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 skloxo/TideTrading --skill volatilitygit clone --depth 1 https://github.com/skloxo/TideTradingWrote 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/skloxo/tidetrading/volatility)<a href="https://agentmods.dev/skills/skloxo/tidetrading/volatility"><img src="https://agentmods.dev/badge/skills/skloxo/tidetrading/volatility/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/skloxo/tidetrading/volatility"><img src="https://agentmods.dev/badge/skills/skloxo/tidetrading/volatility.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 | $0.00029 | $0.00505 |
| Opus 5 | $0.00015 | $0.00253 |
| Sonnet 5 | $0.00006 | $0.00101 |
| Haiku 4.5 | $0.00003 | $0.00051 |
Grade A, and why
volatility 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 7d 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
100% identical to volatility — 0 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.
What it actually says
Volatility Strategy
Purpose
Uses percentile ranking of historical volatility (HV) to capture volatility mean reversion: build positions in low-volatility regimes while waiting for volatility expansion, and exit or short in high-volatility regimes to capture contraction.
Signal Logic
- Compute HV: annualized standard deviation of returns over the past
hv_windowdays - Percentile ranking: percentile position of HV within the past
lookbackdays (0-100) - Signal generation:
- Percentile <
low_pct→ go long (volatility is low, waiting for expansion) - Percentile >
high_pct→ exit / go short (volatility is high, waiting for contraction) - Middle region → keep the current position
- Percentile <
Key Implementation Details
- HV =
returns.rolling(hv_window).std() * sqrt(252)(annualized) - Percentile =
hv.rolling(lookback).rank(pct=True) * 100 - For cryptocurrencies, use 365 instead of 252 as the annualization factor
Parameters
| Parameter | Default | Description |
|---|---|---|
| hv_window | 20 | Historical volatility calculation window |
| lookback | 120 | Lookback period for percentile ranking |
| low_pct | 20.0 | Low-volatility threshold (percentile) |
| high_pct | 80.0 | High-volatility threshold (percentile) |
| annualize | 252 | Annualization factor (252 for China A-shares, 365 for crypto) |
Common Pitfalls
- Before the lookback window is filled, there is not enough data to compute percentiles, so the signal should be 0 (
fillna) - Volatility is not direction. Going long in low-volatility regimes does not guarantee price appreciation; it only means volatility expansion is statistically more likely
- Cryptocurrencies trade 7x24, so
annualizeshould be set to 365
Dependencies
pip install pandas numpy
Signal Convention
1= long (low-volatility regime),-1= short (high-volatility regime),0= stand aside
What ships with it
1 file 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.
- 7d ago First seen · 52 lines · 29 tokens per session scan A 28f512107497
volatility is a skill published in the GitHub repository skloxo/TideTrading (10 stars, last pushed 4d ago), licensed MIT. It adds 29 tokens to every session and 505 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to volatility, differing in 0 lines, and is treated as a copy.
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