This is a submission for the Runner H "AI Agent Prompting" Challenge
What I Built
An autonomous AI agent that helps users plan smart purchases for any product by:
- 🧐 Researching historical pricing trends
- 🏷️ Identifying upcoming sales
- 🤑 Estimating price drop forecasts and potential savings
- ⏳ Suggesting the best time to buy
- 👉 Recommend relevant alternatives for the product enquired about
Demo
Video Demo
https://drive.google.com/file/d/1qzpWBunXu7eqQ2O0JvRGaPVpm86lYUEC/view?usp=sharing
Screenshots
| Title/Description | Screenshot |
|---|---|
| Sample Prompt |  |
| Document created in Runner-H |  |
| Output generated with Google Docs integration |  |
| Mail integration used to recieve the generated Google Docs |  |
Prompt generation
The below prompt is slightly different than the one used in the video. It is improved, more detailed and gives better results compared to the one used for recording the video.
I’m considering buying Iphone 15 [product to buy] and want to make a financially smart decision. Your role is to act as my Smart Purchase Advisor. I live in India [location for context]. Here’s what I want you to do step-by-step for any product I give you (either by name or link):
🔍 1. Research Current Prices
Search for the product across major Indian e-commerce platforms (Amazon, Flipkart, Croma, Reliance Digital, etc.) and return:
- Product name
- Platform
- Current selling price
- Link to listing
- Seller name (if available)
Present this data in a clean table or list.
📈 2. Analyze Historical Price Trends
- Use public sources like Keepa (Amazon), price tracker APIs, or summaries from past sales to answer:
- What was the lowest recorded price in the past 6–12 months?
- How much did it drop during past major sales (e.g., Diwali, Amazon Great Indian Festival, Prime Day)?
- What has been the average price fluctuation in recent months?
- Include clear pricing insights (e.g., “Price usually drops by 12–18% during Diwali sales.”).
📅 3. Detect Upcoming Sales
- Based on the product category and current month, identify the next relevant sales or discounts.
- For India, focus on: Amazon/Flipkart sales (e.g., Big Billion Days, Prime Day, Independence Day)
- Festival discounts (Diwali, Raksha Bandhan, Republic Day)
- Global deals (Black Friday, Cyber Monday, if international delivery is relevant)
- Mention: Sale Name, Approximate Dates, Product types typically discounted in that sale
💸 4. Forecast Expected Price & Recommend
- Based on the price trend and upcoming sales:
- Predict a likely sale price during the next event
- Estimate how much I could save
- Make a recommendation: “Buy Now”, “Wait for [Sale Name]”, or “No major discounts expected, safe to buy now.”
Provide a one-line summary like:
“Waiting 3 weeks for the Diwali sale could save you ₹4,500 (~15%) on this product.”
📤 5. Export Results to Google Sheet
Update the following columns in a sheet titled Smart Purchase Tracker (create it if not already present):
- Product Name
- Platform
- Current Price
- Estimated Sale Price
- Savings Amount
- Best Time to Buy
- Recommendation
📧 6. Send Me a Summary
Send a short summary (3–4 bullet points + recommendation) via email or Slack, formatted like:
How I Used Runner H
Use Case & Impact
The Smart Purchase Advisor & Deal Forecaster addresses a common pain point for millions of online shoppers — not knowing the best time to buy a product and often missing out on significant discounts during major sales.
👤 Who Benefits:
- Everyday consumers who want to save money while shopping online.
- Students and budget-conscious buyers who carefully time purchases (e.g., laptops, smartphones, books).
- Deal hunters and e-commerce enthusiasts who track prices across multiple platforms.
- Personal finance advocates who encourage mindful spending.
💡 Real-World Applications:
- Tracks historical pricing patterns using data sources like Keepa or CamelCamelCamel.
- Identifies region-specific sale events (like Diwali, Black Friday, Prime Day, etc.).
- Forecasts potential savings and makes a clear “Buy Now or Wait” recommendation.
- Sends updates via Slack or email and maintains a log in Google Sheets for multi-product tracking.
🚀 Impact:
- Saves users time by automating comparison shopping and research.
- Increases purchase confidence with data-backed forecasts.
- Reduces impulse buying by encouraging smarter, strategic purchases.
- Adds financial literacy by showing price trends and historical savings patterns.
Instead of manually checking 3+ sites and waiting for unpredictable discounts, users can now rely on an autonomous agent to handle all the research and notify them exactly when to act — making online shopping both smarter and stress-free.
Social Love
Save your money by visiting my AI agent workflow powered by Runner-H: https://t.co/CEu5w7qRPf
— Himanshu (@_himanshuc3) June 24, 2025
P.S. Don't be shy sharing your opinions, improvements and potential savings on and from the workflow 😉 pic.twitter.com/E4hTZoHohD
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