India Price Tracker

Track and compare product prices across popular Indian stores (Amazon India, Flipkart, Reliance Digital, Croma, Vijay Sales, Tata CLiQ, and more), compute ef...

Security Scan

The skill's code and runtime instructions match its stated purpose (local, mock price comparison and monitoring) and do not request unrelated credentials or perform hidden network/exfiltration operations.

Purpose & Capability

The name/description promise price comparison, tracking, and history analysis; the included scripts implement mock search, comparison, history, and CSV-driven bulk monitoring consistent with that purpose. There are no unexpected credentials, cloud SDKs, or unrelated binaries requested.

Instruction Scope

SKILL.md instructs running the included Python scripts in mock mode, reading local CSVs, and writing local reports. The instructions do not direct the agent to read unrelated system files, access external endpoints, or exfiltrate data. The README/setup explicitly recommends mock mode and validating policies before adding live adapters.

Install Mechanism

No install spec or external downloads are present; this is an instruction-plus-source bundle. All code is included in the package and there are no extract/download steps or third-party package installs declared.

Credentials

The skill only requires python3 (declared). It declares no environment variables, secrets, or config paths. The code uses deterministic mock data and local files only — no API keys or tokens are requested or referenced.

Persistence & Privilege

always is false and the skill does not attempt to modify other skills or global agent settings. It only writes local report files (e.g., reports/alerts.txt) when invoked, which is consistent with its functionality.

Assessment

This skill appears coherent and safe for local evaluation: run it in the provided mock mode first, follow setup.md and validation-checklist.md, and only implement 'live' adapters after you review each store's API/ToS and add proper rate-limiting and secure credential storage. Do not hardcode API keys into the source; inspect any later changes to scripts/config.py for network calls before running in production. Also be aware the scripts will write local report files (e.g., reports/alerts.txt) and may overwrite existing files with the same path.

Overview

Track prices across major Indian ecommerce stores and compare true payable cost, not just listed price.

Primary stores:

• Amazon India
• Flipkart
• Reliance Digital
• Croma
• Vijay Sales
• Tata CLiQ

Additional stores:

• JioMart
• Myntra
• AJIO
• Nykaa
• Snapdeal

Disclaimer

This skill provides tracking and comparison workflows only. It does not execute purchases. Store APIs, policies, and pricing terms can change. You are responsible for complying with each platform's Terms of Service and applicable laws.

Use at your own risk. The skill author/publisher/developer is not liable for direct or indirect loss, trading losses, missed opportunities, scraping/API bans, account restrictions, or other damages arising from use or misuse of this guidance.

What is improved vs generic price trackers

1. India-first store adapters

   • Store list and naming normalized for Indian catalogs.

2. Effective price modeling

   • Calculates final payable estimate:
   • effective_price = listing_price - instant_discount - coupon_discount - card_cashback + shipping

3. Pincode-aware availability

   • Supports regional availability and shipping variance inputs.

4. Arbitrage with fee model

   • Computes net margin after platform fees and shipping.

5. History + trend flags

   • Tracks 30/60/90 day movement and volatility.

6. Alerting modes

   • Price-drop threshold
   • Margin threshold
   • Restock + price condition

Setup

On first use, read setup.md, then run scripts in mock mode first.

Core workflows

1) Compare prices across stores

python3 scripts/compare_prices.py \
  --keyword "iPhone 15 128GB" \
  --stores amazon_in,flipkart,reliance_digital,croma,vijay_sales,tata_cliq \
  --report markdown

2) Track a product with threshold alerts

python3 scripts/track_product.py \
  --product "Sony WH-1000XM5" \
  --stores amazon_in,flipkart,croma \
  --alert-below 24999 \
  --alert-margin 0.18 \
  --pincode 560001

3) Bulk monitor from CSV

python3 scripts/bulk_monitor.py \
  --csv examples/products.india.csv \
  --margin-threshold 0.15 \
  --output reports/alerts.txt

4) Price history analysis

python3 scripts/price_history.py \
  --product "Samsung Galaxy S24" \
  --days 60 \
  --stores amazon_in,flipkart \
  --trend-analysis

Strategy rules

• Prefer effective price over headline price.
• Compare same SKU/variant only (storage, color, seller condition).
• Flag uncertain matches for manual review.
• Never assume stock parity across stores.
• Respect platform policies if implementing live adapters.

Output format

When asked to analyze products, return:

1. best store by effective price
2. next best alternative
3. arbitrage opportunity (if margin above threshold)
4. confidence notes (match quality, availability, shipping)

Files

• scripts/compare_prices.py
• scripts/track_product.py
• scripts/bulk_monitor.py
• scripts/price_history.py
• scripts/config.py
• examples/products.india.csv
• README.md

Validation

• Use validation-checklist.md before switching to any live adapter mode.
• Re-validate each store's terms, rate limits, and allowed integration method before production automation.