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smart-price-monitor智能价格监控

Agent Skill

smart-price-monitor 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,143

周安装

135

GitHub Stars

公开资料未说明

下载量

1,102
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:smart-price-monitor(智能价格监控)
来源仓库:https://github.com/chloepark85/smart-price-monitor
安装命令:
openclaw skills install smart-price-monitor
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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openclaw skills install smart-price-monitor

简介

智能价格监控系统实时跟踪商品价格、库存与市场趋势变化。

  • 适用于电商比价、抢购提醒与投资品价格波动监测等场景。
  • 支持自定义阈值报警与多平台数据聚合展示。smart-price-monitor 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 在 OpenClaw 中响应用户的价格查询或监控请求时自动启用。
  • 使用前请配置目标网站 API 或爬虫权限,注意合规性与频率限制。

SKILL.md

name
smart-price-monitor
description
>

Smart Price & Deal Monitor

A comprehensive skill for monitoring real-world prices, deals, and market data with intelligent alerting and trend analysis. Turns your AI agent into a vigilant price-watching assistant that tracks changes, spots deals, and surfaces insights automatically.

What This Skill Does

This skill enables three core workflows:

  1. Price Monitoring — Track product prices across e-commerce sites and APIs over time
  2. Deal Detection — Identify price drops, sales, and deals that match user criteria
  3. Market Intelligence — Analyze pricing trends, competitor pricing, and market dynamics

Quick Start

When the user asks to monitor a price or track a deal, follow this sequence:

  1. Ask what they want to monitor (product URL, search term, or data source)
  2. Set up the monitoring target configuration
  3. Define alert thresholds (price drop %, absolute price target, restock)
  4. Choose delivery method (file report, notification summary, or dashboard)
  5. Run the first data collection to establish a baseline

Core Workflow

Step 1: Identify Monitoring Targets

Ask the user for one or more of:

  • Product URLs — Direct links to products on any e-commerce site
  • Search queries — "iPhone 16 Pro Max 256GB" across multiple retailers
  • API endpoints — REST APIs that return pricing data (stocks, crypto, commodities)
  • Competitor pages — Competitor product/pricing pages to watch

Store targets in a monitors.json configuration file:

{
  "monitors": [
    {
      "id": "monitor-001",
      "name": "iPhone 16 Pro Max - Amazon",
      "type": "product_url",
      "source": "https://amazon.com/dp/B0EXAMPLE",
      "check_interval": "6h",
      "alert_rules": {
        "price_drop_pct": 5,
        "price_target": 899,
        "restock_alert": true
      },
      "history": []
    }
  ],
  "settings": {
    "currency": "USD",
    "timezone": "America/Los_Angeles",
    "report_format": "markdown"
  }
}

Step 2: Data Collection

For each monitoring target, extract pricing data using the appropriate method:

Web Scraping Approach (for product URLs):

  1. Fetch the page using available web tools (WebFetch, browser tools, or curl)
  2. Parse the HTML/markdown to extract: current price, original price, availability, seller, ratings
  3. Handle common anti-bot patterns: rotate user agents, respect robots.txt, add delays
  4. Store extracted data with timestamp in the history array

API Approach (for structured data sources):

  1. Call the API endpoint with appropriate headers
  2. Parse JSON/XML response for price fields
  3. Handle pagination if needed
  4. Normalize data into standard format

Search-Based Approach (for price comparison):

  1. Search for the product across multiple retailers
  2. Extract prices from search results
  3. Rank by price, factoring in shipping and seller reputation
  4. Build a comparison table

Step 3: Trend Analysis

After collecting data points over time, analyze trends:

  • Price Direction — Is the price trending up, down, or stable?
  • Volatility — How much does the price fluctuate? High volatility = wait for a dip
  • Seasonality — Does this product follow seasonal pricing? (holidays, back-to-school, etc.)
  • Best Time to Buy — Based on historical data, when is the optimal purchase window?
  • Deal Score — Rate current price vs. historical average (0-100, where 100 = best deal ever)

Calculate a simple Deal Score:

deal_score = max(0, min(100, ((historical_avg - current_price) / historical_avg) * 200 + 50))

Step 4: Alert Generation

Generate alerts when conditions are met:

Alert Types:

  • PRICE_DROP — Price decreased by more than threshold percentage
  • TARGET_REACHED — Price hit or fell below the user's target price
  • RESTOCK — Previously out-of-stock item is now available
  • NEW_LOW — All-time lowest price detected
  • DEAL_EXPIRING — Sale or deal is ending soon
  • COMPETITOR_CHANGE — Competitor changed their pricing

Alert Format:

## Price Alert: [Product Name]

**Status:** PRICE_DROP
**Current Price:** $849.99 (was $999.99)
**Drop:** -15.0% ($150.00 savings)
**Deal Score:** 87/100
**Historical Low:** $829.99 (Black Friday 2025)
**Recommendation:** Strong buy — this is within 2% of the all-time low.

