Stockbee Episodic Pivot Analyzer
Analyze Stockbee-style Day 1 Episodic Pivot candidates from earnings, guidance raises, M&A, FDA/regulatory approvals, analyst actions, major contracts, product launches, short-squeeze catalysts, or theme/story events. Scores catalyst quality together with gap/range expansion, volume shock, neglect/revaluation context, liquidity, and risk to the EP-day low. Use when the user asks for EP candidates, episodic pivots, Day 1 catalyst trades, game-changing news reactions, delayed EP watchlists, or handoffs into PEAD monitoring.
No API FMP Optional
Download Skill Package (.skill) View Source on GitHub
Table of Contents
1. Overview
Stockbee Episodic Pivot Analyzer
2. When to Use
- The user asks for Pradeep Bonde / Stockbee style EP candidates
- The user provides earnings, guidance, M&A, FDA, analyst, contract, product, short-squeeze, or theme/news events
- The user wants to separate
ACTIONABLE_DAY1candidates fromDELAYED_EP_WATCHnames - The user wants to hand strong earnings/guidance EPs into
pead-screener - The user wants to combine catalyst analysis with
stockbee-momentum-burst-screenerprice/volume output
3. Prerequisites
- Python 3.10+
- Optional: FMP API key for OHLCV/profile enrichment
- One of:
- Catalyst/events JSON
earnings-trade-analyzerJSON output- Catalyst JSON plus
stockbee-momentum-burst-screenerJSON enrichment
- This skill does not fetch or discover news by itself. If the catalyst is not supplied, first gather the event/news context using the user’s preferred news or research process.
4. Quick Start
**Mode B — Earnings pipeline:**
Use the JSON produced by `earnings-trade-analyzer`.
**Mode C — Price/volume enrichment:**
Pass a `stockbee-momentum-burst-screener` JSON report to reuse day-gain, volume, close-location, and risk-distance fields.
### Step 2: Run the Analyzer
5. Workflow
Step 1: Prepare Candidate Inputs
Use one or more of these input modes.
Mode A — Catalyst/event JSON:
{
"events": [
{
"symbol": "ABC",
"event_date": "2026-04-25",
"catalyst_type": "guidance_raise",
"headline": "ABC raises FY guidance after record demand",
"summary": "Management raised revenue and EPS guidance."
}
]
}
Mode B — Earnings pipeline:
Use the JSON produced by earnings-trade-analyzer.
Mode C — Price/volume enrichment:
Pass a stockbee-momentum-burst-screener JSON report to reuse day-gain, volume, close-location, and risk-distance fields.
Step 2: Run the Analyzer
# Catalyst JSON + offline OHLCV
python3 skills/stockbee-episodic-pivot-analyzer/scripts/analyze_ep.py \
--events-json data/catalysts.json \
--prices-json data/daily_ohlcv.json \
--output-dir reports/
# Earnings pipeline input
python3 skills/stockbee-episodic-pivot-analyzer/scripts/analyze_ep.py \
--earnings-json reports/earnings_trade_analyzer_YYYY-MM-DD_HHMMSS.json \
--output-dir reports/
# Catalyst JSON + Stockbee momentum enrichment
python3 skills/stockbee-episodic-pivot-analyzer/scripts/analyze_ep.py \
--events-json data/catalysts.json \
--momentum-json reports/stockbee_momentum_burst_YYYY-MM-DD_HHMMSS.json \
--output-dir reports/
Optional FMP enrichment:
export FMP_API_KEY=your_key
python3 skills/stockbee-episodic-pivot-analyzer/scripts/analyze_ep.py \
--events-json data/catalysts.json \
--max-api-calls 200 \
--output-dir reports/
Step 3: Review the Output
For each candidate, present:
state:ACTIONABLE_DAY1,DAY1_WATCH,DELAYED_EP_WATCH,CATALYST_WATCH, orREJECTep_type:EARNINGS_EP,GUIDANCE_EP,FDA_EP,M_AND_A_EP,STORY_EP, etc.- Catalyst quality score and reasons
- Price/range expansion, volume shock, and close-location quality
- Risk to EP-day low
pead_handoffanddelayed_ep_watchflags
Step 4: Handoff Rules
ACTIONABLE_DAY1: Send totechnical-analystandposition-sizerbefore any trade decision.DAY1_WATCH: Keep on the intraday/next-day watchlist; require chart confirmation.DELAYED_EP_WATCH: Do not chase Day 1; monitor for a controlled pullback or new range.CATALYST_WATCH: Catalyst may be important, but price/volume confirmation is not yet sufficient.REJECT: Do not trade from this candidate source.- Earnings/guidance EPs with
pead_handoff=truecan be sent topead-screenerfor weekly red-candle / delayed reaction monitoring.
6. Resources
References:
skills/stockbee-episodic-pivot-analyzer/references/catalyst_quality.mdskills/stockbee-episodic-pivot-analyzer/references/ep_methodology.mdskills/stockbee-episodic-pivot-analyzer/references/handoff_rules.md
Scripts:
skills/stockbee-episodic-pivot-analyzer/scripts/analyze_ep.py