SII-leiyuandClaude Opus 4.6
3de7cd3373
- Redesign README with polished badges, structured report preview, collapsible config sections - Update sample report to match actual 7-step deep analysis output (trade signal, event positions, long/short, info gap, historical pattern, asymmetry score) - Add new whale trade report (US x Iran diplomatic meeting) - Update signals database with latest data Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
526 lines
24 KiB
Markdown
526 lines
24 KiB
Markdown
<div align="center">
|
||
|
||
# 🐋 Polymarket Whale Watcher
|
||
|
||
**AI-Powered Whale Trade Intelligence for Polymarket Prediction Markets**
|
||
|
||
[](https://www.python.org/downloads/)
|
||
[](LICENSE)
|
||
[](https://docs.polymarket.com/)
|
||
[](https://aistudio.google.com/)
|
||
|
||
<br/>
|
||
|
||
**Real-time monitoring** of 700+ markets · **14 autonomous research tools** · **Multi-step deep analysis** · **Signal accuracy tracking**
|
||
|
||
<br/>
|
||
|
||
[Quick Start](#-quick-start) | [How It Works](#-how-it-works) | [Sample Report](#-sample-report) | [Configuration](#%EF%B8%8F-configuration) | [Dashboard](#-dashboard)
|
||
|
||
---
|
||
|
||
<img width="720" alt="pipeline" src="https://img.shields.io/badge/Tiered_Markets_(700+)→Whale_Detection→Anomaly_Scoring→LLM_Investigation→Signal_Tracking-000?style=flat-square&labelColor=000"/>
|
||
|
||
</div>
|
||
|
||
<br/>
|
||
|
||
## What It Does
|
||
|
||
Whale Watcher continuously monitors **700+ active Polymarket markets** across three volume tiers, detects large trades with anomalous patterns, and deploys an LLM agent with **14 autonomous research tools** to conduct multi-step deep investigations. Each whale trade undergoes a structured 7-step analysis pipeline — from trader profiling and cross-market position mapping to information gap assessment — producing an **Information Asymmetry Score** that quantifies the likelihood of non-public information advantage.
|
||
|
||
<br/>
|
||
|
||
## Live Demo
|
||
|
||
<details open>
|
||
<summary><strong>Terminal Output</strong> — Real-time whale detection and analysis</summary>
|
||
|
||
<br/>
|
||
|
||
```
|
||
$ python -m src.main run
|
||
|
||
============================================================
|
||
WHALE WATCHER STARTED
|
||
============================================================
|
||
Monitoring: 765 markets
|
||
Interval: 10 seconds
|
||
Min Trade Size: $10,000 USD
|
||
Price Range: 0.1 - 0.9
|
||
============================================================
|
||
|
||
Tiered monitoring: Tier1=8 (>500K), Tier2=198 (>10K), Tier3=559 (>1K)
|
||
|
||
[23:41:12] WHALE TRADE DETECTED!
|
||
Amount: $9,600.00 USDC
|
||
Side: BUY Yes
|
||
Price: 0.7142
|
||
Market: US x Iran diplomatic meeting by June 30, 2026?
|
||
|
||
Generating analysis report...
|
||
Round 1: LLM requested 3 tool call(s)
|
||
→ search_web("US Iran diplomatic meeting June 2026")
|
||
→ search_twitter("US Iran meeting diplomacy")
|
||
→ get_wallet_transfers("0xceza...rn132")
|
||
Round 2: LLM requested 2 tool call(s)
|
||
→ search_web("Islamabad Iran talks Witkoff April 2026")
|
||
→ search_twitter("POLYMARKET Iran meeting odds fading")
|
||
Round 3: LLM requested 1 tool call(s)
|
||
→ search_web("Iran FM Araghchi 3 phase deal proposal")
|
||
|
||
Analysis complete after 3 round(s)
|
||
Information Asymmetry Score: 0.32 (LOW)
|
||
Trader Credibility: MEDIUM (#1733, PnL: $84K)
|
||
Verdict: Thesis continuation / loss recovery — HOLD/PASS
|
||
Report saved: reports/20260504/...
