpt_image_2_skill.cjs --json \
  transparent extract --input /tmp/source-green.png --out /tmp/asset.png \
  --method chroma --matte-color auto --strict

# 6. Verify the final file before delivery
node scripts/gpt_image_2_skill.cjs --json \
  transparent verify --input /tmp/asset.png --profile icon --strict

# 7. Raw request escape hatch
node scripts/gpt_image_2_skill.cjs --json \
  request create --request-operation generate \
  --body-file /tmp/body.json --out-image /tmp/out.png --expect-image

# 8. Self-test (calls doctor + auth inspect)
node scripts/selftest.cjs

Force a provider with --provider openai, --provider codex, or any named provider from config inspect; leave the default --provider auto to use default_provider first. Override the legacy OpenAI base URL with --openai-api-base https://....

本地 Codex 生图(2026-09-09 更新)

以下 CLI 示例走 Responses 路径。复现最新 Codex App 时,应区分宿主原生 image_gen.imagegen 的独立 Images 路径;见 references/codex-native-imagegen.md。原生工具成功不代表 CLI 已适配,服务端别名也不能证明实际权重版本。

用户指定 Codex 时,必须显式传 --provider codex,避免共享配置将请求路由到 OpenAI-compatible 服务。下面的命令从 Skill 目录执行,使用本地 Codex 登录,不需要 OpenAI API key:

bash
node scripts/gpt_image_2_skill.cjs --json --provider codex doctor
mkdir -p output
node scripts/gpt_image_2_skill.cjs --json --json-events --provider codex \
  images generate --model gpt-6-astra \
  --prompt "一只橙色纸雕小狐狸坐在蓝绿色月牙上,深蓝背景" \
  --out output/codex-fox.png --format png --size 1024x1024 \
  > output/result.json 2> output/events.jsonl
  • 当前 CLI 的 Codex 默认值仍是 gpt-5.4;本地实测已被 ChatGPT 账户后端拒绝。示例显式使用本次验证的 gpt-6-astra,其他账户仍需核对可用模型。
  • --model 是外层调用工具的模型,不能填 gpt-image-2.5-flare 或 gpt-image-2.5-sunburst。这两个是图像模型 ID。
  • 普通命令未指定 tools[].model,由 Codex 服务端选择绘图模型。读取 类型为 response.created 的 SSE 日志中 data.response.tools[].model;不要将 CLI 摘要的 delegated_image_model 当作实测结果,该字段在当前版本仍硬编码为 gpt-image-2。
  • 只有最终 JSON 的 ok: true、图片文件真实存在且经过视觉检查,才能报告生图成功。请求被接受或进入 generating 不能视为完成。
  • HTTP 400 的模型不支持错误应修正模型;不要改用其他 provider。遇到额度、权限或认证错误时报告原因,不自动切到付费 API。
  • 对照发现:size 参数本身未保证执行;把尺寸和比例写入提示词曾准确得到1536×1024,冲突时跟随提示词,但4K提示词仍未得到4K。不要按请求值报告实际尺寸。
  • 参数并非全无效:output_format确实决定PNG/JPEG;background=opaque压过透明提示词,生成了RGB棋盘格假透明。透明候选应使用auto,并检查真实alpha;quality不能靠提示词保证。
  • 关于显式 2.5 请求、服务端返回模型和透明背景限制,见 references/codex-local-verification.md。

Image 2.5 与运行时能力边界

OpenAI 官方已列出 gpt-image-2.5-flare 和 gpt-image-2.5-sunburst,可在 OpenAI Image API 中使用 --model 显式选择;这不代表 Codex 订阅后端已支持相同模型选择。保留用户指定的模型和共享配置。

2.5 的公共 API 支持 xhigh / max 质量和原生透明 PNG/WebP,当前 Rust CLI 与桌面生成界面已支持 low|medium|high|xhigh|max|auto;xhigh/max 仅用于支持它们的 API 模型,不能保证 Codex 订阅后端支持。Codex 的原始请求操作必须是 responses,不能用 generate。

