👀MAIGA KOL Alpha

MAIGA KOL Alpha transforms X mentions into actionable crypto intelligence by analyzing KOLs' on-chain wallet activities and delivering real-time trading insights.

Alpha Intelligence

Professional-grade P&L analytics with AI-powered pattern recognition using GPT-4 and retweet-gated insights.

System Capabilities

  • 30–90s Response Time

  • 10+ Wallets Per KOL

  • 50+ Metrics Per Analysis

  • 99.5% Uptime Target


X Monitoring

Intelligent Polling Strategy MAIGA KOL Alpha operates through @maigaxbt with sophisticated anti-detection mechanisms:

Component
Frequency
Randomization
Purpose

Mention Check

1–3 minutes

±60 seconds

Avoid pattern detection

Response Delay

30–90 seconds

Human-like

Natural flow

Session Rotation

Every 100 queries

3 backup sessions

Rate limit management

Multi-Source Data Collection

  • Search API: Queries "@maigaxbt" for public mentions

  • Mentions Timeline: Direct @mentions in notifications

  • All Notifications: Includes quotes, replies, and indirect mentions


KOL Identification

Intent Classification with GPT-4.1 Each mention is intelligently classified with confidence scoring:

  • KOL Analysis → “yo @maigaxbt what’s @blknoiz06 cooking?”

  • Token Analysis → “@maigaxbt thoughts on $PEPE?”

  • Unknown → Unclear intent or spam (~2% of requests)

Entity Resolution Pipeline X Handle → Arkham Entity ID → Wallet Addresses → Chain Classification

Steps:

  1. Cache Check (24-hour validity, ~60% hit rate)

  2. Arkham Query (entity + prediction fallback)

  3. Classification (Ethereum, Solana, multi-chain with 5–10+ wallets)


Wallet Analytics

Multi-Provider Data Aggregation

Provider
Data Type
Cache Duration
Coverage

Arkham Intelligence

Holdings, transfers, history

24 hours

All major chains

Cielo Finance

P&L, win rates, trade history

3 hours

All major chains

Wallet Analytics

Aggregated metrics

3 hours

All data points

Portfolio Composition Analysis

  • Token balances and USD valuations

  • Portfolio allocation percentages

  • Chain distribution analysis

  • Concentration risk assessment

Example Portfolio:

  • Total Value: $2.45M

  • ANI (63.6%): $1.56M

  • WETH (18.2%): $447K

  • PEPE (8.4%): $206K

Trading Performance Metrics

  • Total P&L = Realized + Unrealized

  • ROI = (Total P&L ÷ Total Invested) × 100

Performance Categories

  • Alpha Generator → Win rate >70%, ROI >100%

  • Consistent Performer → Win rate >60%, positive P&L

  • Risk Taker → High volatility, mixed results

  • Bag Holder → Negative P&L, low win rate


AI Insight Generation

GPT-4.1 Prompt Engineering Dynamic templates generate insights based on performance metrics:

  • High Performance Signals:

    • P&L >100% → “alpha tsunami incoming”

    • Win Rate >70% → “sniper mode engaged”

    • Concentration → “ALL-IN on $TOKEN. Pure conviction.”

  • Risk Signals:

    • High Risk → “degen but dangerous”

    • Losses → “bags too heavy”

    • Rotation → “Dumping ETH, accumulating SOL”

Three-Part Takeaway Structure

  1. Position Analysis – largest holdings and strategy

  2. Market Impact – influence on prices

  3. Action Item – what followers should watch for

Example Output:

  • 63% in $ANI shows massive conviction play

  • Their buys move charts, their sells can nuke them

  • Watch for rotation signals when profits start


Access Control

Retweet-Based Unlock Mechanism Social proof powers viral distribution:

  • 0 Retweets → Locked (teaser only)

  • 1+ Retweets → Globally unlocked, full dashboard view


Key Insights for Users

  • Consistent Win Rate → >65% success across 100+ trades

  • Significant P&L → $100K+ in realized profits

  • Active Trading → New transactions in last 7 days

  • Smart Positioning → Early entries in winning tokens

Interpretation Guide

  • “Sniper mode” → Exceptional win rate (>70%)

  • “All-in conviction” → >60% concentrated bet

  • “Rotation alert” → Switching sectors

  • “Bag warning” → Losing positions held too long

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