Stockbee Momentum Burst Screener

Screen US stocks for Stockbee-style short-term Momentum Burst setups using 4% breakout, dollar breakout, range expansion, volume expansion, prior range contraction, close-location, failure filters, and risk-distance scoring. Use when the user asks for Stockbee, Pradeep Bonde, momentum burst, 4% breakout, range expansion, dollar breakout, short-term swing momentum candidates, or 3-5 day burst setup review.

FMP Required

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

Stockbee Momentum Burst Screener

2. When to Use

  • User asks for Stockbee / Pradeep Bonde style Momentum Burst screening
  • User wants 4% breakout, dollar breakout, or range expansion candidates
  • User asks for short-term 3-5 day swing momentum setups
  • User wants to review whether a daily breakout has A/B/C setup quality
  • User provides a symbol list, universe file, or historical OHLCV JSON for screening
  • User wants candidate outputs to feed into technical-analyst, position-sizer, or trader-memory-core

3. Prerequisites

  • FMP API key for live universe and historical OHLCV screening: 
    export FMP_API_KEY=your_api_key_here
  • Optional no-API path: provide --prices-json containing daily OHLCV bars by symbol.
  • Run only after the market-regime workflow allows new swing risk, or mark output as manual-review-only.

4. Quick Start 

python3 skills/stockbee-momentum-burst-screener/scripts/screen_momentum_burst.py \
  --fmp-universe \
  --max-symbols 300 \
  --output-dir reports/

5. Workflow

Step 1: Choose Input Mode

Use one of three modes:

Mode A: FMP universe scan

python3 skills/stockbee-momentum-burst-screener/scripts/screen_momentum_burst.py \
  --fmp-universe \
  --max-symbols 300 \
  --output-dir reports/

Mode B: Explicit symbols

python3 skills/stockbee-momentum-burst-screener/scripts/screen_momentum_burst.py \
  --symbols NVDA SMCI PLTR TSLA \
  --output-dir reports/

Mode C: Offline OHLCV JSON

python3 skills/stockbee-momentum-burst-screener/scripts/screen_momentum_burst.py \
  --prices-json data/daily_ohlcv.json \
  --output-dir reports/

Step 2: Run the Screening Pass

The script detects these trigger families:

  • 4% Breakout: close / previous_close >= 1.04, volume above previous day, and volume above the liquidity floor
  • Dollar Breakout: close - open >= 0.90, volume above the liquidity floor
  • Range Expansion: current daily range exceeds the prior three daily ranges while the prior day was not already extended

It then scores setup quality using:

  • Trigger strength
  • Volume expansion
  • Prior base / range contraction quality
  • Close location near the high of day
  • Risk distance to the trigger-day low
  • Failure filters such as prior 3-day run-up or recent 4% breakdown
  • Market gate alignment

Step 3: Review Output

Read the generated JSON and Markdown reports. For each candidate, present:

  • Trigger type and all matched trigger tags
  • Day gain, dollar gain, volume ratio, and close-location percentage
  • Prior base length and base width
  • Entry reference, stop reference, and risk percentage to stop
  • Setup score, rating, state, and reject reasons
  • Suggested downstream action

Step 4: Send Survivors to Trade Planning

Use the output conservatively:

  • A / A- candidates: send to technical-analyst for manual chart validation, then position-sizer
  • B candidates: watchlist or smaller-risk review only
  • Watch-only candidates: keep in model book; do not plan a trade unless chart review upgrades the setup
  • Rejected candidates: retain for post-analysis, not for execution

6. Resources

References:

  • skills/stockbee-momentum-burst-screener/references/entry_exit_rules.md
  • skills/stockbee-momentum-burst-screener/references/momentum_burst_methodology.md
  • skills/stockbee-momentum-burst-screener/references/scoring_system.md

Scripts:

  • skills/stockbee-momentum-burst-screener/scripts/screen_momentum_burst.py