Market data integrity rules — gap filling, look-forward bias prevention, and stock split handling. Use when writing or reviewing code that loads prices, fills missing data, computes returns, backtests strategies, or makes trading decisions. Applies across Python, TypeScript, SQL, and TimescaleDB.
Analyze Volatio debug logs from /tmp/volatio-debug/. Use when the user asks to check debug logs, analyze problems, or diagnose simulation issues.
Apply bottom-up systematic testing to a multi-layer system. Use when asked to test, debug, or verify a pipeline that spans multiple layers (e.g., Python worker → bridge → processor → API → UI).
Drizzle Kit workflow for Volatio using idempotent migrations (generate + edit + migrate), never use push. Idempotent patterns prevent partial failure issues, enable safe re-runs, and work cleanly in CI. Use when schema changes, migration errors, or database sync issues occur.
Template for creating Volatio research experiments with Optuna optimization and portfolio backtesting. Includes proper train/test splits, lookahead bias prevention, results saving, and validated patterns from Exp 051-053.
Financial research look-ahead bias verification for Volatio ML pipelines, mandatory baseline comparisons, timezone handling, feature leakage detection. Use when model accuracy seems too good or validating prediction experiments.
Creating PROGRESSION.md documents for research experiment series in Volatio. Captures the evolution of ideas, learnings, and breakthroughs across numbered experiments (001, 002, ...). Use when documenting experiment series or reviewing research evolution.
Run Volatio CI locally before pushing (ci-local.sh), mirrors GitHub Actions exactly, catches failures fast. Use when preparing to push, debugging CI failures, or verifying changes will pass.