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 vnpy-exportgit 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/vnpy-export)<a href="https://agentmods.dev/skills/hkuds/vibe-trading/vnpy-export"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/vnpy-export/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/vnpy-export"><img src="https://agentmods.dev/badge/skills/hkuds/vibe-trading/vnpy-export.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 178 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
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 | $0.00040 | $0.03004 |
| Opus 5 | $0.00020 | $0.01502 |
| Sonnet 5 | $0.00008 | $0.00601 |
| Haiku 4.5 | $0.00004 | $0.00300 |
Grade A, and why
vnpy-export 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 5d 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:
- vnpy-export — 100% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
This skill translates a Vibe-Trading strategy into a vnpy CtaTemplate subclass .py file
that can be loaded directly into the vnpy CTA Strategy App for live trading or vnpy backtesting.
Output file: artifacts/vnpy_strategy/<StrategyName>Strategy.py (inside the run directory).
vnpy is the most widely-used open-source quant framework in mainland China (39k+ GitHub stars).
Use this skill when the user asks to export to vnpy, requests a /vnpy command, or wants to
run a Vibe-Trading strategy inside vnpy's CTA backtester or live trading engine.
Workflow: Export from Backtest Run
load_skill("vnpy-export")— read this guideread_file("config.json")— extract instrument, dates, parameters, intervalread_file("code/signal_engine.py")— understand the Python signal logic- Determine asset class from
config.json→ choose correct CtaTemplate convention (see below) - Translate signal logic to CtaTemplate using the reference tables
write_file("artifacts/vnpy_strategy/<StrategyName>Strategy.py")— save the output- Return the class in a code block with setup instructions
Workflow: Generate from Description
load_skill("vnpy-export")— read this guide- Write a CtaTemplate class from the user's strategy description
write_file("artifacts/vnpy_strategy/<StrategyName>Strategy.py")— save the output- Return the class with setup and usage instructions
Asset Class Conventions
vnpy uses the same CtaTemplate base class for all asset types, but parameter conventions differ:
| Asset Class | Instrument Example | vt_symbol Format |
Position Unit |
|---|---|---|---|
| A-share stock | Ping An Bank | 000001.SZSE |
shares (整手, min 100) |
| Futures | IF2406 | IF2406.CFFEX |
lots |
| Crypto | BTC/USDT | BTC/USDT.BINANCE |
coin units |
For stocks: use buy / sell only (no short selling unless margin account).
For futures / crypto: use all four directions — buy, sell, short, cover.
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.
- 5d ago First seen · 321 lines · 40 tokens per session scan A 155d427fa84d
vnpy-export is a skill published in the GitHub repository HKUDS/Vibe-Trading (33,017 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 3,004 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 2026-09-03.
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