robonuggets/gpt-image-2-skill

Latest recorded source activity: April 22, 2026 at 00:46

SkillsMP catalog refreshed: October 29, 2026 at 18:30

skills collected: 1

GitHub stars: 74
GitHub forks: 14

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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/robonuggets/gpt-image-2-skill.

Repository README

Repository README source: README.md

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# GPT Image 2 Skill > Generate or edit images with OpenAI's GPT Image 2 — best-in-class for fine typography — via Fal AI. A Claude Code skill that wires GPT Image 2 (ChatGPT Images 2.0) into your agent in one drop-in file. Two endpoints: text-to-image AND image edit (with optional masks). Sync API, no polling, single POST. ## Why this model GPT Image 2 is currently the best public model for **legible text inside images**. Use it when the picture *is* the typography: - Chalkboards, store signs, hand-lettered posters - Menu boards, packaging mockups, magazine covers - UI screenshot / app store mockups - Social cards, banners, multilingual designs For photoreal portraits or strict style preservation, use a different model (Nano Banana, Flux). For everything text-heavy, this wins. ## Quick Start ### 1. Install the skill Copy the `SKILL.md` file to your Claude Code project's `.claude/skills/gpt-image-2/` directory. ### 2. Add your Fal AI key ```bash echo "FAL_KEY=your-fal-ai-key" >> .env ``` Get a key at [fal.ai/dashboard/keys](https://fal.ai/dashboard/keys). ### 3. Generate Tell Claude Code: ``` Generate a vintage diner chalkboard reading "TODAY SPECIAL — Lobster Roll $24" ``` Or for an edit: ``` Edit https://example.com/photo.png — same scene but everyone is on their phones now ``` ## Two endpoints | Endpoint | When | Required input | |----------|------|----------------| | `openai/gpt-image-2` | Generate from a prompt | `prompt` | | `openai/gpt-image-2/edit` | Modify an existing image | `prompt` + `image_urls` (+ optional `mask_url`) | The skill ships with one combined helper in Node, Python, and bash — pass `image_urls` to use the edit endpoint, omit for text-to-image. ## What You Get - **Sync API** — single POST returns the image URL. No polling, no taskId. - **Up to 4 images per call** for picking from variants. - **Custom dimensions** up to 3840×2160 (aspect ratio ≤ 3:1, multiples of 16). - **Image edit** with optional masks for surgical region edits. - **Combined helper** in Node, Python, and bash — same shape across languages. ## Defaults | Param | Default | Why | |-------|---------|-----| | `quality` | `medium` | Best cost/quality sweet spot (~$0.05/image). High is ~3.5x more — reserve for finals where typography really matters. | | `image_size` | `landscape_4_3` (T2I) / `auto` (Edit) | Sensible defaults, override per call. | | `num_images` | `1` | Bump to 4 for variants. | | `output_format` | `png` | | ## Prompting patterns The community has converged on two patterns the skill documents: 1. **Structured JSON prompts** for multi-element scenes (posters, infographics, comics, app mockups). Pass the prompt as a JSON object with explicit slots (`type`, `subject`, `style`, `background`, `header`, `layout`). Notably better than prose for complex layouts. 2. **Raycast-style placeholders** — `{argument name="quote" default="Stay hungry, stay foolish"}` — for parameterizable prompt templates. The skill also points at the **[awesome-gpt-image-2](https://github.com/YouMind-OpenLab/awesome-gpt-image-2)** community library (700+ curated prompts, CC BY 4.0) — when a user asks "how would I prompt this?" Claude can fetch the README, grep the relevant category, and adapt an example. ## Key Rules 1. **Default `quality: medium`** — `high` is ~3.5x the cost. Use medium for iteration, high for finals only. 2. **Auth header is `Key`, not `Bearer`** — Fal-specific. The skill notes this, but if you're hand-rolling: don't burn an hour like I did. 3. **Reference images need public URLs** — Fal storage, prior Fal output URL, or any external host. The skill explains how. 4. **No real transparent backgrounds** — Fal's wrapper doesn't expose OpenAI's `background: "transparent"` param. Asking the prompt for "transparent bg" gets you a *fake* checkerboard baked into RGB pixels. Chain `fal-ai/imageutils/rembg` on the output if you need real alpha. 5. **Edit endpoint preserves more when you describe the *change*, not the whole scene.** "Same workers, but on phones now" beats re-describing everything. ## Pricing Token-based, billed via Fal: | Quality | Rough cost (1536×1024) | |---------|------------------------| | `low` | ~$0.02 / image | | `medium` | **~$0.05 / image** ← default | | `high` | ~$0.18 / image | Quality is the biggest cost lever. Check actual usage in [fal.ai/dashboard](https://fal.ai/dashboard). ## Credits - Community prompt library: **[YouMind OpenLab — awesome-gpt-image-2](https://github.com/YouMind-OpenLab/awesome-gpt-image-2)** (CC BY 4.0). When you reuse a prompt verbatim, credit the original author named in each prompt's Details section. - Hosted via [Fal AI](https://fal.ai). - Model by [OpenAI](https://openai.com). ## Built By [RoboNuggets](https://robonuggets.com) — AI agent tools and community. ## License MIT

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gpt-image-2

Graphic Designers

Generate or edit images with OpenAI's GPT Image 2 (ChatGPT Images 2.0) via Fal AI. Two endpoints — text-to-image AND image edit (reference images + optional mask). Best-in-class for fine typography — chalkboards, signs, menus, posters, packaging, UI mockups,…

2026-04-22

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