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whale-hunting捕鲸

Agent Skill

whale-hunting 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

269

周安装

11

GitHub Stars

131

下载量

86
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:whale-hunting(捕鲸)
来源仓库:https://github.com/staskh/trading_skills
仓库路径:skills/whale-hunting
安装命令:
npx skills add https://github.com/staskh/trading_skills --skill whale-hunting
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/staskh/trading_skills --skill whale-hunting

简介

追踪股票期权大宗交易中的机构鲸鱼活动信号。

  • 聚合每日期权数据,识别高置信度的买卖动向。
  • 支持按股票代码、日期或波动阈值筛选事件记录。
  • 依赖 Massive API 密钥获取实时交易流数据。
  • 结果仅供研究参考,不构成投资决策依据。whale-hunting 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Whale Hunting

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

  1. Crude scan (Yahoo Finance) — finds contracts with anomalous daily investment vs the rest of the chain.
  2. 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)TickerTypeStrikeExpiry# EventsTotal InvestedBreak 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.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.5%
按下载量换算31

Claude

29.3%
按下载量换算25

Cursor

21.32%
按下载量换算18

Gemini CLI

11.2%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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