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trader-train

trader-train

github.com/ruvnetData & databases80.0k736 installsUpdated today
Repository

About trader-train

A skill for training neural prediction models with neural-trader, reviewing metrics, generating forecasts, and comparing model types. It also stores results and trains SONA on outcomes.

Key features

  1. 01Train LSTM, transformer, and N-BEATS models
  2. 02Review loss and validation metrics
  3. 03Generate forecasts with confidence intervals
  4. 04Compare model performance
  5. 05Store results and train SONA

Use cases

  1. 01Train a model for a specified ticker
  2. 02Forecast a ticker over a chosen horizon
  3. 03Compare prediction model types
  4. 04Save results for later analysis

MCP support

Uses Ruflo memory storage to save training results in the trading-analysis namespace and calls neural_train to train SONA on model outcomes.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/ruvnet/ruflo --skill trader-train

After installing, type/trader-trainin Claude Code to confirm it loaded.

Details

From the project README

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: 
    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: 
    npx neural-trader --model MODEL --symbol TICKER --predict --horizon 5d
  5. Compare model performance across types: 
    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 })

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