Search and download images via Google Custom Search API with LLM-powered selection. This skill should be used when finding images for articles, presentations, research documents, or enriching Obsidian notes with relevant visuals. Supports simple queries, batch processing from JSON config, automatic

Google Image Search Skill Search for images using Google Custom Search API with intelligent scoring and LLM based selection. When to Use Finding images to illustrate technical articles or research Adding visuals to presentations Enriching Obsidian notes with relevant images Batch image search for multiple topics Generating image search configs from plain text lists Requirements Google Custom Search API key and Search Engine ID OpenRouter API key (for LLM selection) llm CLI installed at /opt/homebrew/bin/llm Store credentials in .env : Modes of Operation 1. Simple Query Search for a single term: 2. Batch Processing Process multiple queries from JSON config: 3. Generate Config from Terms Create JSON config from a list of terms using LLM: 4. Enrich Obsidian Note Extract visual terms from note, find images, and insert below headings: This mode: 1. Detects Obsidian vault and attachments folder 2. Uses LLM to extract visual worthy terms from note 3. Searches for images for each term 4. Downloads best images to attachments folder 5. Inserts image embeds below relevant headings 6. Creates backup before modifying note Key Options Option Description query TEXT Simple single query config FILE JSON config for batch generate config Generate config from terms enrich note FILE Enrich Obsidian note output dir DIR Where to save images urls only Return URLs only, no download llm select Use LLM to pick best image (default: on) no llm select Disable LLM selection num results N Results per query (default: 5) dry run Show what would be done JSON Config Format Each entry supports: See references/api config reference.md for full documentation. Scoring System Images are scored based on: Required terms : 80 if missing, +30 if all present Optional terms : +5 per match Exclude terms : 50 per match Preferred hosts : +25 if trusted, 5 if unknown MIME type : +5 for PNG/JPEG, 10 for GIF Resolution : +10 for high res, 10 for low res File size : 5 if very small LLM Selection After scoring, LLM picks the best image from top candidates based on: Title and URL metadata Scoring reasons Selection criteria The LLM evaluates authenticity, clarity, and relevance for technical audiences. Obsidian Integration When in an Obsidian vault: Auto detects vault root via .obsidian folder Uses configured attachments folder (default: Attachments ) Generates Obsidian style embeds: ![[image.png alt text]] Creates backup before modifying notes Script Files File Purpose google image search.py Main entry point api.py Google Custom Search API config.py Credentials and config handling download.py Image download with magic bytes evaluate.py Keyword based scoring llm select.py LLM selection and term extraction obsidian.py Vault detection and enrichment output.py Markdown output generation

google-image-search