Vibe-Trading is a personal trading agent that gives an AI system tools for market analysis, algorithmic trading, backtesting, and related workflows. It is for users who want an agent to research and evaluate trading strategies or manage simulated and other trading activities. The catalogue contains skills that expose these trading capabilities to compatible agents.
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 HKUDS/Vibe-Trading --skill correlation-regimegit clone --depth 1 https://github.com/HKUDS/Vibe-TradingWrote 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/hkuds/vibe-trading/correlation-regime)<a href="https://agentmods.dev/skills/hkuds/vibe-trading/correlation-regime"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/correlation-regime/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/hkuds/vibe-trading/correlation-regime"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/correlation-regime.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- 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 | $0.00070 | $0.05306 |
| Opus 5 | $0.00035 | $0.02653 |
| Sonnet 5 | $0.00014 | $0.01061 |
| Haiku 4.5 | $0.00007 | $0.00531 |
Grade A, and why
correlation-regime 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 — 505 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Correlation-Regime Detection and Crisis Attribution
Overview
The correlation-analysis skill answers "how correlated are these assets?" — a snapshot.
This skill answers the temporal questions a snapshot cannot:
- When did the market fuse into one highly-correlated bloc, and when did it release? (Mode 1 — regime detection)
- What does a fused regime mean for position sizing? (Mode 2 — risk context)
- Who moved first when a crisis broke — is there a nameable trigger asset? (Mode 3 — first-mover attribution)
- Who quietly rewired their relationship to the rest of the market, even without a violent move? (Mode 4 — rewiring leaderboard)
The methodology comes from an open-source streaming pipeline (see References) whose public repository pins the regime machinery's math and an eight-event historical replay regression (COVID, May-2021, China ban, Nov-2021 top, LUNA, FTX, SVB, yen-carry — 17 crypto symbols, 1-minute bars) that its CI reproduces bit-for-bit. The finer-grained numbers quoted in this skill — 13 fused/defused regime cycles on the continuous 2020–2024 tape at a ~0.008/day calm false-alarm rate, and zero wrong culprit names across 10 labeled crises (2 held out-of-sample), including naming FTT roughly two days before the November 2022 collapse — are the author's unpublished internal replays on that same pipeline and are not independently verifiable. All of it is historical replay, never live results, and the method is market-agnostic even though the validation tape is crypto.
What this skill is NOT: a trade-timing signal. The same validation program tested regime-based exits head-to-head against a plain price stop and lost — correlation regimes cannot time tops, and the give-up cost of selling into a crash is a property of the tape, not of any signal. Use these modes for risk context, monitoring, and post-hoc attribution; never present them as buy/sell triggers.
Mode 1: Correlation-Regime Detection (Edge Density + Hysteresis)
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 · 505 lines · 70 tokens per session scan A a77e8d994c3a
correlation-regime is a skill published in the GitHub repository HKUDS/Vibe-Trading (33,085 stars, last pushed today), licensed MIT. It adds 70 tokens to every session and 5,306 once invoked, about $0.0003 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.
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