entry-signals_skill

Overview

This skill provides a catalog of entry signal patterns with historical success rates and confidence levels to help decide whether to open a position. It highlights multi-timeframe alignments, indicator combinations (SMA, MACD, RSI, funding rates), and scaling techniques with sample counts and empirical success. Use it as a quantitative checklist to prioritize high-probability trade ideas and to document why an entry was chosen.

How this skill works

The skill inspects learned patterns from historical competition data and reports each signal’s success rate, sample size, and statistical confidence. It surfaces signals validated across multiple timeframes and indicator stacks, and annotates those that consistently passed risk and trade validation checks. Traders combine these signals with their own risk rules to make final entry decisions.

When to use it

• When you need a data-driven filter before opening a new position
• To validate an idea generated by technical or trend analysis
• When scaling into an existing winning position and seeking historical precedent
• Before committing capital to multi-timeframe trend trades
• To compare alternative entry setups and choose the higher-probability option

Best practices

• Treat success rates as conditional probabilities, not guarantees
• Combine signals with explicit risk validation and position-sizing rules
• Favor patterns with higher confidence and larger sample counts for core entries
• Use low-confidence or experimental signals only as secondary inputs
• Document each entry and compare outcomes to the skill’s historical metrics

Example use cases

• Confirm a long entry when 15m/1h/4h timeframes all show bullish alignment and risk checks pass
• Validate adding size to a winning trade when scaling patterns show positive historical results
• Filter out trades when indicator stacks (SMA crossover, bullish MACD, neutral Bollinger) are not aligned
• Avoid using single-factor signals (e.g., funding rate alone) as primary justification for opening positions
• Investigate contrarian opportunities flagged as low success but recurring in recent samples