+📖 About The Project
+In today's fast-paced e-commerce world, prices for the exact same product fluctuate wildly across different websites. Manually checking Amazon, Walmart, Best Buy, and other retailers to find the best deal is time-consuming and frustrating.
-# Webcmd
+Deal Pulse is a smart shopping analyzer that does the heavy lifting for you. Simply enter a product name, and Deal Pulse instantly scans the internet to provide you with a comprehensive price analysis. It finds the absolute lowest and highest prices available, calculates your exact savings, and gives you a direct link to make the purchase.
-**Self-learning browser infra for AI agents.**
+Stop overpaying and start shopping smarter with Deal Pulse!
-Webcmd learns the navigational context of websites as agents use them, then
-turns that knowledge into local memory for faster, cheaper, more reliable
-browser automation. The goal is simple: stop making agents rediscover the same
-sites on every run and cut browser-agent token spend by up to 90%.
+✨ Key Features
+🔍 Global Price Scanning: Scours multiple e-commerce platforms across the internet to find the product you are looking for.
-Webcmd pairs live browser control with a self-learning memory layer:
+📉 High/Low Price Detection: Instantly displays the highest and lowest prices currently available on the web.
-| Layer | Scenario | What Webcmd Helps With |
-| --- | --- | --- |
-| 0. Live browser control | The site is unfamiliar. | Use `webcmd browser` to inspect, click, type, extract, capture network calls, and complete the task in a real browser. |
-| 1. Sitemap memory | The site is familiar, but the action space is not fully known. | Capture an agent-facing sitemap of observed pages, states, actions, workflows, APIs, pitfalls, and fallback paths. |
+💰 Smart Savings Calculator: Automatically calculates and displays exactly how much money you save by choosing the best deal.
-## Demo
+🛒 Direct Purchase Links: One-click routing to the retailer offering the lowest price so you can checkout immediately.
-https://github.com/user-attachments/assets/bdb65307-9e2a-4d58-9175-45d59528ae37
+📊 Multi-Retailer Comparison: Provides a clean, comparative list of prices from other top retailers offering the exact same product.
-## Quick Start
+💻 How It Works
+Search: The user enters the name or URL of a desired product into the Deal Pulse search bar.
-### Agent prompt
+Analyze: Our engine scrapes and aggregates real-time pricing data from various trusted e-commerce platforms.
-```text
-Fetch and follow https://raw.githubusercontent.com/agentrhq/webcmd/main/start.md to set up Webcmd end to end.
-```
+Compare: The algorithm sorts the data, identifying the price ceiling (highest) and floor (lowest).
-### Manual
+Deliver: The user is presented with a dashboard showing their potential savings, alternative retailer prices, and the winning link to buy the product.
-Webcmd requires Node.js 20.6+.
+🛠️ Tech Stack
+(Update this section based on the actual technologies your team used!)
-```bash
-npm install -g @agentrhq/webcmd
-webcmd skills add
-```
+Frontend: React.js / HTML5 / CSS3 / Tailwind CSS
-When prompted, choose Claude, Codex, another supported harness, or a custom
-skills path. That installs exactly one skill, `webcmd-browser`.
+Backend: Node.js / Express / Python (Flask/Django)
-Load or tag `webcmd-browser` only for live browser work, then describe the
-outcome you want. Installation and setup commands do not require that skill.
-
-```text
-Use webcmd to research the latest discussions about browser automation across Hacker News and Reddit, then return a concise comparison with source links.
-```
-
-## What You Can Ask
-
-- “Use webcmd to research agentic browser automation on PubMed and return the title, authors, publication date, abstract, and URL for each result.”
-- “Use webcmd to find active AI infrastructure companies in the YC company directory and return the company, batch, description, location, profile URL, and source links. Keep it read-only.”
-- “Use webcmd to look up parts on Grainger by part number and return price, stock, minimum order quantity, lead time, and product URL.”
-- “Use webcmd with my logged-in `work` profile to summarize unread LinkedIn messages from the last seven days and return the sender, subject or opening text, received time, and conversation URL.”
