image-well

Solid

Search and download images from 12 APIs in parallel (Openverse, Pexels, Pixabay, Met Museum, NASA, Rijksmuseum, Wikimedia Commons, Unsplash, Smithsonian, Europeana, Iconify, Pollinations AI). Supports license filtering, presets (military, museum, stock), cached results, and bulk download with metadata sidecars. Triggers on find images, stock photos, public domain artwork, museum images, CC-licensed, NASA photos, icons.

Web & Frontend 41 stars 3 forks Updated yesterday MIT

Install

View on GitHub

Quality Score: 84/100

Stars 20%

Recency 20%

100

Frontmatter 20%

Documentation 15%

100

Issue Health 10%

License 10%

100

Description 5%

100

Skill Content

# Image Well Search and download images from 12 sources through a single CLI. Four sources work with zero API keys (Openverse, Wikimedia, Met Museum, NASA). Additional sources activate when keys are set. ## Quick Start ```bash # Search across all no-key sources uv run ~/.claude/skills/image-well/scripts/well.py search "ancient Minoan fresco" # Use a preset for domain-specific searches uv run ~/.claude/skills/image-well/scripts/well.py search "F-35 fighter jet" --preset military # Download results with metadata sidecars uv run ~/.claude/skills/image-well/scripts/well.py search "sunset" --format download --output ./images/ # Check which sources are available uv run ~/.claude/skills/image-well/scripts/well.py sources # Visual HTML preview — opens in browser, no context pollution uv run ~/.claude/skills/image-well/scripts/well.py search "bronze statue" --format html # Output as JSON for piping uv run ~/.claude/skills/image-well/scripts/well.py search "cat" --format json ``` ## Sources | Tier | Source | Key Required | License | |------|--------|-------------|---------| | 1 | Openverse (800M+) | No | CC variants | | 1 | Wikimedia Commons | No | CC variants | | 1 | Met Museum (375k) | No | CC0 | | 1 | NASA (140k) | No | Public Domain | | 2 | Pexels | `PEXELS_API_KEY` | Pexels License | | 2 | Pixabay | `PIXABAY_API_KEY` | Pixabay License | | 2 | Rijksmuseum (700k) | `RIJKSMUSEUM_API_KEY` | CC0 | | 2 | Unsplash | `UNSPLASH_ACCESS_KEY` | Unsplash License | | 3 | Smithsonian |...

Details

Author: tdimino
Repository: tdimino/claude-code-minoan
Created: 7 months ago
Last Updated: yesterday
Language: Python
License: MIT

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Listed

generate-image

Generate AI images (illustrations, icons, abstract art, product/brand visuals, transparent-background graphics) via the OpenAI Images API, or fetch real photographs (people, lifestyle, office, nature) from Unsplash or Pexels, then save them straight into a project's assets/public folder. Use this whenever a website, app, or design task needs an image and one isn't already provided — hero images, avatars, backgrounds, favicons, OG images, blog thumbnails, empty-state illustrations, team photos, stock photography. Also use when the user says things like "generate an image of...", "we need a photo of...", "find/download a picture of...", "make an illustration for...", or "get me some stock photos of...".

0 Updated 1 weeks ago

bubblesdev

AI & Automation Solid

creative-toolkit

Generate images from text with multi-provider routing — supports Nanobanana Pro, GPT Image, Seedream, and local ComfyUI workflows. Includes 1,300+ curated prompts and style-aware prompt enhancement. Use when users want to create images, design assets, enhance prompts, or manage AI art workflows.

8 Updated 2 days ago

HUANGcvs

AI & Automation Listed

free-image-and-video-generation

Free local AI image and video processing toolkit with cloud AI generation. Local tools: upscale (Real-ESRGAN), face enhance (GFPGAN/CodeFormer), background remove (rembg), object erase (LaMa), face swap (InsightFace), segment (FastSAM), media process (FFmpeg). Cloud tools: AI image/video generation via Atlas Cloud API (300+ models). For cloud generation, ALWAYS first use Atlas Cloud MCP tools (atlas_list_models, atlas_get_model_info) to find the model ID and parameter schema, then call scripts/ai-generate.py with the correct --model and parameters. Use when user asks to process, enhance, upscale, generate, or edit images/videos.

1 Updated today

xramjetx