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How to give your OpenClaw agent Access To Walmart Data in Less Than 2 Minutes

#openclaw #ai #python #agents

If you're building a shopping or price comparison agent with OpenClaw, Amazon alone isn't enough. A lot of US retail happens at Walmart — and Walmart has data Amazon doesn't, like in-store availability, same-day pickup, and local pricing by ZIP code.

Here's how to add it.

1. Install the skill 

clawhub install scavio-walmart
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2. Set your API key

Get a free key at scavio.dev (1,000 credits/month, no card), then:

export SCAVIO_API_KEY=sk_live_your_key
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3. Ask your agent

Your agent can now search Walmart products and look up product details by ID:

Find standing desks under $300 on Walmart sorted by best seller.
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Search Walmart for air purifiers that can be delivered by tomorrow to ZIP code 10001.
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Look up Walmart product 123456789 and give me the full details including current price and availability.
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The skill covers both product search (with price range, sort, fulfillment speed, delivery ZIP, and in-store filters) and full product detail lookup by Walmart product ID.

What makes this different from Amazon

Walmart-specific filters your agent can use:

  • fulfillment_speed — today, tomorrow, 2_days, anytime
  • fulfillment_type — in_store for click-and-collect
  • delivery_zip — localized pricing and availability by ZIP code
  • store_id — filter to a specific Walmart store

These don't exist in the Amazon skill. If your agent needs to answer "can I get this today near me?", Walmart is the right call.

Pair with scavio-amazon for price comparison

Install both skills and your agent can compare prices across retailers automatically:

Compare the price of Sony WH-1000XM5 headphones on Amazon and Walmart.
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Both skills return the same JSON structure so the agent can reason over them together without any adapter logic.

Direct API access 

import os, requests

response = requests.post(
    "https://api.scavio.dev/api/v1/walmart/search",
    headers={"Authorization": f"Bearer {os.environ['SCAVIO_API_KEY']}"},
    json={"query": "standing desk", "sort_by": "best_seller", "max_price": 300},
)
print(response.json()["data"])
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Full docs at scavio.dev/docs

(I work with the Scavio team.)

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