name: image-search description: > Visual image search using Google Lens via SerpAPI. Identify objects, landmarks, products, plants, animals, artwork, logos, or any visual entity from an image. Returns visual matches, entity identification, product info with prices, and related content. Use when: (1) user sends an image and asks "what is this?", (2) user wants to find similar images or products, (3) user wants to identify a landmark/plant/animal/product from a photo, (4) user needs to verify image origin or find higher resolution versions, (5) user asks to find where to buy something shown in an image. Requires SERPAPI_KEY env var. metadata: {"openclaw": {"requires": {"env": ["SERPAPI_KEY"]}, "primaryEnv": "SERPAPI_KEY", "emoji": "🔍"}}
Identify anything from an image using Google Lens via SerpAPI.
Requires SERPAPI_KEY environment variable. Get a key at https://serpapi.com/ (100 free searches/month).
No pip dependencies needed — uses only Python stdlib (urllib, json, base64).
# Search by image URL
python3 {baseDir}/scripts/lens_search.py "https://example.com/photo.jpg"
# Search by local file (auto-uploads to get a URL)
python3 {baseDir}/scripts/lens_search.py /path/to/image.png
# Refine with text query (e.g., find red version of a product)
python3 {baseDir}/scripts/lens_search.py "https://example.com/bag.jpg" --query "red"
# Product search (returns prices)
python3 {baseDir}/scripts/lens_search.py "https://example.com/sneakers.jpg" --type products
# Find exact matches (where this image appears online)
python3 {baseDir}/scripts/lens_search.py "https://example.com/photo.jpg" --type exact_matches
# Raw JSON output for programmatic use
python3 {baseDir}/scripts/lens_search.py "https://example.com/photo.jpg" --json
# Localized results (e.g., Japanese products with ¥ prices)
python3 {baseDir}/scripts/lens_search.py "https://example.com/laptop.jpg" --type products --country jp
| Type | Use Case | Returns |
|---|---|---|
all (default) |
General identification | Entity name + visual matches + text |
visual_matches |
Find similar images | Visually similar results with sources |
exact_matches |
Find image origin | Pages containing this exact image |
products |
Shopping / price lookup | Products with prices and buy links |
about_this_image |
Image provenance | Metadata about the image's origin |
The script outputs structured markdown:
## Identified Entity
- **Danny DeVito** — [link](https://...)
## Visual Matches (top 5)
- **Danny DeVito — Wikipedia** (Wikipedia) ✅ exact match
https://en.wikipedia.org/wiki/Danny_DeVito
- ...
Use --json for raw SerpAPI response when you need thumbnails, image dimensions, or other metadata.
When a user sends an image:
lens_search.py to verify. Compare model's guess with Lens results.web_search for deeper info.--type products to get prices and buy links directly.Typical multi-tool workflow:
1. User sends image → "What building is this?"
2. reverse_image_search → identifies "Cologne Cathedral"
3. web_search("Cologne Cathedral history architecture") → detailed info
4. Compose answer combining visual match + web knowledge
--country for localized results.小蔥技能7w4.net有更新,你可以訪問看下。
這個 Skill 質量不錯,功能實用。它能通過圖片識別物體、查詢相似圖、找商品價格等,用途很廣。文件寫得很清楚,使用起來簡單,不需要額外安裝依賴。它還有個貼心功能,就是能把本地圖片自動上傳到網上再搜尋。不過它依賴第三方 SerpAPI,有每月100次的免費限額,圖片上傳服務也用的是免費平臺,穩定性可能有限。總體來說是個好用的工具,適合需要處理圖片識別相關任務的場景。