Universal AI image generation supporting OpenAI DALL·E / gpt-image, Google Gemini Image / Imagen, Replicate (Flux / SDXL / any model), Stability AI, FAL, Ark (Seedream 4.5), Bailian (qwen-image / wanx), and SiliconFlow. Use this skill whenever the user asks to generate, create, draw, illustrate, render, or synthesize images from text prompts or reference images. Typical phrases include "draw a ...", "generate an image of ...", "画一张 ...", "给我来张图", "make a poster of ...", "create an illustration ...", or any mention of image-generation model families like DALL·E, gpt-image, Flux, SDXL, Seedream, Imagen, Gemini image, Kolors, or Wanx. Always use this skill even if the user does not name a specific model — pick a provider based on their EXTEND.md defaults or available API keys in the environment. Do NOT use this skill when the user explicitly mentions 即梦 / Dreamina / Jimeng — those go to happy-dreamina instead.
npx skills add https://github.com/iamzhihuix/happy-claude-skills --skill happy-image-gen
Generates still images across 8 providers through one CLI: bun scripts/main.ts .... The same CLI handles text-to-image and image-to-image (reference-driven) edits.
bun scripts/main.ts --prompt "A calico cat on green grass, cinematic light" --ar 16:9 --image ./out.png
Invoke this skill whenever the user:
Route to happy-dreamina instead when the user explicitly names 即梦, Jimeng, or the dreamina CLI.
Run these checks:
./.happy-skills/happy-image-gen/EXTEND.md (project)$XDG_CONFIG_HOME/happy-skills/happy-image-gen/EXTEND.md~/.happy-skills/happy-image-gen/EXTEND.md (user)If none exist, run bun scripts/main.ts --setup and follow references/config/first-time-setup.md to create one. Do not proceed to generation until the user has at least one provider configured.
OPENAI_API_KEY) or EXTEND.md references an api_key_env / api_key_source that resolves. If nothing resolves, loop back to setup.command -v bun. If missing, fall back to npx -y bun scripts/main.ts ....Pick in this order of preference:
--provider <id> explicitly passed by the user.default_provider in EXTEND.md.openai → google → replicate → stability → fal → ark → bailian → siliconflow.See references/providers.md for each provider's required env vars, default models, and strengths (e.g., prefer google for text-in-image, replicate for Flux-family photorealism, ark for Chinese text fidelity).
--prompt: the user's full request, trimmed. Always double-quote.--ar: aspect ratio — 1:1 / 16:9 / 9:16 / 3:4 / 4:3. See references/aspect_ratio_map.md for how each provider interprets this.--quality: draft (fastest + cheapest), hd (default), or ultra (4K-class, slower).--ref <path>: repeat for multiple reference images. Not every provider supports this — see providers.md.--model: override the default model for the chosen provider. Omit unless the user asked for a specific one.--image <path>: REQUIRED — output file path. Use a descriptive name (e.g., ./out/hero-landscape.png).bun scripts/main.ts \
--prompt "..." \
--image ./out.png \
--provider openai \
--ar 1:1 \
--quality hd
On success the CLI prints the resolved absolute path and byte count. In --json mode it emits:
{ "success": true, "provider": "openai", "model": "gpt-image-1", "image": "/abs/path.png", "size_bytes": 1416341, "format": "png" }
Echo the path back to the user.
config: No provider selected ... — no API key in env and no EXTEND.md. Loop back to Step 0.[openai] OpenAI images API 401 ... — key invalid or expired. Ask the user to refresh it.[openai] ... 400 ... content_policy_violation — prompt blocked. Show the raw error to the user; do not paraphrase.provider so the user knows what to check.See references/error_codes.md for a per-provider error table.
Read on demand:
references/providers.md — all 8 providers, required env vars, default models, strengths.references/aspect_ratio_map.md — how each provider interprets --ar.references/error_codes.md — common errors per provider and fixes.references/config/first-time-setup.md — step-by-step for --setup.references/config/extend-schema.md — EXTEND.md schema reference.Template for EXTEND.md: assets/EXTEND.template.md.
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Take iamzhihuix/happy-image-gen from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference npx.
Without those the skill loads but fails at the first command.