Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add nicepkg/ai-workflow --skill institutional-flow-trackergit clone --depth 1 https://github.com/nicepkg/ai-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nicepkg/ai-workflow/institutional-flow-tracker)<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/institutional-flow-tracker"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/institutional-flow-tracker/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/institutional-flow-tracker"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/institutional-flow-tracker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00064 | $0.02853 |
| Opus 5.5 | $0.00026 | $0.01141 |
| Sonnet 5.5 | $0.00013 | $0.00571 |
| Haiku 4.5 | $0.00006 | $0.00285 |
Grade A, and why
institutional-flow-tracker scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
83% identical to institutional-flow-tracker — 110 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- README.md 12 KB
- references/13f_filings_guide.md 12 KB
- references/institutional_investor_types.md 19 KB
- references/interpretation_framework.md 20 KB
- scripts/analyze_single_stock.py 17 KB runs code
- scripts/track_institution_portfolio.py 3.6 KB runs code
- scripts/track_institutional_flow.py 15 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 358 lines · 64 tokens per session scan A a42d5f48ff70
institutional-flow-tracker is a skill published in the GitHub repository nicepkg/ai-workflow (288 stars, last pushed 9mo ago), licensed MIT. It adds 64 tokens to every session and 2,853 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 83% identical to institutional-flow-tracker, differing in 110 lines, and is treated as a copy.
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