# Trader Train

> Train neural models (LSTM, Transformer, N-BEATS) on market data using npx neural-trader with confidence intervals

- Skill: `thedixitjain/trader-train` (Agent Skill)
- Install (CLI): `npx skillmds add thedixitjain/trader-train`
- Raw SKILL.md: https://api.skillmd.com/api/skills/thedixitjain/trader-train/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: thedixitjain (https://skillmd.com/u/thedixitjain)
- Updated: 2026-09-09
- Page: https://skillmd.com/skills/thedixitjain/trader-train

---


Train neural prediction models using neural-trader's ML engine.

Steps:
1. Ensure neural-trader is available:
   `npm ls neural-trader 2>/dev/null || npm install --ignore-scripts neural-trader`
2. Train the specified model:
   ```bash
   npx 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
   ```
3. Review training output: loss curves, validation metrics, prediction accuracy
4. Generate predictions with confidence intervals:
   ```bash
   npx neural-trader --model MODEL --symbol TICKER --predict --horizon 5d
   ```
5. Compare model performance across types:
   ```bash
   npx neural-trader --model-compare --symbol TICKER --models "lstm,transformer,nbeats"
   ```
6. Store model results (canonical `trading-analysis` namespace per ADR-126 Phase 1 — was previously stored to undeclared `trading-models`):
   `mcp__plugin_ruflo-core_ruflo__memory_store({ key: "model-MODEL-TICKER-DATE", value: "TRAINING_RESULTS", namespace: "trading-analysis" })`
7. Train SONA on model outcomes:
   `mcp__plugin_ruflo-core_ruflo__neural_train({ patternType: "trading-model", epochs: 10 })`

---

**Source:** [`ruvnet/ruflo`](https://github.com/ruvnet/ruflo) → `plugins/ruflo-neural-trader/skills/trader-train/SKILL.md`