官方依据:Flare、Sunburst、图像生成指南。

防止静默降级与中文质量验收

  • 用户要求Image 2或2.5时,不得为了透明、速度或失败重试自行改用1.5,也不得切换provider掩盖失败。
  • 区分请求模型、服务端报告模型、实际权重版本。Codex只返回别名或没有版本字段时,将实际版本标为unknown;不能保证未发生后端回退,也不能仅凭中文表现或透明alpha推断版本。
  • 复杂中文须核对原文:常规长句、金额、近形字、生僻字和标点分别检查。2026-09-09新增4张对照中,两条路径均能生成清晰常规中文和真实透明,但均未正确保持“戊戌戍”等辨字及全部生僻字,不能宣称全文准确。
  • 最新官方提示词指南已将Image 2透明列为preview,2.5两款均支持透明;“真透明意味着1.5”已不是有效判据。公开API支持不代表Codex订阅路径相同参数必然成功。
  • 模型身份不可验证时,不把质量测试包装成身份认证。此处是Skill执行要求,不是已实现的服务端版本锁定功能。

Runtime freshness check

Before using newly documented command groups, especially transparent generate, transparent extract, or transparent verify, confirm the actual CLI runtime is fresh enough. Skill files, the Tauri App bundle, npm global CLI, cargo-installed CLI, and wrapper cache can drift independently.

Start by checking the latest upstream CLI version:

bash
npm view gpt-image-2-skill version

Then look for the Tauri App bundled CLI first. Treat the app bundle as user-managed software: if it exists but is older than upstream, ask the user before updating or replacing the app.

bash
APP_CLI="/Applications/GPT Image 2.app/Contents/Resources/bin/gpt-image-2-skill"
[ -x "$APP_CLI" ] && "$APP_CLI" --version

If no app bundle CLI exists, check the shell CLI. If it is missing or older than upstream, silently update the CLI dependency with npm, then verify that the current shell resolves the new binary:

bash
command -v gpt-image-2-skill || true
gpt-image-2-skill --version || true
npm install -g gpt-image-2-skill@latest
command -v gpt-image-2-skill
gpt-image-2-skill --version

After any update, run the skill wrapper smoke checks:

bash
node scripts/gpt_image_2_skill.cjs --json doctor
node scripts/selftest.cjs

If a documented subcommand fails with unrecognized subcommand, diagnose stale runtime first rather than changing prompts or providers. Prefer the wrapper in this skill directory for reproducible skill execution, but keep the bare CLI fresh when examples or user commands call gpt-image-2-skill directly.

Shared config

Use the CLI config surface when the user asks to add or pin a provider:

bash
node scripts/gpt_image_2_skill.cjs --json config path
node scripts/gpt_image_2_skill.cjs --json config add-provider \
  --name my-image-api \
  --type openai-compatible \
  --api-base https://example.com/v1 \
  --api-key sk-... \
  --set-default
node scripts/gpt_image_2_skill.cjs --json config test-provider my-image-api

Credential sources supported by CLI, App, and Skill: file, env, and keychain. File credentials are stored in the shared config file; JSON output redacts them.

Flags vs prompt — what each controls

输出属性优先通过接口参数表达,但 Codex 后端可能归一化或忽略参数。提示词可表达期望,最终必须读取实际返回值并检查图片;不要将任何单一参数或提示词视为执行保证。

PropertyCLI flag
Output background (transparent / opaque / auto)--background auto|transparent|opaque
Output dimensions--size 2K, --size 4K, or --size WIDTHxHEIGHT
Output container--format png|jpeg|webp
Compression level--compression 0..100
Render quality--quality low|medium|high|auto
Number of images--n <count> (OpenAI only)
Edit mask region--mask <png> (OpenAI only)

提示词用于内容与视觉意图;--background opaque 只表达不透明,不指定白色。白背景还需在提示词中明确。对于 Codex,透明提示词配合 background=auto 可能得到真实 alpha,而显式透明参数当前可能报错;以实测和文件检查为准。

Provider asymmetry: --n, --moderation, --mask 和 --input-fidelity 在 Codex 普通命令中返回 unsupported_option。--background 会写入 Codex 请求,但不能据此保证上游执行;本次原始透明背景请求被后端拒绝。公共 Image API 与 Codex 后端的能力必须分别验证。

