VCP Screener - Minervini Volatility Contraction Pattern Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP), identifying Stage 2 uptrend stocks with contracting volatility near breakout pivot points. When to Use User asks for VCP screening or Minervini-style setups User wants to find tight base / volatility contraction patterns User requests Stage 2 momentum stock scanning User asks for breakout candidates with defined risk Prerequisites FMP API key (set FMP_API_KEY environment variable or pass --api-key ) Free tier (250 calls/day) is sufficient for default screening (top 100 candidates) Paid tier recommended for full S&P 500 screening ( --full-sp500 ) Workflow Step 1: Prepare and Execute Screening Run the VCP screener script:

Default: S&P 500, top 100 candidates

python3 skills/vcp-screener/scripts/screen_vcp.py --output-dir skills/vcp-screener/scripts

Custom universe

python3 skills/vcp-screener/scripts/screen_vcp.py --universe AAPL NVDA MSFT AMZN META --output-dir skills/vcp-screener/scripts

Full S&P 500 (paid API tier)

python3 skills/vcp-screener/scripts/screen_vcp.py --full-sp500 --output-dir skills/vcp-screener/scripts Advanced Tuning (for backtesting) Adjust VCP detection parameters for research and backtesting: python3 skills/vcp-screener/scripts/screen_vcp.py \ --min-contractions 3 \ --t1-depth-min 12.0 \ --breakout-volume-ratio 2.0 \ --trend-min-score 90 \ --atr-multiplier 1.5 \ --output-dir reports/ Parameter Default Range Effect --min-contractions 2 2-4 Higher = fewer but higher-quality patterns --t1-depth-min 8.0% 1-50 Higher = excludes shallow first corrections --breakout-volume-ratio 1.5x 0.5-10 Higher = stricter volume confirmation --trend-min-score 85 0-100 Higher = stricter Stage 2 filter --atr-multiplier 1.5 0.5-5 Lower = more sensitive swing detection --contraction-ratio 0.75 0.1-1 Lower = requires tighter contractions --min-contraction-days 5 1-30 Higher = longer minimum contraction --lookback-days 120 30-365 Longer = finds older patterns Step 2: Review Results Read the generated JSON and Markdown reports Load references/vcp_methodology.md for pattern interpretation context Load references/scoring_system.md for score threshold guidance Step 3: Present Analysis For each top candidate, present: VCP composite score and rating Contraction details (T1/T2/T3 depths and ratios) Trade setup: pivot price, stop-loss, risk percentage Volume dry-up ratio Relative strength rank Step 4: Provide Actionable Guidance Based on ratings: Textbook VCP (90+): Buy at pivot with aggressive sizing Strong VCP (80-89): Buy at pivot with standard sizing Good VCP (70-79): Buy on volume confirmation above pivot Developing (60-69): Add to watchlist, wait for tighter contraction Weak/No VCP (<60): Monitor only or skip 3-Phase Pipeline Pre-Filter - Quote-based screening (price, volume, 52w position) ~101 API calls Trend Template - 7-point Stage 2 filter with 260-day histories ~100 API calls VCP Detection - Pattern analysis, scoring, report generation (no additional API calls) Output vcp_screener_YYYY-MM-DD_HHMMSS.json - Structured results vcp_screener_YYYY-MM-DD_HHMMSS.md - Human-readable report Resources references/vcp_methodology.md - VCP theory and Trend Template explanation references/scoring_system.md - Scoring thresholds and component weights references/fmp_api_endpoints.md - API endpoints and rate limits