SkillsLib.ai

Signal Analysis Framework for Crypto Trading

Generate and validate crypto trading signals with technical and on-chain analysis

3.2(5 reviews)
100+ downloads
Updated Sep 2026

What You Can Do

You can systematically generate crypto trading signals by combining technical indicators with on-chain metrics, then validate each signal against your risk criteria before execution. The framework evaluates market conditions, calculates position sizing based on volatility and risk tolerance, and produces actionable entry/exit recommendations with clear confidence scores.

Features

Multi-Indicator Technical Analysis

Evaluate moving averages, RSI, MACD, Bollinger Bands, and support/resistance levels to generate directional signals with chart context

On-Chain Metric Integration

Assess wallet movements, exchange flows, whale transactions, and holder behavior to confirm signals with blockchain-level conviction

Signal Validation Framework

Apply a systematic checklist that grades each signal across multiple criteria (trend confirmation, volume, momentum, risk) before marking it actionable

Risk-Adjusted Position Sizing

Calculate optimal trade size based on your risk tolerance, stop-loss distance, and account equity to protect against catastrophic drawdowns

Entry and Exit Recommendations

Generate specific price levels for entry, take-profit targets, and stop-loss with clear rationale tied to support/resistance and volatility

Confidence Scoring

Rank signals on a scale that reflects how many confirmation criteria passed, helping you prioritize high-conviction trades

Market Regime Detection

Identify trending, ranging, or volatile market conditions and adjust signal sensitivity accordingly to reduce false signals

Trade Logging and Backtesting

Document each trade outcome, calculate win rate and risk-reward ratios, and iterate signal rules based on historical performance

Example Output

Sample Signal Output

Ethereum (ETHUSDT) - Long Signal (4h)

Confidence Score: 8.2/10

  • Technical: Bullish (moving average crossover, RSI oversold recovery, breakout above key resistance at $2,480)
  • On-Chain: Bullish (whale accumulation +5,234 ETH, exchange outflows exceed inflows by 12%)
  • Regime: Trending upward, moderate volatility

Recommendation:

  • Entry Zone: $2,485 to $2,510 (support + breakout retest)
  • Take-Profit 1: $2,580 (first resistance, +3%)
  • Take-Profit 2: $2,650 (secondary target, +6.6%)
  • Stop-Loss: $2,420 (below support, 2.5% risk)
  • Position Size: 0.5 BTC equivalent (2% account risk at stop)

Invalidation: Close below $2,420 on 4h candle


Signal Validation Checklist

✓ Trend confirmation (multiple timeframes aligned) ✓ Support/resistance respected ✗ Volume surge needed (current volume: 95% of average) ✓ Risk-reward ratio exceeds 1:2 ✓ On-chain behavior supportive ✓ No conflicting macro news

What's Included

  • Technical Analysis Template: Pre-built evaluation system for identifying trends, momentum shifts, and reversal patterns across moving averages, RSI, MACD, and price action
  • On-Chain Metric Queries: Structured prompts to assess wallet concentrations, exchange flows, transaction patterns, and holder sentiment to confirm or contradict technical signals
  • Signal Validation Checklist: Multi-criteria framework that scores each signal across trend, volume, momentum, on-chain, and risk dimensions before you commit capital
  • Position Sizing Calculator: Formulas to calculate optimal trade size based on your risk tolerance, stop-loss distance, account equity, and portfolio exposure limits
  • Risk Management Playbook: Guidelines for setting stop-losses, managing partial positions, scaling into trends, and protecting unrealized gains during volatile moves
  • Trade Journal Template: Structured format to log each trade, record entry/exit prices, note signal criteria used, and calculate performance metrics for continuous improvement

Who It's For

  • Day traders seeking systematic entry and exit rules
  • Swing traders validating multi-day position ideas
  • Crypto analysts developing and backtesting strategies
  • Portfolio managers evaluating rebalancing opportunities
  • Trading bot developers building decision logic for automation

Best For

  • Identifying high-conviction entry points with multiple confirmations
  • Quantifying risk before placing a trade
  • Validating gut-feeling signals against systematic criteria
  • Building a repeatable, testable trading process
  • Analyzing trade outcomes to refine signal rules over time

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