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Train neural models (LSTM, Transformer, N-BEATS) on market data using npx neural-trader with confidence intervals
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Based on SOC occupation classification
Build or rebuild the ADR index + dependency graph in AgentDB by running the in-process `agentdb index` command (one cold-start, all surfaces in one pass — no per-record npx round-trips). Handles v3-style and plugin-style ADR formats.
Create a new Architecture Decision Record with sequential numbering and AgentDB registration
Hive Mind orchestration patterns — queen-led multi-agent coordination with Byzantine/Raft/Gossip/CRDT consensus, typed collective memory, dialectic council, and session checkpoint/resume. Use for decision-bearing work; use swarm-advanced for parallel execution without consensus.
Analyze git diffs for risk scoring, reviewer recommendations, and change classification
Detect missing test coverage and generate test suggestions
Hive Mind orchestration patterns — queen-led multi-agent coordination with Byzantine/Raft/Gossip/CRDT consensus, typed collective memory, dialectic council, and session checkpoint/resume. Use for decision-bearing work; use swarm-advanced for parallel execution without consensus.
| name | trader-train |
| description | Train neural models (LSTM, Transformer, N-BEATS) on market data using npx neural-trader with confidence intervals |
| allowed-tools | Bash Read mcp__ruflo__memory_store mcp__ruflo__memory_search mcp__ruflo__neural_train |
| argument-hint | <lstm|transformer|nbeats> --symbol <TICKER> |
Train neural prediction models using neural-trader's ML engine.
Steps:
npm ls neural-trader 2>/dev/null || npm install neural-tradernpx neural-trader --model lstm --symbol TICKER --confidence 0.95
npx neural-trader --model transformer --symbol TICKER --predict
npx neural-trader --model nbeats --symbol TICKER --decompose
npx neural-trader --model MODEL --symbol TICKER --predict --horizon 5d
npx neural-trader --model-compare --symbol TICKER --models "lstm,transformer,nbeats"
trading-analysis namespace per ADR-126 Phase 1 — was previously stored to undeclared trading-models):
mcp__ruflo__memory_store({ key: "model-MODEL-TICKER-DATE", value: "TRAINING_RESULTS", namespace: "trading-analysis" })mcp__ruflo__neural_train({ patternType: "trading-model", epochs: 10 })