|
||
```
|
||
|
||
</details>
|
||
|
||
<br/>
|
||
|
||
<details>
|
||
<summary><strong>Sample Report</strong> — 7-Step Deep Analysis (click to expand)</summary>
|
||
|
||
<br/>
|
||
|
||
Each whale trade generates a comprehensive markdown report with structured multi-step analysis:
|
||
|
||
> **Full example**: [docs/examples/sample_report.md](docs/examples/sample_report.md)
|
||
|
||
#### Report Structure
|
||
|
||
```
|
||
======================================================================
|
||
# Whale Trade Analysis Report
|
||
======================================================================
|
||
|
||
┌─ Trade Summary ─────────────────────────────────────────────────────┐
|
||
│ Market, trade size, direction, price, odds, time, trader rank │
|
||
└─────────────────────────────────────────────────────────────────────┘
|
||
|
||
┌─ Step 2: Trade Signal Analysis ─────────────────────────────────────┐
|
||
│ Trader profile: rank, PnL, avg size, large trade ratio │
|
||
│ Domain expertise detection, trade timing analysis │
|
||
└─────────────────────────────────────────────────────────────────────┘
|
||
|
||
┌─ Step 3: Event-Related Position Analysis ───────────────────────────┐
|
||
│ Cross-market positions, roll-forward detection │
|
||
│ Loss recovery patterns, hedge identification │
|
||
└─────────────────────────────────────────────────────────────────────┘
|
||
|
||
┌─ Step 4: Market Long/Short Analysis ────────────────────────────────┐
|
||
│ Top 5 bulls & bears with rankings and PnL │
|
||
│ Smart money consensus assessment │
|
||
└─────────────────────────────────────────────────────────────────────┘
|
||
|
||
┌─ Step 5: Information Gap Analysis ──────────────────────────────────┐
|
||
│ Public information audit (web, Twitter, Telegram) │
|
||
│ Market pricing efficiency check │
|
||
│ Non-public information evidence search │
|
||
└─────────────────────────────────────────────────────────────────────┘
|
||
|
||
┌─ Step 6: Historical Pattern ────────────────────────────────────────┐
|
||
│ Trader's past bets on related events │
|
||
│ Strategy pattern recognition (laddering, hedging, etc.) │
|
||
└─────────────────────────────────────────────────────────────────────┘
|
||
|
||
┌─ Step 7: Information Asymmetry Assessment ──────────────────────────┐
|
||
│ Score (0–1), trader credibility, evidence, reasoning │
|
||
│ Multi-factor summary table with signal strength │
|
||
│ Recommended action: BUY / HOLD / PASS │
|
||
└─────────────────────────────────────────────────────────────────────┘
|
||
```
|
||
|
||
#### Example Summary Table
|
||
|
||
| Factor | Assessment | Signal |
|
||
|--------|-----------|--------|
|
||
| Trader Rank/PnL | Rank #1733, $84K PnL | Moderate |
|
||
| Trade Size vs. Normal | ~$9.6K vs. avg $10K | Routine — neutral |
|
||
| Related Position | Heavy loser on May 15 market (-$6.5K) | Suppresses signal |
|
||
| Domain Expertise | Iran geopolitics specialist | Supportive |
|
||
| Public Info Coverage | Extensive public news | Reduces asymmetry |
|
||
| Smart Money Bulls | Rank #278 also long | Modest support |
|
||
| **Overall** | **Thesis continuation, not insider signal** | **Low-Medium** |
|
||
|
||
</details>
|
||
|
||
<br/>
|
||
|
||
<details>
|
||
<summary><strong>Daily Briefing</strong> — Automated intelligence summary</summary>
|
||
|
||
<br/>
|
||
|
||
Daily briefings are generated at **10:00 AM local time** and emailed automatically.
|
||
|
||
> **Full example**: [docs/examples/sample_briefing.md](docs/examples/sample_briefing.md)
|
||
|
||
**Includes:**
|
||
- High-confidence signals (IAS >= 60%) with full analysis summaries
|
||
- Fallback: top 5 signals by score if none reach the threshold
|
||
- Abnormal price volatility alerts
|
||
- Historical signal performance — win rate and ROI by confidence tier
|
||
|
||
</details>
|
||
|
||
<br/>
|
||
|
||
---
|
||
|
||
## Quick Start
|
||
|
||
### One-Click Setup
|
||
|
||
```bash
|
||
git clone https://github.com/chaoleiyv/polymarket-whale-watcher.git
|
||
cd polymarket-whale-watcher
|
||
chmod +x setup.sh && ./setup.sh
|
||
```
|
||
|
||
The setup script will:
|
||
1. Check Python 3.10+ is installed
|
||
2. Create a virtual environment
|
||
3. Install all dependencies
|
||
4. Create `.env` from template
|
||
|
||
Then add your API key and start:
|
||
|
||
```bash
|
||
# Add your Gemini API key (the only required key)
|
||
echo "GEMINI_API_KEY=your_key_here" >> .env
|
||
|
||
# Activate the environment and run
|
||
source .venv/bin/activate
|
||
python -m src.main run
|
||
```
|
||
|
||
> **Get a free Gemini API key**: https://aistudio.google.com/apikey
|
||
|
||
### Docker
|
||
|
||
```bash
|
||
docker build -t whale-watcher .
