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 event-drivengit 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/event-driven)<a href="https://agentmods.dev/skills/hkuds/vibe-trading/event-driven"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/event-driven/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/event-driven"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/event-driven.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00038 | $0.02086 |
| Opus 5 | $0.00019 | $0.01043 |
| Sonnet 5 | $0.00008 | $0.00417 |
| Haiku 4.5 | $0.00004 | $0.00209 |
Grade A, and why
event-driven 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- event-driven — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Event-Driven Strategy
Purpose
Uses event information such as news, announcements, and macro policy updates. The LLM analyzes sentiment and impact magnitude to generate event-driven trading signals. Event data is managed in CSV format, and technical signals are combined with event signals through weighted aggregation to form the final trading decision.
Workflow
- Data collection: use the
read_urltool to fetch the full text of news and announcements - LLM analysis: the LLM reads the news and scores it from
-1.0to1.0with a standardized prompt (extremely bearish to extremely bullish) - Generate the event CSV: write data in the
date,event_type,score,source,summaryschema - Signal aggregation:
signal_engine.pyreads the event CSV, applies time decay, and combines it with the technical signal
Key principle: the event CSV is the data layer, and signal_engine.py is the logic layer. Keep them decoupled.
Event CSV Schema
date,event_type,score,source,summary
2024-01-15,earnings,0.8,read_url,Q4 revenue beat expectations by 30%
2024-01-20,macro,-0.5,read_url,Central bank raised rates by 25bp
2024-02-01,policy,0.3,read_url,New-energy subsidies extended
2024-02-10,sentiment,-0.7,read_url,Bearish sentiment surged on social media
2024-03-05,insider,0.4,read_url,CEO bought 5 million shares
Field descriptions:
| Field | Type | Description |
|---|---|---|
| date | str (YYYY-MM-DD) |
Date when the event became knowable (publication date, not occurrence date. If released after market close → use the next trading day) |
| event_type | str | earnings / macro / policy / sentiment / insider / technical_break |
| score | float | -1.0 ~ 1.0 (standardized LLM score) |
| source | str | Data-source tag (such as read_url) |
| summary | str | Event summary (one sentence, no commas) |
Event Type Details
| Type | Meaning | Typical Impact | Duration |
|---|---|---|---|
| earnings | Earnings release | Short-term shock | 1-5 days |
| macro | Macro data / central-bank policy | Medium-term impact | 5-20 days |
| policy | Industry policy / regulatory change | Long-term impact | 20-60 days |
| sentiment | Market sentiment / public opinion | Short-term shock | 1-3 days |
| insider | Insider trading / block trade | Medium-term signal | 5-10 days |
| technical_break | Break of a key technical level | Short-term catalyst | 1-5 days |
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.
- 9d ago First seen · 181 lines · 38 tokens per session scan A 169e5bfab7e8
event-driven is a skill published in the GitHub repository HKUDS/Vibe-Trading (33,017 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 2,086 once invoked, about $0.0002 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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