agentsclimarketplace

Case 00000

Skill knownasnaffy/prompthound/dataset/case_00000

A fast, offline static risk analysis CLI for AI agent skill files. Detects malicious instructions, steganographic payloads, and dangerous capability chains.

Install
npx -y skills add knownasnaffy/prompthound --skill case_00000

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What its author says it does

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Cryptocurrency market analysis for Bitcoin and Ethereum. Fetches 4h (24h) and 1d (30-day) data from Binance API, calculates technical indicators (RSI, SMAs, support/resistance), and provides bullish/bearish sentiment analysis with reasoning. Use when user asks for crypto market reports, BTC/ETH analysis, or daily market summaries.

SKILL.md

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Crypto Market Analyzer

This skill provides automated cryptocurrency market analysis for Bitcoin (BTC) and Ethereum (ETH).

What It Does

  • Fetches market data from Binance public API (no authentication required)
  • Analyzes 4-hour timeframe (last 24 hours)
  • Analyzes daily timeframe (last 30 days)
  • Calculates technical indicators:
    • RSI (Relative Strength Index, 14-period)
    • Simple Moving Averages (20-day and 50-day)
    • Support and resistance levels
    • Price change (24h and 7d)
  • Provides sentiment analysis (Bullish/Bearish/Neutral) with confidence level
  • Generates structured reports with reasoning

Usage

Generate Market Report

Run the analysis script:

python3 scripts/fetch_crypto_data.py

Output format (JSON):

{
  "BTCUSDT": {
    "indicators": {
      "current_price": 43250.50,
      "sma_20": 42800.00,
      "sma_50": 41500.00,
      "rsi": 58.3,
      "support": 42000.00,
      "resistance": 44000.00,
      "price_change_24h": 2.5,
      "price_change_7d": 5.8
    },
    "sentiment": {
      "sentiment": "Bullish (看涨)",
      "confidence": 0.75,
      "reasons": [
        "RSI (58.3) shows bullish momentum",
        "Price above both SMAs (20d and 50d) - bullish trend",
        "Strong 24h gain (2.50%) - bullish"
      ]
    },
    "timestamp": "2026-02-11T14:38:00"
  },
  "ETHUSDT": { ... }
}

Generate Human-Readable Report

To create a user-friendly report, use the JSON output and format it:

📊 加密货币市场分析报告
生成时间: 2026-02-11 14:38

## 比特币 (BTC)

💰 当前价格: $43,250.50
📈 24h涨跌: +2.5%
📊 7日涨跌: +5.8%

### 技术指标
- RSI (14): 58.3
- SMA 20: $42,800
- SMA 50: $41,500
- 支撑位: $42,000
- 阻力位: $44,000

### 市场判断
🎯 趋势: 看涨 (Bullish)
📊 置信度: 75%

📝 分析理由:
- RSI (58.3) 显示多头动能
- 价格位于20日和50日均线上方 - 上升趋势
- 24小时涨幅强劲 (2.50%) - 多头信号

## 以太坊 (ETH)
...

Scheduled Execution

This skill is designed for daily automated execution at 10:00 AM (UTC+8).

To schedule via OpenClaw cron:

# Create a cron job to run daily at 10:00 AM UTC+8
# This corresponds to 02:00 UTC

The cron job should:

  1. Execute the analysis script
  2. Parse the JSON output
  3. Format a human-readable report
  4. Send the report to the user via messaging channel

Technical Details

Data Source

  • API: Binance Public API
  • Endpoint: /api/v3/klines
  • Rate Limits: 1200 request weight per minute (well within limits)
  • No Authentication Required: Public market data

Timeframes

  • 4h: 6 candles (24 hours of data)
  • 1d: 30 candles (30 days of data)

Indicators Explained

  • RSI: Momentum oscillator (0-100). <30 = oversold, >70 = overbought
  • SMA 20/50: Trend indicators. Price > both SMAs = bullish
  • Support/Resistance: Recent low/high averages
  • Price Change: Percentage change over specified period

Sentiment Logic

Sentiment is determined by combining multiple signals:

  1. RSI position (oversold/overbought/momentum)
  2. Price vs moving averages (trend direction)
  3. Recent price changes (momentum strength)

Each signal contributes to a bullish/bearish score, which determines:

  • Overall sentiment (Bullish/Bearish/Neutral)
  • Confidence level (0.3 to 0.9)
  • Detailed reasoning

Extending the Skill

To add more cryptocurrencies:

Edit scripts/fetch_crypto_data.py and modify the symbols list:

symbols = ["BTCUSDT", "ETHUSDT", "SOLUSDT", "ADAUSDT"]

To add more indicators:

Extend the calculate_technical_indicators() function with additional calculations (MACD, Bollinger Bands, etc.).

To customize sentiment logic:

Modify the analyze_sentiment() function to adjust weighting and thresholds.

Keep looking

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