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openai/imagegen

Générer ou modifier des images matricielles lorsque la tâche bénéficie de visuels bitmap créés par IA tels que des photos, illustrations, textures, sprites, maquettes ou découpes avec fond transparent.

Qu'est-ce que imagegen ?

Cette compétence permet à un agent IA comme Codex de générer ou modifier des images matricielles (bitmap) à l'aide de l'API OpenAI DALL·E. Elle est utile lorsque l'utilisateur a besoin de créer une nouvelle image à partir de zéro, de transformer une image existante (par exemple, recadrage, changement de style, ajout d'éléments) ou de générer des variantes visuelles à partir de références. L'agent utilise des appels API structurés pour envoyer des instructions en langage naturel et recevoir des images prêtes à l'emploi. La compétence est compatible avec les environnements de développement intégrant des appels API REST, comme les outils de terminal ou les IDE supportant l'exécution de code. Elle évite les cas où la modification de ressources SVG/vecteur existantes, l'extension de systèmes d'icônes ou la création de visuels directement en HTML/CSS/canvas serait plus appropriée. Le flux de travail consiste à analyser les spécifications de l'utilisateur, à formater la requête correctement pour l'API, puis à intégrer l'image résultante dans le projet cible.

Compatible avec~Claude Code✓Codex CLI~Cursor
npx skills add https://github.com/openai/skills/tree/main/skills/imagegen

Installed? Explore more Image skills: steipete/songsee, affaan-m/frontend-design, mattpocock/improve-codebase-architecture · View all 6 →

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Documentation

Que fait imagegen ?

Générer ou modifier des images matricielles lorsque la tâche bénéficie de visuels bitmap créés par IA tels que des photos, illustrations, textures, sprites, maquettes ou découpes avec fond transparent. À utiliser lorsque Codex doit créer une toute nouvelle image, transformer une image existante ou dériver des variantes visuelles à partir de références, et que le résultat doit être un actif bitmap plutôt qu'un code natif au dépôt ou un vecteur. Ne pas utiliser lorsque la tâche est mieux gérée en modifiant des actifs SVG/vecteur/code natif existants, en étendant un système d'icônes ou de logos établi, ou en construisant le visuel directement en HTML/CSS/canvas.

Utilisation

import requests
import json

response = requests.post(
    "https://api.openai.com/v1/images/generations",
    headers={
        "Authorization": f"Bearer {OPENAI_API_KEY}",
        "Content-Type": "application/json"
    },
    json={
        "model": "dall-e-3",
        "prompt": "Votre description détaillée de l'image",
        "n": 1,
        "size": "1024x1024"
    }
)
image_url = response.json()["data"][0]["url"]

Instructions

  1. Définir la requête – Décrivez l'image souhaitée en langage naturel, en précisant le style, le format et le contexte.
  2. Configurer les paramètres – Choisissez la taille (256x256, 512x512, 1024x1024) et le nombre d'images.
  3. Appeler l'API – Utilisez la clé OPENAI_API_KEY pour authentifier la requête.
  4. Récupérer l'image – Téléchargez l'image depuis l'URL retournée.
  5. Intégrer – Ajoutez l'image au dossier approprié du projet.

Variables d'environnement

  • OPENAI_API_KEY – Votre clé API OpenAI (obligatoire)

Bonnes pratiques

  • Prompts descriptifs – Soyez précis sur le sujet, le style et la composition.
  • Format de sortie – Les images sont générées en PNG par défaut.
  • Limitations – DALL·E 3 ne supporte pas la modification directe d'images existantes ; utilisez plutôt l'édition via inpainting si nécessaire.
  • Coût – Chaque appel API consomme des crédits selon la taille de l'image.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

openai/aspnet-core

Build, review, refactor, or architect ASP.NET Core web applications using current official guidance for .NET web development. Use when working on Blazor Web Apps, Razor Pages, MVC, Minimal APIs, controller-based Web APIs, SignalR, gRPC, middleware, dependency injection, configuration, authentication, authorization, testing, performance, deployment, or ASP.NET Core upgrades.

openai/chatgpt-apps

Build, scaffold, refactor, and troubleshoot ChatGPT Apps SDK applications that combine an MCP server and widget UI. Use when Codex needs to design tools, register UI resources, wire the MCP Apps bridge or ChatGPT compatibility APIs, apply Apps SDK metadata or CSP or domain settings, or produce a docs-aligned project scaffold. Prefer a docs-first workflow by invoking the openai-docs skill or OpenAI developer docs MCP tools before generating code.

openai/cli-creator

Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read/write commands, return stable JSON, manage auth, and pair with a companion skill.

openai/cloudflare-deploy

Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.