[Link to product](url)

Step 5: Reporting

Generate reports in the user's preferred format:

Daily Summary Report:

  • All monitored items with current prices
  • Items with price changes in the last 24 hours
  • Top deals (sorted by deal score)
  • Items approaching target prices

Trend Report (Weekly/Monthly):

  • Price charts showing trends for each item (ASCII or HTML)
  • Average prices by category
  • Best deals found this period
  • Recommendations for when to buy vs. wait

Comparison Report:

  • Side-by-side pricing across retailers
  • Total savings potential
  • Shipping cost comparison
  • Seller reliability notes

Data Storage

Store all monitoring data in a structured directory:

price-monitor-data/
├── monitors.json          # Active monitoring configurations
├── history/
│   ├── monitor-001.json   # Price history for each monitor
│   └── monitor-002.json
├── reports/
│   ├── daily-2026-04-06.md
│   └── weekly-2026-W14.md
└── alerts/
    └── alerts-2026-04-06.json

History Entry Format

Each price check creates a history entry:

{
  "timestamp": "2026-04-06T14:30:00Z",
  "price": 849.99,
  "original_price": 999.99,
  "currency": "USD",
  "in_stock": true,
  "seller": "Amazon",
  "shipping": "Free",
  "condition": "New",
  "coupon": null,
  "source_url": "https://..."
}

Advanced Features

Multi-Currency Support

When monitoring across regions, normalize prices to the user's preferred currency using current exchange rates. Always show both the original and converted prices.

Competitor Intelligence Mode

For business users monitoring competitor pricing:

  1. Track competitor product catalog changes (new products, discontinued items)
  2. Monitor pricing strategy shifts (frequent sales vs. everyday low price)
  3. Generate competitive positioning reports
  4. Alert on significant competitor price moves

Deal Aggregation

Combine multiple data sources to find the best overall deal:

  • Base price across retailers
  • Available coupons and promo codes (search for "[product] coupon code [year]")
  • Cashback opportunities
  • Credit card rewards optimization
  • Bundle deals and accessories

Error Handling

  • If a page fails to load, retry up to 3 times with exponential backoff
  • If price extraction fails (page layout changed), flag the monitor as "needs attention"
  • If an API returns errors, log the error and continue with other monitors
  • Always validate extracted prices (not $0, not absurdly high, within 200% of last known price)
  • If a product page returns 404, mark as "possibly discontinued" and alert user

Integration Points

This skill works well with:

  • Scheduled tasks — Set up recurring price checks using the schedule skill
  • Slack/Email — Send alerts to Slack channels or email via connected MCPs
  • Spreadsheets — Export price history to CSV/XLSX for further analysis
  • Dashboards — Build HTML dashboards showing all monitored items

Example Interactions

Example 1: Simple Price Watch User: "Watch this laptop for me and let me know if it drops below $1200" → Set up a single product monitor with target price alert at $1200

Example 2: Multi-Retailer Comparison User: "Find me the best deal on AirPods Pro 2 across all major retailers" → Search Amazon, Best Buy, Walmart, Target; build comparison table; set up ongoing monitoring

Example 3: Competitor Pricing Analysis User: "Track how our competitor prices their SaaS plans and alert me when they change" → Set up multiple competitor page monitors; generate weekly competitive pricing report

Example 4: Market Data Tracking User: "Monitor gold prices and alert me when it drops below $2000/oz" → Set up API-based monitor for commodity prices with threshold alert

Korean Market Support (한국 시장 지원)

For Korean e-commerce monitoring:

  • Supports Coupang, Naver Shopping, 11st, G-Market, Auction
  • Korean Won (KRW) as base currency option
  • Korean-language alert generation
  • 네이버 최저가 비교 integration
  • 쿠팡 로켓배송 availability tracking

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

84.5%
按下载量换算931

安全审计

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操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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