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 yennanliu/InvestSkill --skill institutional-ownershipgit clone --depth 1 https://github.com/yennanliu/InvestSkillWrote 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/yennanliu/investskill/institutional-ownership)<a href="https://agentmods.dev/skills/yennanliu/investskill/institutional-ownership"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/institutional-ownership/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/yennanliu/investskill/institutional-ownership"><img src="https://agentmods.dev/badge/skills/yennanliu/investskill/institutional-ownership.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00015 | $0.04900 |
| Opus 5 | $0.00008 | $0.02450 |
| Sonnet 5 | $0.00003 | $0.00980 |
| Haiku 4.5 | $0.00002 | $0.00490 |
Grade A, and why
institutional-ownership 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 538 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Institutional Ownership Analysis
⚠️ Data Verification — Do This Before Any Analysis
Before running any analysis, always retrieve the latest market data for the ticker:
- Fetch current price — use web search or ask the user for the live price, 52-week range, and market cap. Never assume a price from training data.
- Confirm key figures — recent earnings, revenue, key ratios (P/E, P/S, etc.) as applicable to this skill.
- State your data source — note where the numbers came from (e.g., "Google Finance, June 19 2026") at the top of the output.
- Flag stale data explicitly — if live data is unavailable, display this warning before proceeding:
⚠️ Live data unavailable. The following analysis uses training-data estimates which may be significantly out of date. Verify all prices and metrics before making any decisions.
Never silently substitute training-data estimates for current prices. When in doubt, ask the user to paste the latest quote.
Comprehensive analysis of institutional investor holdings to identify "smart money" trends, ownership concentration, and investment signals from SEC 13F filings.
Analysis Framework
1. Institutional Ownership Overview
Provide current snapshot of institutional holdings:
Aggregate Statistics
- Total institutional ownership: [%] of shares outstanding
- Number of institutional holders: [N]
- Total shares held by institutions: [Number] shares
- Total value held: $[Amount]
- Float ownership by institutions: [%] (excl. insider holdings)
Ownership Trend (4 Quarters)
Quarter Institutional % # of Holders Change from Prior
Q4 2024 73.2% 850 +1.5%
Q3 2024 71.7% 832 +0.8%
Q2 2024 70.9% 815 -0.3%
Q1 2024 71.2% 809 +2.1%
Trend Interpretation
- Increasing ownership: Growing institutional interest = Bullish
- Stable ownership: Maintained confidence = Neutral to Bullish
- Decreasing ownership: Distribution or loss of confidence = Bearish
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.
- 10d ago First seen · 538 lines · 15 tokens per session scan A db6527cfb2f0
institutional-ownership is a skill published in the GitHub repository yennanliu/InvestSkill (206 stars, last pushed today), licensed MIT. It adds 15 tokens to every session and 4,900 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
dcf-model
DCF valuation: free cash flow projections, WACC, terminal value, sensitivity analysis.
initiating-coverage
Full equity research initiation: company research, financial model, valuation, charts, 30-50 page report.
comps-analysis
Comparable company analysis: operating metrics, valuation multiples, peer benchmarking.
ui-design
Design-quality reference for financial-research visual output: typography, color, composition, and avoiding generic AI aesthetics.
onboarding
First-time user onboarding to set up investment profile, watchlists, portfolio, and preferences.
chart-annotation
Draw price lines, trendlines, zones, and event markers directly on a stock's price chart — reach for it whenever you'd otherwise describe a level, pattern, or event in prose. Renders live on MarketView and as a clickable preview card in any other chat.