-- “Use webcmd to check Grainger part prices and SAP Ariba purchase-order status, then return a combined summary.”
-
-## See It in Action
-
-```text
-Use webcmd with my logged-in `social` profile to collect my recent X bookmarks and return the author, text, and URL.
-```
-
-The agent uses the logged-in profile to complete the task in a real browser.
-Along the way, Webcmd quietly retains useful navigation context so later agents
-can avoid repeating the same exploration.
-
-## Where Webcmd Works
-
-Webcmd can work through authenticated browser sessions across research, social,
-AI, shopping, and booking products.
-
-| Group | Supported surfaces | Representative outcomes |
-| --- | --- | --- |
-| research and communities | Hacker News, Reddit, PubMed | Compare current discussions, find primary research, and return concise summaries with source links. |
-| social and professional | X/Twitter, LinkedIn, TikTok | Collect bookmarks, monitor public posts, or research people and creators with a named profile when needed. |
-| AI tools | ChatGPT, Claude, Gemini, NotebookLM | Retrieve conversations, research outputs, notebooks, and generated materials from the tools you already use. |
-| shopping and bookings | Amazon, Blinkit, Zepto, BigBasket, District, Practo | Compare products, availability, prices, appointments, events, and delivery options. |
-
-This list is illustrative. Webcmd can operate other websites through the same
-live browser workflow.
-
-## How Self-Learning Works
-
-
-
-Learning stays quiet and selective: the live browser is always truth, Webcmd
-never explores just to learn, and a memory failure never blocks the task. First
-access may use a Webcmd Cloud seed; subsequent learning stays local.
-
-For local, multi-step browser exploration, agents can send one sandboxed
-Playwright-style program to an explicit browser session:
-
-```bash
-webcmd --profile work session create "Work Project" -f json
-# id: work-project-k7
-webcmd --profile work --session work-project-k7 browser tabs
-webcmd --profile work --session work-project-k7 browser run --file explore.js
-printf 'return await page.title();' \
- | webcmd --profile work --session work-project-k7 browser run --stdin
-webcmd --profile work session close work-project-k7
-```
-
-Profiles are cookie jars; Sessions are independent browser windows within a
-profile, so Session IDs are immutable, Profile-scoped, and safe to reuse for
-that Session's lifetime. Parallel agents should create separate Sessions.
-Raw browser commands require an explicit readable Session ID.
-
-## Benchmarks
-
-On [BU Bench V1](https://github.com/browser-use/benchmark#bu-bench-v1), a
-100-task browser automation benchmark, Webcmd recorded the highest accuracy and
-lowest estimated controller cost per completed task, and fewest agent turns per
-completed task in this comparison.
-
-
-
-All tools used the same Pi controller, controller model, Codex `gpt-5.4` judge,
-and CloakBrowser engine. This is a stronger judge than the original BU Bench
-setup, whose [current runner uses Gemini 2.5 Flash](https://github.com/browser-use/benchmark/blob/main/run_eval.py#L37-L38).
-Accuracy is passed tasks out of 100. Cost and agent turns are averaged over
-completed tasks; cost excludes judge usage. See the
-[benchmark report](./benchmarks/README.md) for category results, methodology,
-architectural analysis, and reproduction steps.
-
-## Learn More
-
-Webcmd Cloud can run supported commands and browser sessions on hosted infrastructure. It is in active development and is not yet stable.
-
-- [Prompt Cookbook](https://webcmd.dev/docs/agent-prompts)
-- [How Webcmd Works](https://webcmd.dev/docs/concepts)
-- [Local or Cloud](https://webcmd.dev/docs/local-or-cloud)
-- [Command Surface](https://webcmd.dev/docs/cli-reference)
-
-## Contributing
-
-See [CONTRIBUTING.md](./CONTRIBUTING.md).
-
-## License
-
-Released under the terms in [`LICENSE`](./LICENSE).
