Finance Skills is a collection of agent skills for financial analysis and trading, covering activities such as company valuation, earnings research, market analysis, and options calculations. It is for users who want coding agents to perform structured finance workflows, and the catalogue contains its skills, plugins, instructions, and MCP integration.
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 himself65/finance-skills --skill etf-premiumgit clone --depth 1 https://github.com/himself65/finance-skillsWrote 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/himself65/finance-skills/etf-premium)<a href="https://agentmods.dev/skills/himself65/finance-skills/etf-premium"><img src="https://agentmods.dev/badge/skills/himself65/finance-skills/etf-premium/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/himself65/finance-skills/etf-premium"><img src="https://agentmods.dev/badge/skills/himself65/finance-skills/etf-premium.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 | $0.00223 | $0.05055 |
| Opus 5 | $0.00112 | $0.02527 |
| Sonnet 5 | $0.00045 | $0.01011 |
| Haiku 4.5 | $0.00022 | $0.00505 |
Grade A, and why
etf-premium scanned grade A with 1 finding 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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance", "pandas", "numpy"]) How it starts
The opening of the file, as written. The whole thing — 402 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ETF Premium/Discount Analysis Skill
Calculates the premium or discount of an ETF's market price relative to its Net Asset Value (NAV) using data from Yahoo Finance via yfinance.
Why this matters: An ETF's market price can diverge from the value of its underlying holdings (NAV). When you buy at a premium, you're overpaying relative to the assets; at a discount, you're getting a bargain. This divergence is typically small for liquid US equity ETFs but can be significant for bond ETFs, international ETFs, leveraged/inverse products, and crypto ETFs — especially during periods of market stress.
Important: For research and educational purposes only. Not financial advice. yfinance is not affiliated with Yahoo, Inc.
Step 1: Ensure Dependencies Are Available
Current environment status:
!`python3 -c "exec('try:\n import yfinance, pandas, numpy\n print(f\'yfinance={yfinance.__version__} pandas={pandas.__version__} numpy={numpy.__version__}\')\nexcept Exception:\n print(\'DEPS_MISSING\')')"`
If DEPS_MISSING, install required packages:
import subprocess, sys
subprocess.check_call([sys.executable, "-m", "pip", "install", "-q", "yfinance", "pandas", "numpy"])
If already installed, skip and proceed.
Step 2: Route to the Correct Sub-Skill
Classify the user's request and jump to the matching section. If the user asks a general question about an ETF's premium or discount without specifying a particular analysis type, default to Sub-Skill A (Single ETF Snapshot).
| User Request | Route To | Examples |
|---|---|---|
| Single ETF premium/discount | Sub-Skill A: Single ETF Snapshot | "is SPY at a premium?", "AGG premium to NAV", "BITO premium" |
| Compare multiple ETFs | Sub-Skill B: Multi-ETF Comparison | "compare bond ETF discounts", "which has bigger premium IBIT or BITO", "rank these ETFs by premium" |
| Screener / find extreme premiums | Sub-Skill C: Premium Screener | "which ETFs have biggest discount", "find ETFs trading below NAV", "premium screener" |
| Deep analysis with context | Sub-Skill D: Premium Deep Dive | "why is HYG at a discount", "is ARKK premium normal", "ETF premium analysis with context" |
| Sudden premium surge / gamma squeeze | Sub-Skill E: Premium Surge Decomposition | "why did KWEB jump 13% today", "is this ETF rally driven by gamma", "decompose today's ETF move", "dealer GEX for SOXL", "how long until the premium converges" |
What ships with it
3 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.
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 · 402 lines · 223 tokens per session scan A 2feb9285691b
etf-premium is a skill published in the GitHub repository himself65/finance-skills (3,302 stars, last pushed 13d ago), licensed MIT. It adds 223 tokens to every session and 5,055 once invoked, about $0.0011 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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