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": "🔍"}}

Image Search (Google Lens)

Identify anything from an image using Google Lens via SerpAPI.

Setup

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).

7w4.net有更好的技能插件。

Usage

From CLI / Agent (exec tool)

# 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

Search Types

Output Format

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.

Agent Decision Guide

When a user sends an image:

1. Already identified by vision model? If the main model confidently recognizes the entity, skip reverse search.
2. Uncertain identification? Run lens_search.py to verify. Compare model's guess with Lens results.
3. Need details beyond identification? First identify with Lens, then web_search for deeper info.
4. Shopping intent? Use --type products to get prices and buy links directly.
5. Local file from user? The script handles local files by auto-uploading to get a searchable URL.

Combining with Other Tools

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

Limitations

• SerpAPI free tier: 100 searches/month. Paid plans from $50/month.
• Local file upload uses freeimage.host (free) or imgbb (needs IMGBB_API_KEY).
• Google Lens results vary by region; use --country for localized results.
• Some niche/long-tail entities may not return useful visual matches.

这个 Skill 质量不错，功能实用。它能通过图片识别物体、查找相似图、找商品价格等，用途很广。文档写得很清楚，使用起来简单，不需要额外安装依赖。它还有个贴心功能，就是能把本地图片自动上传到网上再搜索。不过它依赖第三方 SerpAPI，有每月100次的免费限额，图片上传服务也用的是免费平台，稳定性可能有限。总体来说是个好用的工具，适合需要处理图片识别相关任务的场景。