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BytesAgainBytesAgain
πŸ¦€ ClawHub

Beta TA Signal Engine

by @1477009639zw-blip

Generate technical-analysis trade setups from OHLCV CSV using SMA/EMA/RSI/MACD/ATR with clear entry, stop, target, and position size.

Versionv1.0.0
Downloads801
TERMINAL
clawhub install beta-ta-signal-engine

πŸ“– About This Skill


name: ta-signal-engine description: Generate technical-analysis trade setups from OHLCV CSV using SMA/EMA/RSI/MACD/ATR with clear entry, stop, target, and position size.

TA Signal Engine

Use this skill when the user wants technical-analysis based entry/exit signals and risk-defined trade setup proposals.

Inputs

  • OHLCV CSV with headers including: date, open, high, low, close (case-insensitive)
  • Strategy mode: trend, mean-reversion, or breakout
  • Run

    python3 scripts/ta_signal_engine.py \
      --csv /abs/path/prices.csv \
      --symbol BTCUSDT \
      --strategy trend \
      --account-size 100000 \
      --risk-per-trade 0.01 \
      --json
    

    Workflow

    1. Run the script and inspect signal and confidence. 2. If signal=flat, explain why (no edge from current indicators). 3. If signal is active, use generated entry/stop/target/size as the candidate plan. 4. Do not claim certainty; frame it as probabilistic setup.

    Notes

  • This skill only produces analysis and paper-trade plans.
  • For historical evaluation, use ta-backtest skill.
  • For ledger/order lifecycle, use ta-paper-executor skill.
  • πŸ“‹ Tips & Best Practices

  • This skill only produces analysis and paper-trade plans.
  • For historical evaluation, use ta-backtest skill.
  • For ledger/order lifecycle, use ta-paper-executor skill.