|
||
docker run --env-file .env -v ./data:/app/data -v ./reports:/app/reports whale-watcher
|
||
```
|
||
|
||
---
|
||
|
||
## How It Works
|
||
|
||
```mermaid
|
||
flowchart LR
|
||
A[Polymarket API] --> B[Market Fetcher]
|
||
B --> C[700+ Tiered Markets]
|
||
C --> D[Trade Monitor]
|
||
D --> E{Whale\nTrade?}
|
||
E -->|No| D
|
||
E -->|Yes| F[Anomaly Detector]
|
||
F --> G{Score >= 0.65?}
|
||
G -->|No| D
|
||
G -->|Yes| H[LLM Analyzer]
|
||
H --> I[14 Research Tools]
|
||
I --> J[Signal + Report]
|
||
J --> K[Resolution Tracker]
|
||
K --> L[Dashboard + Email]
|
||
```
|
||
|
||
### Pipeline
|
||
|
||
| Stage | What Happens |
|
||
|-------|-------------|
|
||
| **1. Market Selection** | Fetches all active markets from Polymarket Gamma API, classifies into 3 tiers by 24h volume, adds token launch markets. Refreshes every 15 minutes. |
|
||
| **2. Trade Monitoring** | Parallel async tasks per market (700+), polls official Polymarket data-api for new taker BUY trades, deduplicates by transaction hash. Connection pool: 50 connections, 120s timeout. |
|
||
| **3. Whale Pre-filter** | Price range 0.10–0.90, $5K hard floor, dynamic threshold scaled by volume ($5K–$100K), conviction check (must pay above mid), resolution window 6h–90d. |
|
||
| **4. Anomaly Scoring** | 5-factor model (max 1.0): base confidence (0.50) + premium ratio (0.20) + signal cleanliness (0.10) + depth ratio (0.10) + cluster tier (0.10). Threshold: >= 0.65. |
|
||
| **5. LLM Investigation** | Builds rich context (trade + trader profile + event positions + market top holders + historical signals). LLM autonomously selects tools for up to 3 rounds. Produces structured 7-step analysis with information asymmetry score (0–1). |
|
||
| **6. Signal Tracking** | Resolution tracker checks every 30 min, validates signal correctness, computes theoretical ROI. Daily briefings at 10:00 AM, emailed to recipients. |
|
||
|
||
---
|
||
|
||
## Features
|
||
|
||
| Feature | Description |
|
||
|---------|-------------|
|
||
| **Tiered Market Monitoring** | 700+ markets across 3 tiers: Tier1 (>$500K, 15s), Tier2 (>$10K, 60s), Tier3 (>$1K, 300s) |
|
||
| **5-Factor Anomaly Detection** | Premium ratio, signal cleanliness, depth ratio, cluster signals, base confidence |
|
||
| **7-Step Deep Analysis** | Trade signal → Event positions → Long/short mapping → Info gap → Historical pattern → Asymmetry score |
|
||
| **14 Autonomous Research Tools** | Web, Twitter, Telegram, crypto, DeFi, stocks, on-chain, legislation |
|
||
| **Cross-Market Position Analysis** | Detects roll-forwards, hedges, and loss recovery patterns across related markets |
|
||
| **Signal Accuracy Tracking** | Auto resolution checking every 30 min, win rate stats by confidence tier |
|
||
| **Daily Briefings** | 10:00 AM automated summary with high-confidence signals, emailed to recipients |
|
||
| **Real-time Email Alerts** | Instant notifications for high information-asymmetry signals (>= 60%) |
|
||
| **Web Dashboard** | FastAPI-based signal performance dashboard with ROI breakdowns |
|
||
|
||
### 14 LLM Research Tools
|
||
|
||
The LLM agent autonomously selects and chains these tools during its multi-round investigation:
|
||
|
||
| Category | Tools | Use Case |
|
||
|----------|-------|----------|
|
||
| **Social & Sentiment** | `search_twitter` · `search_telegram` · `search_web` | Public sentiment, insider chatter, news coverage |
