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coderwpf

QMT

by coderwpf · GitHub ↗ · v1.0.3 · MIT-0
cross-platform ✓ Security Clean
608
Downloads
5
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0
Active Installs
4
Versions
Install in OpenClaw
/install qmt
Description
QMT迅投量化交易终端 - 内置Python策略开发、回测引擎和实盘交易,支持中国证券市场全品种。
Usage Guidance
This bundle is documentation and examples for the QMT / xtquant trading client and appears coherent. Before using: (1) do not run example code against a real brokerage account — test with a sandbox or paper/trading-enabled test account; (2) review the xtquant package source and only install it from a trusted source (pip package provenance); (3) be aware the demos assume a local QMT/miniQMT client (Windows) and local data paths; (4) never paste real account credentials into code you did not audit, and confirm broker permissions before enabling automated orders.
Capability Analysis
Type: OpenClaw Skill Name: qmt Version: 1.0.3 The skill bundle provides a comprehensive integration for the QMT (Quant Market Trading) platform, a legitimate quantitative trading terminal. The content consists of extensive documentation (SKILL.md, xtdata.md, xttrader.md), API references, and a connectivity demo (demo.py) for the official xtquant SDK. The instructions for the AI agent focus on best practices for financial data handling, such as data validation and multi-step analysis, and do not contain any evidence of malicious intent, data exfiltration, or harmful prompt injections.
Capability Assessment
Purpose & Capability
Name/description claim a QMT trading terminal and the package files, requirements (python3, xtquant) and examples all match that purpose. Required binaries/env/configs are proportional to a Python trading SDK that connects to a local QMT/miniQMT client.
Instruction Scope
SKILL.md and included demos contain direct examples of trading calls (order_shares, cancel, connect/subscribe) and reference local QMT paths and account IDs. This is expected for a trading integration, but those instructions, if executed, will interact with brokerage APIs and can place real trades — the agent/docs do not themselves request secrets but they do assume access to a running QMT/miniQMT client and broker-enabled accounts.
Install Mechanism
No install spec is provided (instruction-only plus docs). requirements.txt lists xtquant and numpy which is appropriate for the described SDK; nothing is downloaded from arbitrary URLs and no archive extraction is present.
Credentials
The skill does not request environment variables, secrets, or unusual config paths. It does expect local QMT/miniQMT installation directories and account identifiers to be used by the examples — those are reasonable for a trading SDK but are sensitive (account IDs, broker access) and should be handled carefully by the user.
Persistence & Privilege
Skill is not always-enabled and does not request persistent system privileges or attempt to modify other skills. It is user-invocable and may be invoked autonomously by the agent (platform default), which is normal for skills.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install qmt
  3. After installation, invoke the skill by name or use /qmt
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
- 新增 demo_project 示例目录,包含 demo.py 示例脚本和 README.md 说明文件。 - 便于用户快速参考和上手 QMT 策略开发。
v1.0.2
**Summary:** This version updates the documentation to Simplified Chinese and enriches advanced strategy examples. - Documentation (SKILL.md) fully translated from English to Simplified Chinese. - Expanded advanced strategy examples, adding a complete RSI strategy and a full multi-stock rotation strategy. - No code or functional changes to the skill itself.
v1.0.1
**Version 1.1.0 update summary: Refined documentation and expanded user guidance.** - Added detailed documentation files: README.md, QUICK_REFERENCE.md, xtdata.md, xttrader.md, and requirements.txt. - Expanded and clarified strategy examples, operation modes, and API usage in core docs. - Enhanced comparisons among QMT, miniQMT, and Ptrade platforms. - Improved data coverage and feature explanation for Chinese securities instruments. - Added notes on advanced usage, multi-stock strategy examples, and practical tips. - No changes to the codebase; content/documentation update only.
v1.0.0
QMT skill initial release: - Professional quantitative trading platform for Chinese securities with built-in Python strategy development, backtesting, and live trading. - Supports full desktop client (QMT) and lightweight mode (miniQMT). - Provides event-driven Python strategy framework, historical and real-time data access, and built-in order functions. - Includes backtesting engine with customizable parameters and metrics. - Covers stocks, indices, futures, options, ETFs, bonds, and financial data. - Documentation and example strategies included.
Metadata
Slug qmt
Version 1.0.3
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 4
Frequently Asked Questions

What is QMT?

QMT迅投量化交易终端 - 内置Python策略开发、回测引擎和实盘交易,支持中国证券市场全品种。 It is an AI Agent Skill for Claude Code / OpenClaw, with 608 downloads so far.

How do I install QMT?

Run "/install qmt" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is QMT free?

Yes, QMT is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does QMT support?

QMT is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created QMT?

It is built and maintained by coderwpf (@coderwpf); the current version is v1.0.3.

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