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Skills/tradermonty/claude-trading-skills/vcp-screener
vcp-screener logo

vcp-screener

tradermonty/claude-trading-skills
614 installs2K stars
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Installation

npx skills add https://github.com/tradermonty/claude-trading-skills --skill vcp-screener

Summary

Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP). Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points. Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout candidates, or Stage 2 momentum stock scanning.

SKILL.md

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

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/

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/
ParameterDefaultRangeEffect
--min-contractions22-4Higher = fewer but higher-quality patterns
--t1-depth-min10.0%1-50Higher = excludes shallow first corrections
--breakout-volume-ratio1.5x0.5-10Higher = stricter volume confirmation
--trend-min-score850-100Higher = stricter Stage 2 filter
--atr-multiplier1.50.5-5Lower = more sensitive swing detection
--contraction-ratio0.700.1-1Lower = requires tighter contractions
--min-contraction-days51-30Higher = longer minimum contraction
--lookback-days12030-365Longer = finds older patterns
--max-sma200-extension50.0%—SMA200 distance threshold for Overextended state and penalty
--wide-and-loose-threshold15.0%—Final contraction depth above which wide-and-loose flag triggers
--strictoff—Minervini strict mode: only Pre-breakout or Breakout with valid VCP

Step 2: Review Results

  1. Read the generated JSON and Markdown reports
  2. Load references/vcp_methodology.md for pattern interpretation context
  3. Load references/scoring_system.md for 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

  1. Pre-Filter - Quote-based screening (price, volume, 52w position) ~101 API calls
  2. Trend Template - 7-point Stage 2 filter with 260-day histories ~100 API calls
  3. 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

Score

0–100
65/ 100

Grade

C

Popularity17/30

614 installs — growing adoption. Source repo has 1,912 GitHub stars.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Vcp Screener skill score badge previewScore badge

Markdown

[![Vcp Screener skill](https://www.claudemarket.ai/skills/tradermonty/claude-trading-skills/vcp-screener/badges/score.svg)](https://www.claudemarket.ai/skills/tradermonty/claude-trading-skills/vcp-screener)

HTML

<a href="https://www.claudemarket.ai/skills/tradermonty/claude-trading-skills/vcp-screener"><img src="https://www.claudemarket.ai/skills/tradermonty/claude-trading-skills/vcp-screener/badges/score.svg" alt="Vcp Screener skill"/></a>

Vcp Screener FAQ

How do I install the Vcp Screener skill?

Run “npx skills add https://github.com/tradermonty/claude-trading-skills --skill vcp-screener” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Vcp Screener skill do?

Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP). Identifies Stage 2 uptrend stocks forming tight bases with contracting volatility near breakout pivot points. Use when user requests VCP screening, Minervini-style setups, tight base patterns, volatility contraction breakout candidates, or Stage 2 momentum stock scanning. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Vcp Screener skill free?

Yes. Vcp Screener is a free, open-source skill published from tradermonty/claude-trading-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Vcp Screener work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Vcp Screener works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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