Transparent PNG deliverables

Codex 的显式 background=transparent 在本地对照中被拒绝,但 background=auto 配合透明提示词曾成功生成真实 RGBA。可以将后者作为候选路径,必须验证 alpha 和严格交付指标;本次样本因全透明区域残留 RGB 未通过严格验收。已合格的原生透明图无需再次抠图。需要本地处理时使用下列流程;OpenAI 2.5 公共 API 的原生透明输出也需同样验收:

  • transparent generate — prompt-to-final PNG. It generates a controlled matte source, extracts alpha locally, verifies the result, and only succeeds when the final PNG passes transparency checks.
  • transparent extract — local background removal from controlled source images you generated yourself. It is not a general-purpose background remover for arbitrary photos.
  • transparent verify — final gate for any PNG before delivery. Use --strict and the right --profile when the file must be accepted or fail the task.

A transparent deliverable is valid only if the final file has a real PNG alpha channel and passes verification. A visual appearance of transparency, a white background, or a checkerboard pattern is not sufficient.

--strict is profile-based:

ProfileUse forExtra strictness
genericcommon alpha/file checksdoes not over-police unusual assets
iconclean single-subject icons and propsrequires clean opaque core, margin, low stray noise
productproduct/object cutoutssimilar to icon, with residue and edge checks
stickerdecals, badges, multi-detail propsallows more intentional small components than icon
sealstamps, seals, logos with inner marksallows split components such as ring + center symbol
translucentglass, liquid, crystalrequires partial alpha
glowlight ribbons, flame, smoke, particlesrequires partial alpha and transparent margin
shadowsoft shadow assetsrequires partial alpha and transparent margin
effecthard-alpha particles, bursts, UI effectstransparent margin without requiring partial alpha

The CLI is intentionally not a material classifier. The Agent should choose generation prompts and extraction methods based on the asset:

Asset typeGeneration guidanceExtraction guidance
Opaque object, icon, sticker, productSingle isolated subject, clear margin, perfectly flat chroma matte. Pick a matte color absent from the object.transparent generate or transparent extract --method chroma --matte-color auto
Thin edges, hair, fur, lace, chain, nettingUse high resolution, strong subject/background contrast, no contact shadow, no background-colored details. Try magenta/cyan/green mattes if one contaminates the edge.Chroma extraction with --spill-suppression when needed, then verify with --expected-matte-color; retry with a different matte if residue remains.
Glass, crystal, liquid, hologramAsk for a centered asset on flat black and flat white backgrounds, keeping geometry identical. Use reference/edit flow when possible to keep alignment.transparent extract --method dual --dark-image black.png --light-image white.png
Glow, flame, smoke, mist, magic particlesGenerate dark and light background variants. Avoid textured backgrounds and avoid bloom reaching the image edge unless the edge is intentional.Prefer dual extraction; verify that partial_pixels is non-zero.
ShadowsDecide whether the shadow is part of the asset. If not, explicitly forbid contact shadows. If yes, generate on a flat matte with enough margin.Chroma for opaque shadow silhouettes; dual extraction for soft translucent shadows.
Unknown or unusual materialDo not classify it first. Generate controlled source variants, run extraction candidates, and keep the one that passes verification with the cleanest edge.Use --report-dir / --keep-sources while iterating, then deliver only the final PNG.
Show full SKILL.md (451 more words)Show less

For chroma extraction, --matte-color auto samples the actual flat source background from the image edges. Prefer it when the source was AI-generated, because prompts like "pure #ff00ff" often produce near-matte colors rather than exact RGB values. Use explicit --matte-color <name|#rrggbb> only when the source background is known exactly.

For extraction tuning, use --material only as a broad hint, not as a subject classifier: standard, soft-3d, flat-icon, sticker, or glow. Manual --threshold, --softness, and --spill-suppression override the selected preset.

For style-locked transparent assets, transparent generate is prompt-only. Use a flat RGB reference image with images edit --ref-image to create a controlled matte source, then run transparent extract. Do not use a transparent PNG as the reference image unless you intentionally want the alpha/composited edge behavior to influence the edit.

GPT Image 2 can render accurate UI text, numbers, scores, labels, and logo marks in the bitmap when they are part of the desired artwork. Put the exact wording or numbering in the prompt and verify the output visually. Render text separately in the host app or design tool only when it must stay editable, localizable, programmatically changeable, or perfectly consistent across many generated variants.

