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.
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SKILL.md
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.
Stockbee Episodic Pivot Analyzer
Classify Day 1 Episodic Pivot (EP) candidates using both catalyst quality and price/volume confirmation. The skill is a candidate-quality analyzer, not an execution engine.
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_DAY1 candidates from DELAYED_EP_WATCH names
The user wants to hand strong earnings/guidance EPs into pead-screener
The user wants to combine catalyst analysis with stockbee-momentum-burst-screener price/volume output
Prerequisites
Python 3.10+
Optional: FMP API key for OHLCV/profile enrichment
One of:
Catalyst/events JSON
earnings-trade-analyzer JSON output
Catalyst JSON plus stockbee-momentum-burst-screener JSON 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.
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.