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Agent Skill · 研究检索

institutional-flow-tracker(机构流程追踪器)

institutional-flow-tracker 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

institutional-flow-tracker 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 1,204。

总安装 110,301周安装 4,738GitHub Stars 5下载 38,662核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.1.0

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:institutional-flow-tracker(机构流程追踪器)
来源仓库:https://github.com/veeramanikandanr48/institutional-flow-tracker
安装命令:
openclaw skills install institutional-flow-tracker
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install institutional-flow-tracker

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

使用此技能可以使用 13F 备案数据跟踪机构投资者所有权变化和投资组合流动。分析对冲基金、共同基金和其他机构持有人,以确定具有大量智能资金积累或分配的股票。通过跟踪经验丰富的投资者如何配置资金,帮助在重大波动之前发现股票。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install institutional-flow-tracker;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

institutional-flow-tracker 怎么安装?

在终端执行 openclaw skills install institutional-flow-tracker。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

institutional-flow-tracker 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

institutional-flow-tracker 需要什么权限?

权限级别是接触敏感数据。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。

institutional-flow-tracker 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

institutional-flow-tracker 用的人多吗?

公开数据是累计安装 110,301 次,近一周安装 4,738 次,下载 38,662 次,GitHub 5 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

institutional-flow-tracker 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
institutional-flow-tracker

机构流程追踪器 · 本页

110,3015接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
institutional-flow-tracker
description
Use this skill to track institutional investor ownership changes and portfolio flows using 13F filings data. Analyzes hedge funds, mutual funds, and other institutional holders to identify stocks with significant smart money accumulation or distribution. Helps discover stocks before major moves by following where sophisticated investors are deploying capital.

Institutional Flow Tracker

Overview

This skill tracks institutional investor activity through 13F SEC filings to identify "smart money" flows into and out of stocks. By analyzing quarterly changes in institutional ownership, you can discover stocks that sophisticated investors are accumulating before major price moves, or identify potential risks when institutions are reducing positions.

Key Insight: Institutional investors (hedge funds, pension funds, mutual funds) manage trillions of dollars and conduct extensive research. Their collective buying/selling patterns often precede significant price movements by 1-3 quarters.

When to Use This Skill

Use this skill when:

  • Validating investment ideas (checking if smart money agrees with your thesis)
  • Discovering new opportunities (finding stocks institutions are accumulating)
  • Risk assessment (identifying stocks institutions are exiting)
  • Portfolio monitoring (tracking institutional support for your holdings)
  • Following specific investors (tracking Warren Buffett, Cathie Wood, etc.)
  • Sector rotation analysis (identifying where institutions are rotating capital)

Do NOT use when:

  • Seeking real-time intraday signals (13F data has 45-day reporting lag)
  • Analyzing micro-cap stocks (<$100M market cap with limited institutional interest)
  • Looking for short-term trading signals (<3 months horizon)

Data Sources & Requirements

Required: FMP API Key

This skill uses Financial Modeling Prep (FMP) API to access 13F filing data:

Setup:

# Set environment variable (preferred)
export FMP_API_KEY=your_key_here

# Or provide when running scripts
python3 scripts/track_institutional_flow.py --api-key YOUR_KEY

API Tier Requirements:

  • Free Tier: 250 requests/day (sufficient for analyzing 20-30 stocks quarterly)
  • Paid Tiers: Higher limits for extensive screening

13F Filing Schedule:

  • Filed quarterly within 45 days after quarter end
  • Q1 (Jan-Mar): Filed by mid-May
  • Q2 (Apr-Jun): Filed by mid-August
  • Q3 (Jul-Sep): Filed by mid-November
  • Q4 (Oct-Dec): Filed by mid-February

Analysis Workflow

Step 1: Identify Stocks with Significant Institutional Changes

Execute the main screening script to find stocks with notable institutional activity:

Quick scan (top 50 stocks by institutional change):

python3 institutional-flow-tracker/scripts/track_institutional_flow.py \
  --top 50 \
  --min-change-percent 10

Sector-focused scan:

python3 institutional-flow-tracker/scripts/track_institutional_flow.py \
  --sector Technology \
  --min-institutions 20

Custom screening:

python3 institutional-flow-tracker/scripts/track_institutional_flow.py \
  --min-market-cap 2000000000 \
  --min-change-percent 15 \
  --top 100 \
  --output institutional_flow_results.json

Output includes:

  • Stock ticker and company name
  • Current institutional ownership % (of shares outstanding)
  • Quarter-over-quarter change in shares held
  • Number of institutions holding
  • Change in number of institutions (new buyers vs sellers)
  • Top institutional holders
  • Aggregate dollar value change

