Derive per-symbol feature vectors from streaming NBBO events with deterministic replay.
npx skills add https://github.com/Leiisawesome/feelies --skill feature-engine
Please help me install this Agent Skill. Skill: feature-engine Source: https://github.com/Leiisawesome/feelies/tree/main/.cursor/skills/feature-engine Command: npx skills add https://github.com/Leiisawesome/feelies --skill feature-engine
This Skill provides a deterministic, stateful feature engine that incrementally updates per-symbol feature state from L1 NBBO events, reducing recomputation and ensuring reproducible results across warm-up, cold-start, and recovery scenarios.
Run the feature engine on a stream of NBBO quotes and trades to observe per-symbol feature vectors being emitted as state evolves.
High-intent search queries and answers about installing and using this skill.
To compute incremental per-symbol features from NBBO market data, use a stateful feature engine that processes streaming quotes and trades to emit evolving feature vectors with deterministic replay guarantees.
Per-symbol state isolation in feature engineering ensures each symbol maintains independent lifecycle phases—Init, Warm-up, Active, Stale, and Reset—preventing cross-contamination during stateful processing of concurrent market data streams.
Deterministic replay guarantees reproducibility by applying versioned provenance and a checkpoint/restore contract via a FeatureSnapshotStore, ensuring identical feature vectors are generated across cold-start, warm-up, and recovery scenarios.
Yes, you can manage bounded memory usage for rolling window, count-based, and EWMA features by enforcing strict per-symbol memory limits and staleness detection during incremental state updates.
Yes, feature engineering supports a strict feature–signal boundary, isolating deterministic state management and feature vector emission from downstream signal generation logic to enable reliable quantitative analysis.
You should not use incremental state management for market data backtesting if your workflow requires unbounded historical windowing or lacks a checkpoint/restore contract to handle state staleness and recovery.
LeiisawesomeIngest, validate, and store NBBO and trade data from Massive into an immutable event log.
wudyeGenerate per-symbol trading signals across multiple market types with volatility-adjusted weighting.
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