PluginBench
Skill
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Audit score 90

stockbee-episodic-pivot-analyzer

tradermonty/claude-trading-skills

Identify and score Stockbee-style Day 1 Episodic Pivot candidates from earnings, M&A, FDA, and catalyst events.

What is stockbee-episodic-pivot-analyzer?

Analyzes potential Day 1 Episodic Pivot (EP) trading candidates by combining catalyst quality assessment with price/volume confirmation. Use this when evaluating earnings surprises, guidance raises, M&A announcements, regulatory approvals, or other game-changing news events to separate actionable Day 1 trades from delayed-reaction watchlist candidates.

  • Classifies candidates into ACTIONABLE_DAY1, DAY1_WATCH, DELAYED_EP_WATCH, CATALYST_WATCH, or REJECT states
  • Scores catalyst quality for earnings, guidance, FDA, M&A, analyst actions, contracts, product launches, and short-squeeze events
  • Evaluates price/range expansion, volume shock, close location, and risk-to-EP-day-low
  • Accepts catalyst JSON, earnings-trade-analyzer output, or stockbee-momentum-burst-screener enrichment
  • Generates structured JSON and markdown reports with handoff flags for downstream skills

How to install stockbee-episodic-pivot-analyzer

npx skills add https://github.com/tradermonty/claude-trading-skills --skill stockbee-episodic-pivot-analyzer
Prerequisites
  • Python 3.10+
  • Catalyst/event JSON, earnings-trade-analyzer output, or stockbee-momentum-burst-screener JSON
  • Optional: FMP API key for OHLCV and profile enrichment
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How to use stockbee-episodic-pivot-analyzer

  1. 1.Prepare candidate inputs: catalyst JSON, earnings pipeline output, or price/volume enrichment from momentum screener
  2. 2.Run the analyzer script with your input source (--events-json, --earnings-json, or --momentum-json)
  3. 3.Optionally set FMP_API_KEY environment variable for enriched OHLCV data
  4. 4.Review the output JSON and markdown report for each candidate's state, catalyst quality score, and handoff flags
  5. 5.Send ACTIONABLE_DAY1 candidates to technical-analyst and position-sizer; route earnings EPs with pead_handoff=true to pead-screener

Use cases

Good for
  • Screening earnings announcements for Day 1 gap-and-range-expansion candidates with volume confirmation
  • Evaluating FDA approvals or guidance raises to identify neglect/revaluation pivots
  • Combining catalyst events with momentum data to separate high-conviction Day 1 trades from delayed reactions
  • Preparing earnings/guidance EPs for PEAD (Post-Earnings Announcement Drift) monitoring via pead-screener
  • Building a delayed EP watchlist for controlled pullback entry opportunities
Who it's for
  • Day traders and swing traders focused on catalyst-driven price moves
  • Traders using Stockbee episodic pivot methodology
  • Quantitative researchers building event-driven screening workflows
  • Portfolio managers monitoring earnings and regulatory catalysts for tactical entry points

stockbee-episodic-pivot-analyzer FAQ

What is an Episodic Pivot (EP)?

An EP is a Stockbee-style Day 1 catalyst-driven trade setup where a stock gaps and expands its range on significant news (earnings, guidance, M&A, FDA, etc.) with volume confirmation, often leading to a revaluation or neglect-to-attention shift.

What input formats does this skill accept?

Catalyst/event JSON (with symbol, date, type, headline), earnings-trade-analyzer JSON output, or stockbee-momentum-burst-screener JSON for price/volume enrichment.

What do the output states mean?

ACTIONABLE_DAY1 = high-conviction Day 1 trade; DAY1_WATCH = requires chart confirmation; DELAYED_EP_WATCH = do not chase Day 1, monitor for pullback; CATALYST_WATCH = catalyst important but price/volume not yet sufficient; REJECT = do not trade.

Can I use this without an FMP API key?

Yes. The skill works offline with catalyst JSON and optional local OHLCV data. FMP enrichment is optional and improves profile and liquidity scoring.

How does this integrate with other skills?

Send ACTIONABLE_DAY1 candidates to technical-analyst and position-sizer for trade validation. Route earnings/guidance EPs with pead_handoff=true to pead-screener for weekly post-earnings drift monitoring.

Full instructions (SKILL.md)

Source of truth, from tradermonty/claude-trading-skills.


name: stockbee-episodic-pivot-analyzer description: 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.

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, or REJECT
  • ep_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_handoff and delayed_ep_watch flags

Step 4: Handoff Rules

  • ACTIONABLE_DAY1: Send to technical-analyst and position-sizer before 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=true can be sent to pead-screener for weekly red-candle / delayed reaction monitoring.

Output

  • stockbee_episodic_pivot_YYYY-MM-DD_HHMMSS.json — structured EP scoring report
  • stockbee_episodic_pivot_YYYY-MM-DD_HHMMSS.md — human-readable candidate report

Resources

  • references/ep_methodology.md — Stockbee EP interpretation and setup taxonomy
  • references/catalyst_quality.md — catalyst classification and quality scoring
  • references/handoff_rules.md — downstream workflow handoffs and review rules