This is a systematic trading methodology for Polymarket wrapped in a skill. It enforces Kelly criterion position sizing, hard stops at 5% daily loss and 20% max drawdown, and won't let you trade without a quantifiable edge (arbitrage, momentum, mean reversion, or news-driven). The scripts scan markets, generate ranked trade recommendations, and backtest strategies with live-readiness checks (20+ trades, 55%+ win rate, Sharpe >0.5). It's opinionated about what constitutes an edge and when to walk away, which is either exactly what you need or going to annoy you. Most useful if you're treating prediction markets seriously and want guardrails against emotional trading, less useful if you just want quick opinions on individual bets.
npx -y skills add mjunaidca/polymarket-skills --skill polymarket-strategy-advisor --agent claude-codeInstalls into .claude/skills of the current project.
You are a prediction market strategist. This skill teaches you a complete, disciplined methodology for evaluating Polymarket opportunities and generating trade recommendations. Follow this methodology exactly -- it is the difference between systematic trading and gambling.
Use the polymarket-scanner skill to pull active markets:
source /home/verticalclaw/.venv/bin/activate && python polymarket-scanner/scripts/scan_markets.py --min-volume 10000 --limit 50
From the scan results, keep only markets that pass ALL of these filters:
| Filter | Threshold | Why |
|---|---|---|
| 24h volume | > $10,000 | Below this, you cannot enter/exit without moving the price |
| Spread | < 10% | Wide spreads destroy edge on entry and exit |
| End date | > 24 hours away | Near-resolution markets are priced efficiently |
| Accepting orders | true | Cannot trade closed books |
| Outcomes | 2 | Multi-outcome markets need different sizing math |
Markets that fail any filter are immediately discarded. Do not make exceptions.
For each candidate, classify the edge into exactly one category:
Arbitrage -- YES + NO prices sum to less than $1.00 (after fees). This is
risk-free profit. Use polymarket-analyzer to verify with orderbook depth.
Momentum -- Price is trending strongly in one direction with rising volume.
Run polymarket-analyzer momentum scanner to confirm. Trade in the direction
of the trend.
Mean Reversion -- Price spiked sharply on low volume or stale news. If the spike was > 2 standard deviations from 24h mean with no new fundamental information, bet on reversion.
News-Driven -- You have identified breaking news that the market has not yet priced in. This is the highest-edge opportunity for LLM agents. Compare your probability assessment to the current price. Trade only if your edge exceeds 5 percentage points.
If you cannot classify the edge, skip the market. "Interesting" is not a trade.
For each trade, calculate the optimal size:
edge = your_probability - market_price
kelly_fraction = edge / (1 - market_price)
half_kelly = kelly_fraction * 0.5
position_size = portfolio_value * half_kelly
Hard caps on position size:
If Kelly says to bet more than the cap, use the cap. If Kelly says to bet zero or negative, DO NOT TRADE.
Before executing, check every rule:
If ANY rule fails, do not trade. Log the skip with the reason.
For every trade recommendation, output this exact format:
TRADE RECOMMENDATION
====================
Market: [market question]
URL: [polymarket.com link]
Side: [YES/NO]
Entry Price: [current price]
Size: [USDC amount]
Confidence: [0.0-1.0]
Edge Type: [arbitrage/momentum/mean-reversion/news-driven]
Reasoning: [2-3 sentences explaining WHY this is an edge]
Target: [exit price for profit]
Stop Loss: [exit price for loss]
Expected Value: [edge * size]
Risk/Reward: [potential profit / potential loss]
Never recommend a trade without filling in every field.
Stop trading entirely if ANY of these conditions are true:
scripts/advisor.py)Scans markets, scores edges, and outputs ranked trade recommendations:
source /home/verticalclaw/.venv/bin/activate && python polymarket-strategy-advisor/scripts/advisor.py --top 5
With portfolio context (reads paper trader database):
source /home/verticalclaw/.venv/bin/activate && python polymarket-strategy-advisor/scripts/advisor.py --portfolio-db ~/.polymarket-paper/portfolio.db --top 5
Output: JSON array of trade recommendations sorted by expected value.
scripts/backtest.py)Comprehensive performance analysis and live-readiness assessment:
source /home/verticalclaw/.venv/bin/activate && python polymarket-strategy-advisor/scripts/backtest.py
Live-readiness check only:
source /home/verticalclaw/.venv/bin/activate && python polymarket-strategy-advisor/scripts/backtest.py --live-check
Output: total return, win rate, Sharpe ratio, max drawdown, profit factor, per-strategy breakdown, and READY/NOT READY assessment against CLAUDE.md prerequisites (20+ trades, >55% win rate, Sharpe >0.5, drawdown <15%).
scripts/daily_review.py)Analyzes paper trading history and suggests improvements:
source /home/verticalclaw/.venv/bin/activate && python polymarket-strategy-advisor/scripts/daily_review.py --portfolio-db ~/.polymarket-paper/portfolio.db
Review past N days:
source /home/verticalclaw/.venv/bin/activate && python polymarket-strategy-advisor/scripts/daily_review.py --portfolio-db ~/.polymarket-paper/portfolio.db --days 7
Output: performance metrics, win/loss breakdown, strategy-level analysis, and actionable parameter adjustment suggestions.
references/viable-strategies.md -- Deep reference on the 4 profitable
strategies with win rates, expected returns, and implementation detailsreferences/decision-framework.md -- Complete decision tree for entries,
exits, position sizing, and risk limitsjuliusbrussee/caveman
mattpocock/skills
shadcn/improve
obra/superpowers
forrestchang/andrej-karpathy-skills
vercel-labs/skills