openai/develop-web-game

Use when Codex is building or iterating on a web game (HTML/JS) and needs a reliable development + testing loop: implement small changes, run a Playwright-based test script with short input bursts and intentional pauses, inspect screenshots/text, and review console errors with render_game_to_text.

openai/doc

Use when the task involves reading, creating, or editing `.docx` documents, especially when formatting or layout fidelity matters; prefer `python-docx` plus the bundled `scripts/render_docx.py` for visual checks.

openai/figma

Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.

openai/figma-code-connect-components

Connects Figma design components to code components using Code Connect mapping tools. Use when user says "code connect", "connect this component to code", "map this component", "link component to code", "create code connect mapping", or wants to establish mappings between Figma designs and code implementations. For canvas writes via `use_figma`, use `figma-use`.

openai/figma-create-design-system-rules

Generates custom design system rules for the user's codebase. Use when user says "create design system rules", "generate rules for my project", "set up design rules", "customize design system guidelines", or wants to establish project-specific conventions for Figma-to-code workflows. Requires Figma MCP server connection.

openai/figma-create-new-file

Create a new blank Figma file. Use when the user wants to create a new Figma design or FigJam file, or when you need a new file before calling use_figma. Handles plan resolution via whoami if needed. Usage — /figma-create-new-file [editorType] [fileName] (e.g. /figma-create-new-file figjam My Whiteboard)

openai/figma-generate-design

Use this skill alongside figma-use when the task involves translating an application page, view, or multi-section layout into Figma. Triggers: 'write to Figma', 'create in Figma from code', 'push page to Figma', 'take this app/page and build it in Figma', 'create a screen', 'build a landing page in Figma', 'update the Figma screen to match code'. This is the preferred workflow skill whenever the user wants to build or update a full page, screen, or view in Figma from code or a description. Discovers design system components, variables, and styles via search_design_system, imports them, and assembles screens incrementally section-by-section using design system tokens instead of hardcoded values.

openai/figma-generate-library

Build or update a professional-grade design system in Figma from a codebase. Use when the user wants to create variables/tokens, build component libraries, set up theming (light/dark modes), document foundations, or reconcile gaps between code and Figma. This skill teaches WHAT to build and in WHAT ORDER — it complements the `figma-use` skill which teaches HOW to call the Plugin API. Both skills should be loaded together.

openai/figma-implement-design

Translates Figma designs into production-ready application code with 1:1 visual fidelity. Use when implementing UI code from Figma files, when user mentions "implement design", "generate code", "implement component", provides Figma URLs, or asks to build components matching Figma specs. For Figma canvas writes via `use_figma`, use `figma-use`.

openai/figma-use

**MANDATORY prerequisite** — you MUST invoke this skill BEFORE every `use_figma` tool call. NEVER call `use_figma` directly without loading this skill first. Skipping it causes common, hard-to-debug failures. Trigger whenever the user wants to perform a write action or a unique read action that requires JavaScript execution in the Figma file context — e.g. create/edit/delete nodes, set up variables or tokens, build components and variants, modify auto-layout or fills, bind variables to properties, or inspect file structure programmatically.

openai/frontend-skill

Use when the task asks for a visually strong landing page, website, app, prototype, demo, or game UI. This skill enforces restrained composition, image-led hierarchy, cohesive content structure, and tasteful motion while avoiding generic cards, weak branding, and UI clutter.

openai/gh-address-comments

Help address review/issue comments on the open GitHub PR for the current branch using gh CLI; verify gh auth first and prompt the user to authenticate if not logged in.

openai/gh-fix-ci

Use when a user asks to debug or fix failing GitHub PR checks that run in GitHub Actions; use `gh` to inspect checks and logs, summarize failure context, draft a fix plan, and implement only after explicit approval. Treat external providers (for example Buildkite) as out of scope and report only the details URL.

openai/hatch-pet

Create, repair, validate, visually QA, and package Codex-compatible animated pets and pet spritesheets from character art, generated images, company or prospect brand cues, or visual references. Use when a user wants a lightweight-worker Codex pet workflow, a non-pixel custom pet style, a prospect or company mascot pet, or a full 8x9 animated pet atlas with transparent unused cells, QA contact sheets, and pet.json packaging. This skill composes the installed $imagegen system skill for visual generation and uses bundled scripts for deterministic spritesheet assembly.

openai/jupyter-notebook

Use when the user asks to create, scaffold, or edit Jupyter notebooks (`.ipynb`) for experiments, explorations, or tutorials; prefer the bundled templates and run the helper script `new_notebook.py` to generate a clean starting notebook.

openai/linear

Manage issues, projects & team workflows in Linear. Use when the user wants to read, create or updates tickets in Linear.

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