whale-hunting
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.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/staskh/trading_skills --skill whale-hunting- 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 whale-hunting 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.
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
uvis not installed orpyproject.tomlis not found, replaceuv run pythonwithpythonin 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 inYYYY-MM-DDformat (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 symboltrading_date— Date analyzedsource—"massive"(per-second data) or"yahoo only"(daily chain data)total_whales— Total whale events foundtotal_call_invested— Sum of invested dollars in call whale eventstotal_put_invested— Sum of invested dollars in put whale eventscall_put_ratio— Call invested / put invested (null if no puts)whales— List of whale events:timestamp,ticker,type,strike,expiryclose,volume,transactions,invested,break_even
summary(present only when--summaryis 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 APIsource: "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_KEYenvironment 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.
FAQ
What does the whale-hunting skill do?
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.
How do I install whale-hunting?
Run npx skills add https://github.com/staskh/trading_skills --skill whale-hunting 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/whale-hunting/ (personal) or .claude/skills/whale-hunting/ (project).
Which AI agents can use whale-hunting?
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 whale-hunting 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 whale-hunting?
It is published by staskh in staskh/trading_skills. It has 83 recorded installs.
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