Examples:

bash
# Simple asset: final transparent PNG, sources hidden unless there is a failure
node scripts/gpt_image_2_skill.cjs --json --json-events \
  transparent generate \
  --prompt "a polished fantasy sword game asset, no text, no frame" \
  --out /tmp/sword.png --size 2K --quality high

# Agent-controlled chroma flow
node scripts/gpt_image_2_skill.cjs --json --json-events \
  images generate \
  --prompt "a silver necklace, centered, on a perfectly flat pure magenta background, no shadow" \
  --out /tmp/necklace-magenta.png --format png --size 2K
node scripts/gpt_image_2_skill.cjs --json \
  transparent extract --method chroma \
  --input /tmp/necklace-magenta.png --matte-color auto \
  --out /tmp/necklace.png --material sticker --strict

# Semi-transparent material flow
node scripts/gpt_image_2_skill.cjs --json \
  transparent extract --method dual \
  --dark-image /tmp/glow-on-black.png \
  --light-image /tmp/glow-on-white.png \
  --out /tmp/glow.png --strict

Always inspect the JSON verification fields before delivery: passed, alpha_min, alpha_max, transparent_ratio, partial_pixels, and warnings. Also inspect quality fields: checkerboard_detected, touches_edge, edge_margin_px, stray_pixel_count, largest_component_ratio, matte_residue_checked, matte_residue_score, halo_score, transparent_rgb_scrubbed, alpha_health_score, residue_score, quality_score, and failure_reasons. If passed is false, do not deliver the file as a transparent PNG. If matte_residue_checked is false for a chroma-derived PNG, run transparent verify again with the source matte via --expected-matte-color.

Notes

  • 当前运行时默认值仍是 OpenAI gpt-image-2 / Codex gpt-5.4;Codex 使用上面的显式模型示例,不能依赖旧默认值。
  • 共同接受的 CLI 参数:--size、--quality、--format、--compression;Codex 服务端可能归一化这些参数,应核对返回值和实际文件。
  • OpenAI-only options: --n, --moderation, --mask, --input-fidelity; Codex background behavior requires separate verification.
  • Retries: up to 3 with exponential backoff (1s → 2s → 4s). Codex 401 triggers one token refresh + one retry.
  • Size aliases: 2K → 2048x2048, 4K → 3840x2160. Custom WxH requires both edges multiples of 16, max edge 3840, max 8,294,400 pixels, max aspect ratio 3:1.

Reference files

Load on demand for deeper detail:

  • references/codex-native-imagegen.md — App 原生工具、独立 Images 端点与旧 CLI 调用路径的区别。
  • references/codex-local-verification.md — 本地 Codex 生图命令、实测结果与模型识别边界。
  • references/providers.md — OpenAI / OpenAI-compatible / Codex selection, auth sources, runtime discovery, update policy, and resolution order.
  • references/sizes-and-formats.md — size aliases, custom constraints, format/quality/compression/background, shared vs OpenAI-only flags.
  • references/transparent-png.md — Agent playbook for prompt design, controlled mattes, dual-background extraction, verification, and retry loops.
  • references/json-output.md — --json stdout schema, success and error envelopes, per-command shapes.
  • references/json-events.md — --json-events JSONL phases (request_started, multipart_prepared, retry_scheduled) and Codex SSE passthrough.
  • references/troubleshooting.md — runtime_unavailable, auth_missing, Codex 401 refresh, retry policy, size rejections, moderation, timeouts.

Codex compatibility

The companion file agents/openai.yaml is read by Codex Skill runtime only (Claude Code ignores it). Both runtimes execute the commands above with cwd at the skill directory, so relative paths like scripts/gpt_image_2_skill.cjs resolve in either harness.

© Wangnov, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 14 other files (scripts, references) in skills/gpt-image-2-skill of Wangnov/gpt-image-2-skill.

