weather-trader_skill

Overview

This skill automates trading of temperature markets using NOAA forecasts and Simmer Markets. It applies dynamic confidence modeling and market-quality filters to limit trades and manage risk. Default behavior is manual; autonomous runs occur on a 6-hour schedule only after explicit enablement.

How this skill works

The skill fetches NOAA forecasts and resolves city names via OpenStreetMap geocoding, then discovers matching weather markets on Simmer Markets. It computes an edge using a dynamic confidence model (60–90% based on lead time), scores market quality, and executes buys when price < entry threshold and auto-exits above the exit threshold. Safety checks enforce per-trade and per-run limits and optional dry-run mode.

When to use it

• You want automated temperature trading informed by official NOAA forecasts.
• You need dynamic confidence weighting based on forecast lead time.
• You want built-in market quality filtering to avoid low-liquidity markets.
• You want conservative default risk controls (small position and trade limits).
• You plan to manually validate behavior before enabling autonomous runs.

Best practices

• Review source code and verify network endpoints before use.
• Create a least-privilege Simmer API key (trading/read only, no withdrawal).
• Start with dry-run mode or manual runs to validate behavior and sizing.
• Keep autostart disabled until confident; enable scheduled runs only after testing.
• Use smart-sizing and low per-trade caps; monitor live dashboard for executed trades.

Example use cases

• Manually run a dry simulation to verify forecasts and candidate markets before placing money.
• Trade same-day and next-day temperature buckets with higher confidence weighting.
• Filter out markets with low liquidity or short time-to-resolution using the quality score.
• Enforce conservative exposure by capping USD per trade and trades per run.
• Run scheduled trading every 6 hours after thorough manual testing and API-key verification.