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Analytics

CommunityPopular
alsk1992
analytics

Performance attribution, trade analytics, and strategy optimization

Overview

Publisheralsk1992
RepositoryCloddsBot
Skill nameanalytics
Stars
2.8K
Forks
336
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by alsk1992 on GitHub. Read the source before you install it.

Installation

Install the Analytics AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/alsk1992/CloddsBot.git /tmp/CloddsBot
mkdir -p .claude/skills
cp -r /tmp/CloddsBot/src/skills/bundled/analytics .claude/skills/analytics
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Analytics in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Analytics on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Analytics is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

CategoryDescription
Edge SourceWhere the edge came from
PlatformWhich platform traded on
CategoryMarket category (politics, crypto)
StrategyWhich strategy generated trade
TimeHour/day of trade
SizeTrade size bucket

Key Metrics

MetricGood ValueDescription
Win Rate> 50%Percent of winning trades
Profit Factor> 1.5Gross profit / gross loss
Sharpe Ratio> 1.0Risk-adjusted returns
Realized Edge> 0Actual 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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Analytics AI skill do?

Performance attribution, trade analytics, and strategy optimization

Why use Analytics on TypingMind?

Because you install it once and use it with any model. Analytics is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Analytics in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/alsk1992/CloddsBot/tree/main/src/skills/bundled/analytics. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Analytics?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Analytics?

As many as you like. As long as a model supports skills, you can use Analytics with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Analytics AI skill free?

Yes. It is published on GitHub by alsk1992 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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