skills$openclaw/shopping-expert
udiedrichsen6.7k

by udiedrichsen

shopping-expert – OpenClaw Skill

shopping-expert is an OpenClaw Skills integration for coding workflows. Find and compare products online (Google Shopping) and locally (stores near you). Auto-selects best products based on price, ratings, availability, and preferences. Generates shopping list with buy links and store locations. Use when asked to shop for products, find best deals, compare prices, or locate items locally. Supports budget constraints (low/medium/high or "$X"), preference filtering (brand, features, color), and dual-mode search (online + local stores).

6.7k stars125 forksSecurity L1
Updated Feb 7, 2026Created Feb 7, 2026coding

Skill Snapshot

nameshopping-expert
descriptionFind and compare products online (Google Shopping) and locally (stores near you). Auto-selects best products based on price, ratings, availability, and preferences. Generates shopping list with buy links and store locations. Use when asked to shop for products, find best deals, compare prices, or locate items locally. Supports budget constraints (low/medium/high or "$X"), preference filtering (brand, features, color), and dual-mode search (online + local stores). OpenClaw Skills integration.
ownerudiedrichsen
repositoryudiedrichsen/shopping-expert
languageMarkdown
licenseMIT
topics
securityL1
installopenclaw add @udiedrichsen/shopping-expert
last updatedFeb 7, 2026

Maintainer

udiedrichsen

udiedrichsen

Maintains shopping-expert in the OpenClaw Skills directory.

View GitHub profile
File Explorer
4 files
.
scripts
shop.py
25.9 KB
_meta.json
466 B
SKILL.md
3.9 KB
SKILL.md

name: shopping-expert description: Find and compare products online (Google Shopping) and locally (stores near you). Auto-selects best products based on price, ratings, availability, and preferences. Generates shopping list with buy links and store locations. Use when asked to shop for products, find best deals, compare prices, or locate items locally. Supports budget constraints (low/medium/high or "$X"), preference filtering (brand, features, color), and dual-mode search (online + local stores). homepage: https://github.com/clawdbot/clawdbot metadata: {"clawdbot":{"emoji":"🛒","requires":{"bins":["uv"],"env":["SERPAPI_API_KEY","GOOGLE_PLACES_API_KEY"]},"primaryEnv":"SERPAPI_API_KEY","install":[{"id":"uv-brew","kind":"brew","formula":"uv","bins":["uv"],"label":"Install uv (brew)"}]}}

Shopping Expert

Find and compare products online and locally with smart recommendations.

Quick Start

Find products online:

uv run {baseDir}/scripts/shop.py "coffee maker" \
  --budget medium \
  --max-results 5

Search with budget constraint:

uv run {baseDir}/scripts/shop.py "running shoes" \
  --budget "$100" \
  --preferences "Nike, cushioned, waterproof"

Find local stores:

uv run {baseDir}/scripts/shop.py "Bio Gemüse" \
  --mode local \
  --location "Hamburg, Germany"

Hybrid search (online + local):

uv run {baseDir}/scripts/shop.py "Spiegelreflexkamera" \
  --mode hybrid \
  --location "München, Germany" \
  --budget high \
  --preferences "Canon, 4K Video"

Search US stores:

uv run {baseDir}/scripts/shop.py "running shoes" \
  --country us \
  --budget "$100"

Search Modes

  • online: E-commerce sites (Amazon, Walmart, etc.) via Google Shopping
  • local: Nearby stores via Google Places API
  • hybrid: Both online and local results merged and ranked
  • auto: Intelligent mode selection based on query (default)

Parameters

  • query: Product search query (required)
  • --mode: Search mode (online|local|hybrid|auto, default: auto)
  • --budget: "low/medium/high" or "€X"/"$X" amount (default: medium)
  • --location: Location for local/hybrid searches
  • --preferences: Comma-separated (e.g., "brand:Sony, wireless, black")
  • --max-results: Maximum products to return (default: 5, max: 20)
  • --sort-by: Sort order (relevance|price-low|price-high|rating)
  • --output: text|json (default: text)
  • --country: Country code for search (default: de). Use "us" for US, "uk" for UK, etc.

Budget Levels

  • low: Under €50
  • medium: €50-€150
  • high: Over €150
  • exact: "€75", "€250" (or "$X" for US searches)

Output Format

Default (text): Markdown table with product details, ratings, availability, and buy links

JSON: Structured data with all product metadata, scores, and links

Scoring Algorithm

Products are ranked using weighted scoring:

  • Price match (30%): Within budget range gets full points
  • Rating (25%): Higher ratings score better
  • Availability (20%): In stock > limited > out of stock
  • Review count (15%): More reviews = more trustworthy
  • Shipping/Distance (10%): Free shipping or nearby stores score higher
  • Preference match (bonus): Keywords in product description

API Keys Required

  • SERPAPI_API_KEY: Required for online shopping (all modes except local-only)
  • GOOGLE_PLACES_API_KEY: Only required for local and hybrid modes

Limitations

  • API limits: SerpAPI and Google Places have usage quotas
  • Real-time data: Prices and availability may change
  • Stock accuracy: Online availability reflects last API update
  • Local inventory: Store stock not guaranteed via Places API

Error Handling

  • Invalid query → Returns error with suggestions
  • No results found → Relaxes filters and retries
  • API failures → Retry with exponential backoff (3 attempts)
  • Missing API keys → Clear error message with setup instructions
README.md

No README available.

Permissions & Security

Security level L1: Low-risk skills with minimal permissions. Review inputs and outputs before running in production.

Requirements

  • OpenClaw CLI installed and configured.
  • Language: Markdown
  • License: MIT
  • Topics:

FAQ

How do I install shopping-expert?

Run openclaw add @udiedrichsen/shopping-expert in your terminal. This installs shopping-expert into your OpenClaw Skills catalog.

Does this skill run locally or in the cloud?

OpenClaw Skills execute locally by default. Review the SKILL.md and permissions before running any skill.

Where can I verify the source code?

The source repository is available at https://github.com/openclaw/skills/tree/main/skills/udiedrichsen/shopping-expert. Review commits and README documentation before installing.