whale-hunting

Business

Detect institutional whale activity in options for a given underlying. Use when the user asks about unusual options activity, large block trades, whale trades, or institutional options flow for a specific symbol.

QUICK START

How to use this skill

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Source SKILL.md: https://github.com/staskh/trading_skills/blob/HEAD/.claude/skills/whale-hunting/SKILL.md

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Whale Hunting

Scans option chains for a given underlying to identify institutional-sized trades using a two-step approach:

Crude scan (Yahoo Finance) — finds contracts with anomalous daily investment vs the rest of the chain.
Precise drill-down (Massive API) — fetches per-second bars for each candidate and flags seconds with outlier dollar invested.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

uv run python .claude/skills/whale-hunting/scripts/whale_hunting.py SYMBOL [--months N] [--date YYYY-MM-DD] [--sigma F] [--sigma-z F] [--summary]

Arguments

SYMBOL — Underlying ticker (e.g. AAPL, NVDA, SPY)
--months — Max months until option expiration to consider (default: 2)
--date — Trading date to analyze in YYYY-MM-DD format (default: latest trading day)
--sigma — Std-deviation multiplier for crude outlier threshold (default: 3.0)
--sigma-z — Modified Z-Score threshold for per-second small-sample detection (default: 3.5)
--summary — Also compute per-ticker summary and include it in the JSON output

Output

Returns JSON with:

underlying — The scanned symbol
trading_date — Date analyzed
source — "massive" (per-second data) or "yahoo only" (daily chain data)
total_whales — Total whale events found
total_call_invested — Sum of invested dollars in call whale events
total_put_invested — Sum of invested dollars in put whale events
call_put_ratio — Call invested / put invested (null if no puts)
whales — List of whale events:
- timestamp, ticker, type, strike, expiry
- close, volume, transactions, invested, break_even
summary (present only when --summary is passed) — List of per-ticker aggregates:
- ticker, type, strike, expiry, whale_count, total_invested, break_even

Examples

# Hunt whales for AAPL (latest trading day)
uv run python .claude/skills/whale-hunting/scripts/whale_hunting.py AAPL

# Hunt whales for NVDA on a specific date
uv run python .claude/skills/whale-hunting/scripts/whale_hunting.py NVDA --date 2026-03-13

# With per-ticker summary
uv run python .claude/skills/whale-hunting/scripts/whale_hunting.py HOOD --months 3 --summary

# Looser detection threshold
uv run python .claude/skills/whale-hunting/scripts/whale_hunting.py SPY --sigma 2.0

Reporting

After running the script, present the results as follows.

Header line:

Whale activity for {underlying} on {trading_date} — source: {source} Call flow: ${total_call_invested:,.0f} | Put flow: ${total_put_invested:,.0f} | C/P ratio: {call_put_ratio:.2f}

When --summary was requested, render the summary array as a table:

Time (ET)	Ticker	Type	Strike	Expiry	# Events	Total Invested	Break Even
{timestamp}	{ticker}	{type}	{strike}	{expiry}	{whale_count}	${total_invested:,.0f}	{break_even}

Sort by total_invested descending. For multi-event rows use the time range of first–last event (e.g. 11:46–12:33).

Interpretation guidance:

source: "massive" — High-confidence; per-second block trade data from Massive API
source: "yahoo only" — Fallback; daily-level data (Massive API key missing or no intraday data)
Low C/P ratio (< 0.5) — Bearish institutional positioning
High C/P ratio (> 2.0) — Bullish institutional positioning
transactions: 1 — Single block trade; strongest whale signal

Requirements

MASSIVE_API_KEY environment variable for per-second data. Without it, falls back to Yahoo Finance daily data.

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.