Step 2: Deep Dive on Specific Stocks

For detailed analysis of a specific stock's institutional ownership:

python3 institutional-flow-tracker/scripts/analyze_single_stock.py AAPL

This generates:

  • Historical institutional ownership trend (8 quarters)
  • List of all institutional holders with position changes
  • Concentration analysis (top 10 holders' % of total institutional ownership)
  • New positions vs increased vs decreased vs closed positions
  • Quarterly flow chart (net shares added/removed)
  • Comparison to sector average institutional ownership

Key metrics to evaluate:

  • Ownership %: Higher institutional ownership (>70%) = more stability but limited upside
  • Ownership Trend: Rising ownership = bullish, falling = bearish
  • Concentration: High concentration (top 10 > 50%) = risk if they sell
  • Quality of Holders: Presence of quality long-term investors (Berkshire, Fidelity) vs momentum funds

Step 3: Track Specific Institutional Investors

Follow the portfolio moves of specific hedge funds or investment firms:

# Track Warren Buffett's Berkshire Hathaway
python3 institutional-flow-tracker/scripts/track_institution_portfolio.py \
  --cik 0001067983 \
  --name "Berkshire Hathaway"

# Track Cathie Wood's ARK Investment Management
python3 institutional-flow-tracker/scripts/track_institution_portfolio.py \
  --cik 0001579982 \
  --name "ARK Investment Management"

CIK (Central Index Key) lookup:

  • Search at: https://www.sec.gov/cgi-bin/browse-edgar
  • Or use FMP API institutional search

Analysis output:

  • Current portfolio holdings (top 50 positions)
  • New positions added this quarter
  • Positions completely sold
  • Largest increases/decreases in existing positions
  • Portfolio concentration and sector allocation changes
  • Historical performance of their top picks

Step 4: Interpretation and Action

Read the references for interpretation guidance:

  • references/13f_filings_guide.md - Understanding 13F data and limitations
  • references/institutional_investor_types.md - Different investor types and their strategies
  • references/interpretation_framework.md - How to interpret institutional flow signals

Signal Strength Framework:

Strong Bullish (Consider buying):

  • Institutional ownership increasing >15% QoQ
  • Number of institutions increasing >10%
  • Quality long-term investors adding positions
  • Low current ownership (<40%) with room to grow
  • Accumulation happening across multiple quarters

Moderate Bullish:

  • Institutional ownership increasing 5-15% QoQ
  • Mix of new buyers and sellers, net positive
  • Current ownership 40-70%

Neutral:

  • Minimal change in ownership (<5%)
  • Similar number of buyers and sellers
  • Stable institutional base

Moderate Bearish:

  • Institutional ownership decreasing 5-15% QoQ
  • More sellers than buyers
  • High ownership (>80%) limiting new buyers

Strong Bearish (Consider selling/avoiding):

  • Institutional ownership decreasing >15% QoQ
  • Number of institutions decreasing >10%
  • Quality investors exiting positions
  • Distribution happening across multiple quarters
  • Concentration risk (top holder selling large position)

Step 5: Portfolio Application

For new positions:

  1. Run institutional analysis on your stock idea
  2. Look for confirmation (institutions also accumulating)
  3. If strong bearish signals, reconsider or reduce position size
  4. If strong bullish signals, gain confidence in thesis

For existing holdings:

  1. Quarterly review after 13F filing deadlines
  2. Monitor for distribution (early warning system)
  3. If institutions are exiting, re-evaluate your thesis
  4. Consider trimming if widespread institutional selling

Screening workflow integration:

  1. Use Value Dividend Screener or other screeners to find candidates
  2. Run Institutional Flow Tracker on top candidates
  3. Prioritize stocks with institutional accumulation
  4. Avoid stocks with institutional distribution

Output Format

All analysis generates structured markdown reports saved to repository root:

Filename convention: institutional_flow_analysis_<TICKER/THEME>_<DATE>.md

Report sections:

  1. Executive Summary (key findings)
  2. Institutional Ownership Trend (current vs historical)
  3. Top Holders and Changes
  4. New Buyers vs Sellers
  5. Concentration Analysis
  6. Interpretation and Recommendations
  7. Data Sources and Timestamp

Limitations and Caveats

Data Lag:

  • 13F filings have 45-day reporting delay
  • Positions may have changed since filing date
  • Use as confirming indicator, not leading signal

Coverage:

  • Only institutions managing >$100M are required to file
  • Excludes individual investors and smaller funds
  • International institutions may not file 13F