|
||
| **Crypto & DeFi** | `get_crypto_price` · `get_crypto_market_overview` · `get_protocol_tvl` · `get_token_unlocks` · `get_protocol_revenue` | Token prices, TVL, unlocks, protocol health |
|
||
| **Financial Data** | `get_stock_price` · `get_stock_news` · `get_economic_data` | Equities, ETFs, macro indicators |
|
||
| **On-Chain** | `get_wallet_transfers` · `get_contract_info` | Wallet activity, contract deployments |
|
||
| **Legislation** | `get_bill_status` · `get_recent_legislation` | US bills, regulatory actions |
|
||
|
||
---
|
||
|
||
## Sample Report
|
||
|
||
Every whale trade produces a structured multi-step report. Here's a condensed view:
|
||
|
||
```
|
||
======================================================================
|
||
# Whale Trade Analysis Report
|
||
======================================================================
|
||
|
||
Trade Summary
|
||
Market: US x Iran diplomatic meeting by June 30, 2026?
|
||
Size: $9,600 USDC | Direction: BUY Yes (71.4%) | Trader: #1733
|
||
|
||
Step 2: Trade Signal Analysis
|
||
→ Mid-tier trader, $84K PnL, Iran geopolitics specialist
|
||
→ Trade size ($9.6K) matches avg ($10K) — routine, not exceptional
|
||
|
||
Step 3: Event-Related Position Analysis ← KEY FINDING
|
||
→ Losing -$6,508 on earlier "May 15 meeting" market (15.5% odds)
|
||
→ This trade is a thesis roll-forward, not a fresh insider bet
|
||
|
||
Step 4: Market Long/Short Analysis
|
||
→ Biggest Yes holder is a chronic loser (PnL: -$5.5M) — red flag
|
||
→ One elite trader (Rank #278) also long — modest support
|
||
|
||
Step 5: Information Gap Analysis
|
||
→ All supporting info widely reported in mainstream media
|
||
→ Market at 69.5% — already fairly priced
|
||
|
||
Step 6: Historical Pattern
|
||
→ "Timeline ladder" strategy across multiple Iran-related deadlines
|
||
|
||
Step 7: Information Asymmetry Assessment
|
||
→ Score: 0.32 (LOW) | Credibility: MEDIUM
|
||
→ Verdict: Thesis continuation / loss recovery — HOLD/PASS
|
||
|
||
======================================================================
|
||
```
|
||
|
||
> **Full report**: [docs/examples/sample_report.md](docs/examples/sample_report.md)
|
||
|
||
---
|
||
|
||
## Configuration
|
||
|
||
Copy `.env.example` to `.env` and configure:
|
||
|
||
### Required
|
||
|
||
| Variable | Description | Get It |
|
||
|----------|-------------|--------|
|
||
| `GEMINI_API_KEY` | LLM API key for analysis | [Google AI Studio](https://aistudio.google.com/apikey) |
|
||
|
||
### Optional (enhances analysis quality)
|
||
|
||
<details open>
|
||
<summary><strong>Data Source API Keys</strong></summary>
|
||
|
||
| Variable | Description | Get It |
|
||
|----------|-------------|--------|
|
||
| `TAVILY_API_KEY` | Web search (primary) | [tavily.com](https://tavily.com) |
|
||
| `SERPER_API_KEY` | Web search (fallback) | [serper.dev](https://serper.dev) |
|
||
| `TWITTER_API_KEY` | Twitter sentiment search | [twitterapi.io](https://twitterapi.io) |
|
||
| `POLYGON_API_KEY` | Stock/ETF/forex data | [polygon.io](https://polygon.io) |
|
||
| `FRED_API_KEY` | Economic indicators | [FRED](https://fred.stlouisfed.org/docs/api/api_key.html) |
|
||
| `ETHERSCAN_API_KEY` | On-chain wallet analysis (Polygon V2) | [etherscan.io](https://etherscan.io/apis) |
|
||
| `CONGRESS_API_KEY` | US legislation data | [congress.gov](https://api.congress.gov/) |
