---
name: analytics-16e6b211562b
description: "Performance attribution, trade analytics, and strategy optimization"
emoji: "📊"
---

# Analytics - Complete API Reference

Analyze trading performance with attribution by edge source, time-of-day analysis, and optimization insights.

---

## Chat Commands

### Performance Overview

```
/analytics                          Performance summary
/analytics today                    Today's performance
/analytics week                     Weekly breakdown
/analytics month                    Monthly breakdown
```

### Attribution

```
/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
```

### Time Analysis

```
/analytics best-times               Best trading hours
/analytics by-hour                  Hourly performance
/analytics by-day                   Day of week analysis
```

### Edge Analysis

```
/analytics edge-decay               How edge decays over time
/analytics edge-buckets             Performance by edge size
/analytics liquidity                Performance by liquidity
```

---

## TypeScript API Reference

### Create Analytics Service

```typescript
import { createAnalyticsService } from 'clodds/analytics';

const analytics = createAnalyticsService({
  // Data source
  tradesDb: './trades.db',

  // Time zone
  timezone: 'America/New_York',
});
```

### Performance Summary

```typescript
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}`);
```

### Attribution by Edge Source

```typescript
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)
```

### Time-of-Day Analysis

```typescript
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}`);
}
```

### Day-of-Week Analysis

```typescript
const daily = await analytics.getDayOfWeekPerformance();

for (const day of daily) {
  console.log(`${day.name}: $${day.pnl} (${day.trades} trades, ${day.winRate}% win)`);
}
```

### Edge Decay Analysis

```typescript
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
```

### Edge Size Buckets

```typescript
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}%`);
}
```

### Liquidity Analysis

```typescript
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}`);
}
```

### Execution Quality

```typescript
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}%`);
```

### Platform Comparison

```typescript
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(', ')}`);
}
```

### Export Report

```typescript
// 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',
});
```

---

## Attribution Categories

| 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 |

---

## Key Metrics

| 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 |

---

## Best Practices

1. **Review weekly** — Catch problems early
2. **Track attribution** — Know where profits come from
3. **Optimize timing** — Trade your best hours
4. **Monitor edge decay** — Don't hold too long
5. **Check execution** — Slippage kills edge


---
Source attribution: alsk1992
Original project: https://github.com/alsk1992/CloddsBot/blob/c930628c47a4a745f497e29035a3b64622f97cc7/src/skills/bundled/analytics/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 alsk1992

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: alsk1992
Original project: https://github.com/alsk1992/CloddsBot/blob/c930628c47a4a745f497e29035a3b64622f97cc7/src/skills/bundled/analytics/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Marketing
Roles: Data Analyst, Growth Marketer, Marketing Analyst
Specialties: API
Tools: Clodds
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: d8ab9a179ac120f0f93fdeac0f02509c386f9b99ddd9bc8abe500414685a6ceb