stockbee-episodic-pivot-analyzer

Q: How do I install stockbee-episodic-pivot-analyzer?

Run npx skills add https://github.com/tradermonty/claude-trading-skills --skill stockbee-episodic-pivot-analyzer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/stockbee-episodic-pivot-analyzer/ (personal) or .claude/skills/stockbee-episodic-pivot-analyzer/ (project).

by tradermontyFrontend & Design

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.

Installs: 2.6K
Last 24h: +20
Trending rank: #5849
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/tradermonty/claude-trading-skills --skill stockbee-episodic-pivot-analyzer

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads stockbee-episodic-pivot-analyzer automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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 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

Shared FMP client

Live FMP access uses the bundled generated scripts/fmp_client.py, loaded only when an FMP run starts, so offline modes still work without requests. CLI key/environment precedence, the API-call budget and successful output shapes are preserved. Requests use stable endpoints only; a denied, empty or failed stable request does not fall back to retired v3 URLs. The shared client masks raw and URL-encoded key echoes, retries malformed JSON once, and retries a 429 at most once, after a 60-second wait, before stopping on a repeated rate limit.

FAQ

What does the stockbee-episodic-pivot-analyzer skill do?

How do I install stockbee-episodic-pivot-analyzer?

Run npx skills add https://github.com/tradermonty/claude-trading-skills --skill stockbee-episodic-pivot-analyzer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/stockbee-episodic-pivot-analyzer/ (personal) or .claude/skills/stockbee-episodic-pivot-analyzer/ (project).

Which AI agents can use stockbee-episodic-pivot-analyzer?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is stockbee-episodic-pivot-analyzer safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains stockbee-episodic-pivot-analyzer?

It is published by tradermonty in tradermonty/claude-trading-skills. It has 2,648 recorded installs.