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Research & Knowledge

Shopping Expert skill for OpenClaw

⬇ 4.5K downloads ★ 7 stars Version 1.1.0 Rank #1713 of 10,000+

What this skill does

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).

The Shopping Expert skill is part of the Research & Knowledge category — research and knowledge skills that gather, search, and summarize information. You can install it on its own or alongside other research & knowledge skills from the OpenClaw catalog.

The Shopping Expert skill is ranked #1713 by downloads in the OpenClaw skill catalog (4.5K total downloads, 7 stars). It belongs to the Research & Knowledge category alongside 1884 other top-10000 skills.

How to install the Shopping Expert skill

The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:

  1. Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
  2. Open the in-app Skills panel.
  3. Search for shopping-expert and click Install.
  4. The skill activates automatically when an incoming message matches its description.

Install from the command line

If you already run the OpenClaw CLI, add the Shopping Expert skill with a single command:

openclaw skills add shopping-expert

This pulls shopping-expert from ClawHub and installs it into ~/.openclaw/skills/shopping-expert/. Restart the OpenClaw gateway afterwards so the new skill is discovered.

How to use the Shopping Expert skill

Once installed, the Shopping Expert skill activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.

Manual install (advanced)

If you prefer manual installation:

  1. Click the Download skill .zip button above to grab shopping-expert-1.1.0.zip directly from our S3 mirror.
  2. Unzip into ~/.openclaw/skills/shopping-expert/ (create the directory if it does not exist).
  3. Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.

Frequently asked questions

How do I install Shopping Expert?

Install Shopping Expert in the OpenClaw Easy desktop app by opening the Skills panel, searching for shopping-expert, and clicking Install. From a terminal you can run: openclaw skills add shopping-expert. Either way the skill is placed in ~/.openclaw/skills/shopping-expert/.

Is the Shopping Expert skill free?

Yes. It is free to download and run through ClawHub, with no account or payment required. Each skill is published by its own author under its own licence — see its ClawHub page for the licence and source.

What does Shopping Expert do?

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.

Related: more research & knowledge skills

If the Shopping Expert skill looks useful, you may also want to check out other research & knowledge skills in the OpenClaw catalog:

Skills in this catalog are community-contributed integrations published on ClawHub and distributed under their own open-source licences. Product and company names, and any third-party service a skill connects to, are trademarks of their respective owners; a listing here does not imply affiliation with, sponsorship by, or endorsement from them. This page does not distribute any third-party application. Rights holders can reach us at hello@openclaw-easy.com.

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Free, open-source · Apache-2.0 · Works with Claude, ChatGPT, Gemini, or local Ollama models