weather-py_skill

Overview

This skill automates trading temperature markets on Polymarket using NOAA forecasts via the Simmer API. It implements gopfan2-style rules for buying low and selling high, with optional smart sizing, safeguards, and trend detection. Use it to scan markets, place trades, and tag weather positions for portfolio tracking.

How this skill works

Each run fetches active weather markets from the Simmer API, parses event names into location and date, and pulls the NOAA forecast for that location/date. The script matches the forecast to the market bucket, applies safeguards and trend checks, then buys if the bucket price is below the entry threshold or sells existing positions if above the exit threshold. Trades are tagged with sdk:weather and optional smart sizing uses a percentage of USDC balance capped by a max per-trade limit.

When to use it

• Automate temperature market scanning and trading on Polymarket
• Apply a gopfan2-style buy-low / sell-high weather strategy
• Check NOAA-based signals before placing weather bets
• Manage weather positions and view portfolio-tagged performance
• Run scheduled scans to capture short-lived temperature opportunities

Best practices

• Provide a valid SIMMER_API_KEY and store it in environment variables
• Start in dry-run mode before enabling live trading to verify behavior
• Enable smart sizing to scale position sizes to your balance
• Limit max trades per run to avoid overtrading during scans
• Keep safeguards enabled unless you understand the risks

Example use cases

• Scan NYC temperature markets nightly and buy buckets under $0.15
• Automatically sell weather positions when price rises above $0.45
• Run scheduled scans for multiple supported cities (NYC, Chicago, Seattle)
• Use smart-sizing to allocate 5% of balance per trade with a $2 cap
• Quickly inspect balance and positions with the provided status script