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X Intelligence CLI — search, monitor, analyze, and engage on X/Twitter. TypeScript + Bun. AI agent skill.
Polymarket 套利 | Polymarket Arbitrage. 预测市场套利机会 | Prediction market arbitrage opportunities. 自动发现价格差异 | Auto discover price differences. 触发词:Polymarket、预测市场、套利、arbitrage.
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
SkillHub CLI
skillhub install guohongbin-git/polymarket-arbitrage-cnInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
Find and execute arbitrage opportunities on Polymarket prediction markets.
Run a single scan to see current opportunities:
cd skills/polymarket-arbitrage
pip install requests beautifulsoup4
python scripts/monitor.py --once --min-edge 3.0
View results in polymarket_data/arbs.json
Monitor every 5 minutes and alert on new opportunities:
python scripts/monitor.py --interval 300 --min-edge 3.0
Stop with Ctrl+C
Each detected arbitrage includes:
Good opportunities:
math_arb_buy (safer)Type A: Buy All Outcomes (prob sum < 100%)
Type B: Sell All Outcomes (prob sum > 100%)
See references/arbitrage_types.md for detailed examples and strategies.
Same event priced differently across markets (not yet implemented - requires semantic matching).
Requires real-time orderbook data (homepage shows midpoints, not executable prices).
Scrape Polymarket homepage for active markets.
python scripts/fetch_markets.py --output markets.json --min-volume 50000
Returns JSON with market probabilities, volumes, and metadata.
Analyze markets for arbitrage opportunities.
python scripts/detect_arbitrage.py markets.json --min-edge 3.0 --output arbs.json
Accounts for:
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
# Polymarket Arbitrage Find and execute arbitrage opportunities on Polymarket prediction markets. ## Quick Start ### 1. Paper Trading (Recommended First Step) Run a single scan to see current opportunities: ```bash cd skills/polymarket-arbitrage pip install requests beautifulsoup4 python scripts/monitor.py --once --min-edge 3.0 ``` View results in `polymarket_data/arbs.json` ### 2. Continuous Monitoring Monitor every 5 minutes and alert on new opportunities: ```bash python scripts/monitor.py --interval 300 --min-edge 3.0 ``` Stop with `Ctrl+C` ### 3. Understanding Results Each detected arbitrage includes: - **net_profit_pct**: Edge after 2% fees - **risk_score**: 0-100, lower is better - **volume**: Market liquidity - **action**: What to do (buy/sell all outcomes) Good opportunities: - Net profit: 3-5%+ - Risk score: <50 - Volume: $1M+ - Type: `math_arb_buy` (safer) ## Arbitrage Types Detected ### Math Arbitrage (Primary Focus) **Type A: Buy All Outcomes** (prob sum < 100%) - Safest type - Guaranteed profit if executable - Example: 48% + 45% = 93% → 7% edge, ~5% net after fees **Type B: Sell All Outcomes** (prob sum > 100%) - Riskier (requires liquidity) - Need capital to collateralize - Avoid until experienced See `references/arbitrage_types.md` for detailed examples and strategies. ### Cross-Market Arbitrage Same event priced differently across markets (not yet implemented - requires semantic matching). ### Orderbook Arbitrage Requires real-time orderbook data (homepage shows midpoints, not executable prices). ## Scripts ### fetch_markets.py Scrape Polymarket homepage for active markets. ```bash python scripts/fetch_markets.py --output markets.json --min-volume 50000 ``` Returns JSON with market probabilities, volumes, and metadata. ### detect_arbitrage.py Analyze markets for arbitrage opportunities. ```bash python scripts/detect_arbitrage.py markets.json --min-edge 3.0 --output arbs.json ``` Accounts for: - 2% taker fees (per leg) -...
X Intelligence CLI — search, monitor, analyze, and engage on X/Twitter. TypeScript + Bun. AI agent skill.
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