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- alsk1992/CloddsBot
- 최근 소스 활동
- 2026년 2월 10일 15:14
- 감지된 SKILL.md 언어
- 영어
- 스타
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설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/alsk1992/CloddsBot --skill analytics명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | analytics |
| description | Performance attribution, trade analytics, and strategy optimization |
| emoji | 📊 |
Analyze trading performance with attribution by edge source, time-of-day analysis, and optimization insights.
/analytics Performance summary
/analytics today Today's performance
/analytics week Weekly breakdown
/analytics month Monthly breakdown
/analytics attribution P&L by edge source
/analytics by-platform P&L by platform
/analytics by-category P&L by market category
/analytics by-strategy P&L by strategy
/analytics best-times Best trading hours
/analytics by-hour Hourly performance
/analytics by-day Day of week analysis
/analytics edge-decay How edge decays over time
/analytics edge-buckets Performance by edge size
/analytics liquidity Performance by liquidity
import { createAnalyticsService } from 'clodds/analytics';
const analytics = createAnalyticsService({
// Data source
tradesDb: './trades.db',
// Time zone
timezone: 'America/New_York',
});
const summary = await analytics.getSummary({
period: 'month',
// or: from: '2024-01-01', to: '2024-01-31'
});
console.log('=== Performance ===');
console.log(`Total P&L: $${summary.totalPnl}`);
console.log(`Win Rate: ${summary.winRate}%`);
console.log(`Profit Factor: ${summary.profitFactor}`);
console.log(`Sharpe Ratio: ${summary.sharpeRatio}`);
console.log(`Total Trades: ${summary.totalTrades}`);
console.log(`Avg Trade: $${summary.avgTrade}`);
console.log(`Best Trade: $${summary.bestTrade}`);
console.log(`Worst Trade: $${summary.worstTrade}`);
const attribution = await analytics.getAttribution('edgeSource');
for (const source of attribution) {
console.log(`${source.name}:`);
console.log(` P&L: $${source.pnl}`);
console.log(` Trades: ${source.trades}`);
console.log(` Win Rate: ${source.winRate}%`);
console.log(` Contribution: ${source.contribution}%`);
}
// Example sources:
// - price_lag (stale prices)
// - liquidity_gap (thin orderbooks)
// - information (news/events)
// - model_edge (external models)
// - combinatorial (arbitrage)
const hourly = await analytics.getHourlyPerformance();
console.log('Best Hours:');
for (const hour of hourly.slice(0, 3)) {
console.log(` ${hour.hour}:00 - Win: ${hour.winRate}%, Avg: $${hour.avgPnl}`);
}
console.log('Worst Hours:');
for (const hour of hourly.slice(-3)) {
console.log(` ${hour.hour}:00 - Win: ${hour.winRate}%, Avg: $${hour.avgPnl}`);
}
const daily = await analytics.getDayOfWeekPerformance();
for (const day of daily) {
console.log(`${day.name}: $${day.pnl} (${day.trades} trades, ${day.winRate}% win)`);
}
const decay = await analytics.getEdgeDecay();
console.log('Edge Decay (how fast edge disappears):');
for (const bucket of decay) {
console.log(` ${bucket.holdTime}: ${bucket.avgReturn}% return`);
}
// Shows optimal hold time before edge decays
const edgeBuckets = await analytics.getEdgeBuckets();
for (const bucket of edgeBuckets) {
console.log(`Edge ${bucket.min}-${bucket.max}%:`);
console.log(` Trades: ${bucket.trades}`);
console.log(` Win Rate: ${bucket.winRate}%`);
console.log(` Avg P&L: $${bucket.avgPnl}`);
console.log(` Realized Edge: ${bucket.realizedEdge}%`);
}
const liquidity = await analytics.getLiquidityAnalysis();
for (const bucket of liquidity) {
console.log(`${bucket.name} liquidity:`);
console.log(` Trades: ${bucket.trades}`);
console.log(` Avg Slippage: ${bucket.avgSlippage}%`);
console.log(` Fill Rate: ${bucket.fillRate}%`);
console.log(` Avg P&L: $${bucket.avgPnl}`);
}
const execution = await analytics.getExecutionQuality();
console.log('=== Execution Quality ===');
console.log(`Avg Slippage: ${execution.avgSlippage}%`);
console.log(`Fill Rate: ${execution.fillRate}%`);
console.log(`Avg Fill Time: ${execution.avgFillTimeMs}ms`);
console.log(`Partial Fills: ${execution.partialFillRate}%`);
console.log(`Rejected Orders: ${execution.rejectionRate}%`);
const platforms = await analytics.getPlatformComparison();
for (const platform of platforms) {
console.log(`${platform.name}:`);
console.log(` P&L: $${platform.pnl}`);
console.log(` Win Rate: ${platform.winRate}%`);
console.log(` Avg Slippage: ${platform.avgSlippage}%`);
console.log(` Best For: ${platform.strengths.join(', ')}`);
}
// Generate PDF report
await analytics.exportReport({
format: 'pdf',
period: 'month',
include: ['summary', 'attribution', 'charts'],
outputPath: './reports/january-2024.pdf',
});
// Export raw data
await analytics.exportData({
format: 'csv',
period: 'month',
outputPath: './data/january-trades.csv',
});
| Category | Description |
|---|---|
| Edge Source | Where the edge came from |
| Platform | Which platform traded on |
| Category | Market category (politics, crypto) |
| Strategy | Which strategy generated trade |
| Time | Hour/day of trade |
| Size | Trade size bucket |
| Metric | Good Value | Description |
|---|---|---|
| Win Rate | > 50% | Percent of winning trades |
| Profit Factor | > 1.5 | Gross profit / gross loss |
| Sharpe Ratio | > 1.0 | Risk-adjusted returns |
| Realized Edge | > 0 | Actual vs expected edge |
| Fill Rate | > 95% | Orders fully filled |