|
||
| `TELEGRAM_API_ID` / `TELEGRAM_API_HASH` | Telegram channel monitoring | [my.telegram.org](https://my.telegram.org) |
|
||
|
||
</details>
|
||
|
||
<details>
|
||
<summary><strong>LLM Settings</strong></summary>
|
||
|
||
| Variable | Default | Description |
|
||
|----------|---------|-------------|
|
||
| `LLM_MODEL` | `gemini-3-flash-preview` | Model name (any OpenAI-compatible) |
|
||
| `LLM_BASE_URL` | Google AI endpoint | OpenAI-compatible API base URL |
|
||
| `LLM_TEMPERATURE` | `0` | LLM temperature |
|
||
|
||
</details>
|
||
|
||
<details>
|
||
<summary><strong>Whale Detection Tuning</strong></summary>
|
||
|
||
| Variable | Default | Description |
|
||
|----------|---------|-------------|
|
||
| `MIN_TRADE_SIZE_USD` | `10000` | Minimum trade size to consider |
|
||
| `MIN_PRICE` / `MAX_PRICE` | `0.10` / `0.90` | Price range filter |
|
||
| `FETCH_INTERVAL_SECONDS` | `10` | Default polling interval |
|
||
|
||
</details>
|
||
|
||
<details>
|
||
<summary><strong>Tiered Market Monitoring</strong></summary>
|
||
|
||
| Variable | Default | Description |
|
||
|----------|---------|-------------|
|
||
| `FULL_MARKET_SCAN` | `true` | Enable tiered monitoring (all active markets) |
|
||
| `TIER1_VOLUME_MIN` | `500000` | Tier 1 volume threshold |
|
||
| `TIER2_VOLUME_MIN` | `10000` | Tier 2 volume threshold |
|
||
| `TIER3_VOLUME_MIN` | `1000` | Tier 3 volume threshold |
|
||
| `TIER1_POLL_INTERVAL` | `15` | Tier 1 polling interval (seconds) |
|
||
| `TIER2_POLL_INTERVAL` | `60` | Tier 2 polling interval (seconds) |
|
||
| `TIER3_POLL_INTERVAL` | `300` | Tier 3 polling interval (seconds) |
|
||
|
||
</details>
|
||
|
||
<details>
|
||
<summary><strong>Email Alerts</strong></summary>
|
||
|
||
| Variable | Default | Description |
|
||
|----------|---------|-------------|
|
||
| `EMAIL_ENABLED` | `false` | Enable email notifications |
|
||
| `EMAIL_SENDER` | — | Sender email address |
|
||
| `EMAIL_PASSWORD` | — | Sender email password (app password) |
|
||
| `EMAIL_RECIPIENT` | — | Comma-separated recipient emails |
|
||
|
||
</details>
|
||
|
||
---
|
||
|
||
## Commands
|
||
|
||
```bash
|
||
# Core
|
||
python -m src.main run [--debug] # Start monitoring
|
||
python -m src.main check-markets --limit 20 # View trending markets
|
||
|
||
# Analysis
|
||
python -m src.main test-analyze <market_id> # Test LLM on a specific market
|
||
|
||
# Reports
|
||
python -m src.main briefing --today # Generate today's briefing
|
||
python -m src.main briefing --date 2026-04-17 # Briefing for a specific date
|
||
|
||
# Dashboard
|
||
python -m src.main dashboard --port 8000 # Start web dashboard
|
||
|
||
# Maintenance
|
||
python -m src.main migrate # Migrate legacy JSON to SQLite
|
||
```
|
||
|
||
---
|
||
|
||
## Dashboard
|
||
|
||
```bash
|
||
python -m src.main dashboard
|
||
# Open http://localhost:8000
|
||
```
|
||
|
||
The dashboard shows:
|
||
- Overall signal statistics (total signals, win rate, avg ROI)
|
||
- Performance breakdown by confidence tier
|
||
- Top best/worst signals by theoretical ROI
|
||
- Paginated signal history
|
||
|
||
---
|
||
|
||
## Architecture
|
||
|
||
```
|
||
┌──────────────────────────────┐
|
||
│ Polymarket Gamma API │
|
||
│ (all active markets) │
|
||
└──────────────┬───────────────┘
|
||
│
|
||
┌──────────────▼───────────────┐
|
||
│ Market Fetcher │
|
||
