vcp-screener
Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path. Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points; in historical single-ticker mode walks a multi-year history and emits every VCP that formed with forward-outcome stats (breakout / stop-hit / timeout). Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout candidates, Stage 2 momentum stock scanning, or historical VCP pattern study on a specific ticker (e.g. FIX, TSLA).
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/tradermonty/claude-trading-skills --skill vcp-screener- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads vcp-screener automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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
- User asks "find every historical VCP in <TICKER>" or wants to study one ticker's
past VCP setups with forward outcomes (
--history --ticker SYM)
Prerequisites
- FMP API key (set
FMP_API_KEYenvironment 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
Strict Mode (Minervini pure setup)
Only return stocks with valid_vcp=True AND execution_state in (Pre-breakout, Breakout):
python3 skills/vcp-screener/scripts/screen_vcp.py --strict --output-dir reports/
Historical single-ticker mode
Walk one ticker's multi-year history, detect every VCP that ever formed, and attach forward-outcome stats (breakout / stop-hit / timeout, days-to-outcome, max gain, max loss) per detection. Useful for pattern study and backtesting context — not a real-time screener.
# Default: scan ~5 years (1260 trading days), 5-day stride, 60-day outcome window
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history --ticker FIX --output-dir reports/
# Custom scan length: 750 trading days (~3 years), 90-day outcome window
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history 750 --ticker TSLA \
--stride-days 5 --outcome-days 90 \
--output-dir reports/
# Long scan: 10 years (2520 trading days)
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history 2520 --ticker NVDA --output-dir reports/
Outputs (timestamped):
vcp_history_<SYM>_<YYYY-MM-DD_HHMMSS>.json— timeline of detections with full analyzer payload +forward_outcomeper detection + summary stats.vcp_history_<SYM>_<YYYY-MM-DD_HHMMSS>.md— human-readable timeline.
Mode-specific flags:
| Parameter | Default | Range | Effect |
|---|---|---|---|
--history [DAYS] | (off) / 1260 if bare | 100-5040 | Enable historical mode; optionally specify trading-day scan window (requires --ticker) |
--ticker SYM | — | — | Ticker to scan |
--stride-days | 5 | 1-60 | Trading-day step between as-of cursor positions |
--outcome-days | 60 | 5-252 | Forward window evaluated per detection |
Notes:
- Two FMP API calls per scan (ticker + SPY history), not 100+ like the cross-sectional pipeline.
marketCapand absolute RS percentile reflect the ticker in isolation, not against the live screening universe — use this report for pattern study, not portfolio sizing.- Detections are deduplicated by
(T1_high_date, last_low_date, pivot)so the same VCP isn't reported repeatedly as the cursor ages.
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 | 10.0% | 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 | 0.70 | 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 |
--max-sma200-extension | 50.0% | — | SMA200 distance threshold for Overextended state and penalty |
--wide-and-loose-threshold | 15.0% | — | Final contraction depth above which wide-and-loose flag triggers |
--strict | off | — | Minervini strict mode: only Pre-breakout or Breakout with valid VCP |
Step 2: Review Results
- Read the generated JSON and Markdown reports
- Load
references/vcp_methodology.mdfor pattern interpretation context - Load
references/scoring_system.mdfor score threshold guidance
Step 3: Present Analysis
For each top candidate, present:
- Quality (
composite_score/ rating) — how well-formed is the VCP pattern? - Execution State (
execution_state) — is it buyable now? (Pre-breakout / Breakout = actionable) - Pattern Type (
pattern_type) — Textbook VCP / VCP-adjacent / Post-breakout / Extended Leader / Damaged ★marker if a State Cap was applied (raw score was downgraded)- Contraction details (T1/T2/T3 depths and ratios)
- Trade setup: pivot price, stop-loss, risk percentage
- Volume dry-up ratio and breakout_volume_score
- Relative strength rank
Step 4: Provide Actionable Guidance
By Execution State (primary filter):
- Pre-breakout / Breakout: Pattern is in the active entry window — apply rating-based sizing
- Early-post-breakout: Breakout underway but above ideal entry — reduced size or wait for pullback
- Extended / Overextended: Trade missed — add to watchlist for next base
- Damaged / Invalid: Setup invalidated — do not enter
By Rating (secondary, after state confirms actionability):
- Textbook VCP (90+): Buy at pivot with aggressive sizing (1.5-2x)
- Strong VCP (80-89): Buy at pivot with standard sizing (1x)
- Good VCP (70-79): Buy on volume confirmation above pivot (0.75x)
- 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 resultsvcp_screener_YYYY-MM-DD_HHMMSS.md- Human-readable report
Resources
references/vcp_methodology.md- VCP theory and Trend Template explanationreferences/scoring_system.md- Scoring thresholds and component weightsreferences/fmp_api_endpoints.md- API endpoints and rate limits
FAQ
What does the vcp-screener skill do?
Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP) and detect historical VCPs in a single ticker's price path. Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points; in historical single-ticker mode walks a multi-year history and emits every VCP that formed with forward-outcome stats (breakout / stop-hit / timeout). Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout candidates, Stage 2 momentum stock scanning, or historical VCP pattern study on a specific ticker (e.g. FIX, TSLA).
How do I install vcp-screener?
Run npx skills add https://github.com/tradermonty/claude-trading-skills --skill vcp-screener in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/vcp-screener/ (personal) or .claude/skills/vcp-screener/ (project).
Which AI agents can use vcp-screener?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is vcp-screener safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains vcp-screener?
It is published by tradermonty in tradermonty/claude-trading-skills. It has 3,500 recorded installs.
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