  • SKILL.md
  • agents/openai.yaml
  • evals/README.md
  • evals/evals.json
  • evals/trigger-eval.json
  • references/codex-local-verification.md
  • references/codex-native-imagegen.md
  • references/json-events.md
  • references/json-output.md
  • references/providers.md
  • references/sizes-and-formats.md
  • references/transparent-png.md
  • references/troubleshooting.md
  • scripts/gpt_image_2_skill.cjs
  • scripts/selftest.cjs

Open the folder on GitHubat commit 16fcc05

Compare with similar skills

Gpt Image 2 Skill next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Gpt Image 2 Skill compared with similar skills
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Gpt Image 2 Skill this skillWangnov/gpt-image-2-skill142—~4.5kAutomated safety check: PassMIT
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Yingzaoop7418/guizang-yingzao-skill496—~1.1kAutomated safety check: PassNone
AI Image Creatorcentminmod/my-claude-code-setup2.7k—~8.1kAutomated safety check: NotesMIT
Character Refseternityspring/shuohao-skills4.3k—~1.7kAutomated safety check: WarnApache-2.0
Basic Memory Repo Imagesbasicmachines-co/basic-memory4.1k—~2.7kAutomated safety check: PassAGPL-3.0

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Works with

Questions about Gpt Image 2 Skill

What does Gpt Image 2 Skill do?

This skill should be used when the user asks to "generate an image", "create a logo", "draw an icon", "edit this photo", "change background to transparent", "remove background", "use GPT image"…. Gpt Image 2 Skill is an agent skill from Wangnov/gpt-image-2-skill. This skill should be used when the user asks to "generate an image", "create a logo", "draw an icon", "edit this photo", "change background to transparent", "remove background", "use GPT image", "use Codex to draw", "用 GPT image 生成图片", "用 Codex 画图", "帮我生成一张图", "改成透明背景", "把这张图编辑一下", or any prompt-to-image or reference-image-edit task that benefits from a structured CLI returning JSON results and JSONL progress events.

When should I use Gpt Image 2 Skill?

Gpt Image 2 Skill fits situations like: asks to generate an image; edit this photo; change background to transparent; remove background.

How do I install Gpt Image 2 Skill in Claude Code?

Run `npx skills add Wangnov/gpt-image-2-skill --skill gpt-image-2-skill -a claude-code`. Or copy the skill folder (skills/gpt-image-2-skill in Wangnov/gpt-image-2-skill) into .claude/skills/gpt-image-2-skill in your project. Claude Code loads it when a task matches its description.

How do I install Gpt Image 2 Skill in Codex?

Run `npx skills add Wangnov/gpt-image-2-skill --skill gpt-image-2-skill -a codex`. Or copy the skill folder (skills/gpt-image-2-skill in Wangnov/gpt-image-2-skill) into .agents/skills/gpt-image-2-skill in your project. Codex loads it when a task matches its description.

Can I use Gpt Image 2 Skill in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Wangnov/gpt-image-2-skill --skill gpt-image-2-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gpt-image-2-skill, .gemini/skills/gpt-image-2-skill, .github/skills/gpt-image-2-skill and .opencode/skills/gpt-image-2-skill in your project.

What does Gpt Image 2 Skill need to run?

Going by SKILL.md and its folder, Gpt Image 2 Skill needs JavaScript for the scripts in its folder, the command-line tools its instructions call (node, npm and cargo) and credentials named OPENAI_API_KEY. Our summary lists: Node.js; A credential in OPENAI_API_KEY.

Does Gpt Image 2 Skill access the network?

SKILL.md names 1 domain. As links in the text: developers.openai.com. This is read from the text; nothing was executed.

Is Gpt Image 2 Skill safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Gpt Image 2 Skill use?

Gpt Image 2 Skill is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Gpt Image 2 Skill use?

About 4.5k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 13k tokens, read only when the agent opens those files.

What are the alternatives to Gpt Image 2 Skill?

Skills that share tags, products or a category with Gpt Image 2 Skill: Nano Banana Pro Prompts Recommend Skill (YouMind-OpenLab/nano-banana-pro-prompts-recommend-skill, 1.9k stars), Yingzao (op7418/guizang-yingzao-skill, 496 stars), AI Image Creator (centminmod/my-claude-code-setup, 2.7k stars) and Character Refs (eternityspring/shuohao-skills, 4.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gpt Image 2 Skill?

Wangnov (a GitHub user) maintains it in Wangnov/gpt-image-2-skill, which has 142 GitHub stars. The repository was last updated on October 5, 2026.

Source: Wangnov/gpt-image-2-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.