+Web Scraping / API: BeautifulSoup / Puppeteer / RapidAPI e-commerce endpoints
diff --git a/analyzer.js b/analyzer.js
new file mode 100644
index 000000000..e69de29bb
diff --git a/debug.html b/debug.html
new file mode 100644
index 000000000..03a588e25
--- /dev/null
+++ b/debug.html
@@ -0,0 +1,19 @@
+# Fetched content
+
+Source: https://www.google.com/search?tbm=shop&q=Sony+WH-1000XM5&hl=en
+Final URL: https://www.google.com/search?q=Sony+WH-1000XM5&hl=en&udm=28
+Content type: text/html; charset=UTF-8
+Extraction: raw
+Bytes: 92537
+Truncated: true
+
+Google Search
-
-
- 
-
-
- 
-
-
- 
-
-
- 
-
-
+🛍️ Deal Pulse
+The Ultimate Shopping Analyzer
+Built with ❤️ for the webcmd Hackathon
-
-
-Learning stays quiet and selective: the live browser is always truth, Webcmd
-never explores just to learn, and a memory failure never blocks the task. First
-access may use a Webcmd Cloud seed; subsequent learning stays local.
-
-For local, multi-step browser exploration, agents can send one sandboxed
-Playwright-style program to an explicit browser session:
-
-```bash
-webcmd --profile work session create "Work Project" -f json
-# id: work-project-k7
-webcmd --profile work --session work-project-k7 browser tabs
-webcmd --profile work --session work-project-k7 browser run --file explore.js
-printf 'return await page.title();' \
- | webcmd --profile work --session work-project-k7 browser run --stdin
-webcmd --profile work session close work-project-k7
-```
-
-Profiles are cookie jars; Sessions are independent browser windows within a
-profile, so Session IDs are immutable, Profile-scoped, and safe to reuse for
-that Session's lifetime. Parallel agents should create separate Sessions.
-Raw browser commands require an explicit readable Session ID.
-
-## Benchmarks
-
-On [BU Bench V1](https://github.com/browser-use/benchmark#bu-bench-v1), a
-100-task browser automation benchmark, Webcmd recorded the highest accuracy and
-lowest estimated controller cost per completed task, and fewest agent turns per
-completed task in this comparison.
-
-
-
-All tools used the same Pi controller, controller model, Codex `gpt-5.4` judge,
-and CloakBrowser engine. This is a stronger judge than the original BU Bench
-setup, whose [current runner uses Gemini 2.5 Flash](https://github.com/browser-use/benchmark/blob/main/run_eval.py#L37-L38).
-Accuracy is passed tasks out of 100. Cost and agent turns are averaged over
-completed tasks; cost excludes judge usage. See the
-[benchmark report](./benchmarks/README.md) for category results, methodology,
-architectural analysis, and reproduction steps.
-
-## Learn More
-
-Webcmd Cloud can run supported commands and browser sessions on hosted infrastructure. It is in active development and is not yet stable.
-
-- [Prompt Cookbook](https://webcmd.dev/docs/agent-prompts)
-- [How Webcmd Works](https://webcmd.dev/docs/concepts)
-- [Local or Cloud](https://webcmd.dev/docs/local-or-cloud)
-- [Command Surface](https://webcmd.dev/docs/cli-reference)
-
-## Contributing
-
-See [CONTRIBUTING.md](./CONTRIBUTING.md).
-
-## License
-
-Released under the terms in [`LICENSE`](./LICENSE).
+Web Scraping / API: BeautifulSoup / Puppeteer / RapidAPI e-commerce endpoints
diff --git a/analyzer.js b/analyzer.js
new file mode 100644
index 000000000..e69de29bb
diff --git a/debug.html b/debug.html
new file mode 100644
index 000000000..03a588e25
--- /dev/null
+++ b/debug.html
@@ -0,0 +1,19 @@
+# Fetched content
+
+Source: https://www.google.com/search?tbm=shop&q=Sony+WH-1000XM5&hl=en
+Final URL: https://www.google.com/search?q=Sony+WH-1000XM5&hl=en&udm=28
+Content type: text/html; charset=UTF-8
+Extraction: raw
+Bytes: 92537
+Truncated: true
+
+