Reporting Rules:

  • Only long equity positions reported (no shorts, options, bonds)
  • Holdings as of quarter-end snapshot
  • Some positions may be confidential (delayed reporting)

Interpretation:

  • Correlation ≠ causation (stocks can fall despite institutional buying)
  • Consider overall market environment and fundamentals
  • Combine with technical analysis and other skills

Advanced Use Cases

Insider + Institutional Combo:

  • Look for stocks where both insiders AND institutions are buying
  • Particularly powerful signal when aligned

Sector Rotation Detection:

  • Track aggregate institutional flows by sector
  • Identify early rotation trends before they appear in price

Contrarian Plays:

  • Find quality stocks institutions are selling (potential value)
  • Requires strong fundamental conviction

Smart Money Validation:

  • Before major position, check if smart money agrees
  • Gain confidence or find overlooked risks

References

The references/ folder contains detailed guides:

  • 13f_filings_guide.md - Comprehensive guide to 13F SEC filings, what they include, reporting requirements, and data quality considerations
  • institutional_investor_types.md - Different types of institutional investors (hedge funds, mutual funds, pension funds, etc.), their typical strategies, and how to interpret their moves
  • interpretation_framework.md - Detailed framework for interpreting institutional ownership changes, signal quality assessment, and integration with other analysis

Script Parameters

track_institutional_flow.py

Main screening script for finding stocks with significant institutional changes.

Required:

  • --api-key: FMP API key (or set FMP_API_KEY environment variable)

Optional:

  • --top N: Return top N stocks by institutional change (default: 50)
  • --min-change-percent X: Minimum % change in institutional ownership (default: 10)
  • --min-market-cap X: Minimum market cap in dollars (default: 1B)
  • --sector NAME: Filter by specific sector
  • --min-institutions N: Minimum number of institutional holders (default: 10)
  • --output FILE: Output JSON file path (default: institutional_flow_results.json)
  • --sort-by FIELD: Sort by 'ownership_change', 'institution_count_change', 'dollar_value_change'

analyze_single_stock.py

Deep dive analysis on a specific stock's institutional ownership.

Required:

  • Ticker symbol (positional argument)
  • --api-key: FMP API key (or set FMP_API_KEY environment variable)

Optional:

  • --quarters N: Number of quarters to analyze (default: 8, i.e., 2 years)
  • --output FILE: Output markdown report path
  • --compare-to TICKER: Compare institutional ownership to another stock

track_institution_portfolio.py

Track a specific institutional investor's portfolio changes.

Required:

  • --cik CIK: Central Index Key of the institution
  • --name NAME: Institution name for report
  • --api-key: FMP API key (or set FMP_API_KEY environment variable)

Optional:

  • --top N: Show top N holdings (default: 50)
  • --min-position-value X: Minimum position value to include (default: 10M)
  • --output FILE: Output markdown report path

Integration with Other Skills

Value Dividend Screener + Institutional Flow:

1. Run Value Dividend Screener to find candidates
2. For each candidate, check institutional flow
3. Prioritize stocks with rising institutional ownership

US Stock Analysis + Institutional Flow:

1. Run comprehensive fundamental analysis
2. Validate with institutional ownership trends
3. If institutions are selling, investigate why

Portfolio Manager + Institutional Flow:

1. Fetch current portfolio via Alpaca
2. Run institutional analysis on each holding
3. Flag positions with deteriorating institutional support
4. Consider rebalancing away from distribution

Technical Analyst + Institutional Flow:

1. Identify technical setup (e.g., breakout)
2. Check if institutional buying confirms
3. Higher conviction if both align

Best Practices

  1. Quarterly Reviews: Set calendar reminders for 13F filing deadlines
  2. Multi-Quarter Trends: Look for sustained trends (3+ quarters), not one-time changes
  3. Quality Over Quantity: Berkshire adding > 100 small funds adding
  4. Context Matters: Rising ownership in a falling stock may be value investors catching a falling knife
  5. Combine Signals: Never use institutional flow in isolation
  6. Update Your Data: Re-run analysis each quarter as new 13Fs are filed

Support & Resources

  • FMP API Documentation: https://financialmodelingprep.com/developer/docs
  • SEC 13F Filings Database: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&type=13F
  • Institutional Investor Database: https://whalewisdom.com (free tier available)

Note: This skill is designed for long-term investors (3-12 month horizon). For short-term trading, combine with technical analysis and other momentum indicators.

平台分布

OpenClaw

70.86%
按下载量换算27,396

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

接触敏感数据

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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