│ Tier1: >$500K (15s poll) │
|
||
│ Tier2: >$10K (60s poll) │
|
||
│ Tier3: >$1K (300s poll) │
|
||
└──────────────┬───────────────┘
|
||
│
|
||
┌────────────────────▼────────────────────┐
|
||
│ Trade Monitor (async, 700+) │
|
||
│ Official Polymarket data-api │
|
||
│ Per-market parallel tasks │
|
||
│ Pool: 50 connections, 120s timeout │
|
||
└────────────────────┬────────────────────┘
|
||
│
|
||
┌────────────────────▼────────────────────┐
|
||
│ Pre-filter + Scoring │
|
||
│ $5K+ size, 0.10-0.90 price, conviction │
|
||
│ 5-factor anomaly score >= 0.65 │
|
||
└────────────────────┬────────────────────┘
|
||
│
|
||
┌────────────────────▼────────────────────┐
|
||
│ LLM Analyzer — 7-Step Pipeline │
|
||
│ 14 tools · up to 3 rounds │
|
||
├──────────┬────────┬────────┬────────────┤
|
||
│ Twitter │ Web │ DeFi │ On-Chain │
|
||
│ Telegram │ Search │ Crypto │ Legislation│
|
||
└──────────┴───┬────┴────────┴────────────┘
|
||
│
|
||
┌──────────────▼─────────────────────────┐
|
||
│ Signal Storage (SQLite) │
|
||
│ → Resolution Tracker (every 30min) │
|
||
│ → Daily Briefing (10:00 AM + email) │
|
||
│ → Email Alerts (IAS >= 60%) │
|
||
│ → Dashboard (FastAPI) │
|
||
└────────────────────────────────────────┘
|
||
```
|
||
|
||
---
|
||
|
||
## Project Structure
|
||
|
||
```
|
||
src/
|
||
├── config/settings.py # Environment configuration (Pydantic)
|
||
├── models/ # Data models
|
||
│ ├── market.py # Market, TrendingMarket
|
||
│ ├── trade.py # TradeActivity, WhaleTrade, TraderRanking
|
||
│ ├── decision.py # TradeRecommendation, LLMDecision
|
||
│ └── anomaly_signal.py # AnomalySignal (stored signal)
|
||
├── services/ # Business logic
|
||
│ ├── market_fetcher.py # Polymarket Gamma API (tiered market selection)
|
||
│ ├── trade_monitor.py # Per-market parallel monitoring (official API)
|
||
│ ├── anomaly_detector.py # 5-factor anomaly scoring
|
||
│ ├── llm_analyzer.py # LLM with tool-use (14 tools, 3 rounds)
|
||
│ ├── tools.py # Tool registry
|
||
│ ├── resolution_tracker.py # Market resolution checking
|
||
│ ├── stats_engine.py # Performance statistics
|
||
│ ├── daily_briefing.py # Daily summary generation + email
|
||
│ ├── twitter_search.py # Twitter API search
|
||
│ ├── telegram_search.py # Telegram channel monitoring
|
||
│ ├── web_search.py # Tavily/Serper/DuckDuckGo search
|
||
│ ├── coingecko.py # Crypto prices and market data
|
||
│ ├── defillama.py # DeFi TVL, revenue, token unlocks
|
||
│ ├── fred.py # FRED macroeconomic data
|
||
│ ├── polygon.py # Stock/ETF prices and news
|
||
│ ├── etherscan.py # On-chain data (Polygon, Etherscan V2)
|
||
│ └── congress.py # US legislation data
|
||
├── prompts/ # LLM system prompts
|
||
│ ├── whale_analyzer.py # Whale trade analysis prompt
|
||
│ └── volatility_analyzer.py # Price volatility analysis prompt
|
||
├── db/database.py # SQLite signal storage
|
||
└── main.py # CLI entry point (Typer)
|
||
```
|
||
|
||
---
|
||
|
||
## Disclaimer
|
||
|
||
This system is for **research and educational purposes only**. Prediction market trading involves significant risk. The information asymmetry scores and analyses are AI-generated estimates — not financial advice. Always conduct your own research and verify independently before making any trading decisions.
|
||
|
||
---
|
||
|
||
<div align="center">
|
||
|
||
**MIT License** · Built with Polymarket API + Gemini
|
||
|
||
</div>
|