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Install in OpenClaw
/install xtquant
Description
XtQuant QMT Python SDK - 集成行情数据(xtdata)和交易接口(xttrade)，支持A股、期货、期权等中国证券市场。
Usage Guidance
This appears to be documentation for the real xtquant Python SDK (which connects to a local MiniQMT/QMT trading client). Before installing or running it: 1) Verify the package source on PyPI and the vendor homepage (confirm package owner, checksums, or official repo) — the skill metadata shows small inconsistencies (version/owner IDs) that could indicate an unreviewed bundle. 2) Note the SDK expects a local MiniQMT client (Windows) and will interact with local trading data directories; only run it on a machine where you trust the broker client and where you are comfortable allowing trading operations. 3) Run pip install in a virtualenv or isolated environment and inspect the installed package code. 4) If you plan automation, confirm broker authentication is managed by MiniQMT (not provided to this skill) and avoid giving unrelated secrets to the agent. 5) If anything about ownership or download URLs looks unfamiliar, prefer obtaining the SDK directly from the vendor or an official repository and double-check the package signature/metadata.
Capability Analysis
Type: OpenClaw Skill
Name: xtquant
Version: 1.0.3
The xtquant skill bundle is a legitimate integration of the XtQuant QMT Python SDK for Chinese securities trading and market data. The bundle consists of comprehensive documentation (SKILL.md, xtdata.md, xttrader.md) and code examples for interacting with a local QMT/miniQMT terminal. The instructions provided for the AI agent focus on operational best practices such as data validation, error handling, and multi-step analysis. There are no signs of data exfiltration, malicious execution, or harmful prompt injection; the SDK's core functionality (connecting to a local TCP service and managing trading accounts) is consistent with its stated purpose.
Capability Assessment
Purpose & Capability
Name/description, README and SKILL.md consistently describe an xtquant SDK that provides market data and trading via a local MiniQMT/QMT client; required binary (python3) and pip install guidance are coherent with that purpose.
Instruction Scope
SKILL.md instructs the agent to pip install xtquant and to connect to a local MiniQMT/QMT client via TCP and to read MiniQMT data directories (e.g., userdata_mini). It does not request unrelated files or external endpoints beyond the vendor site and PyPI. However it assumes a Windows-local MiniQMT process — yet the skill has no OS restriction; the instructions also reference local filesystem paths which are environment-specific.
Install Mechanism
There is no built-in install spec (instruction-only). The docs tell users to pip install xtquant (PyPI) or download from the vendor site. That is expected for a Python SDK, but it means pip/network downloads will occur at install time; the homepage is a vendor site (thinktrader.net) rather than a well-known code repo, so users should verify the pip package source before installing.
Credentials
The skill does not request environment variables or credentials. Trading functionality relies on a local MiniQMT client and broker-side credentials configured in that client, which is proportionate to the stated trading purpose.
Persistence & Privilege
always:false and disable-model-invocation:false (normal). The skill does not request permanent platform privileges or attempt to modify other skills' configs.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install xtquant - After installation, invoke the skill by name or use
/xtquant - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
xtquant 1.0.3
- Added a demo_project directory with sample usage (README.md and demo.py).
- Updated documentation files (README.md, SKILL.md) for clarifications and improvements.
- Updated internal metadata files.
v1.0.2
Version 1.2.0
- Increased Chinese language usage in documentation, especially section headings and key terms.
- Minor updates and clarifications in descriptive text and comments.
- No changes detected in the skill's code or functionality.
- Version updated from 1.1.0 to 1.2.0.
v1.0.1
XtQuant 1.1.0 is a major update with greatly expanded documentation and module explanations.
- Added extensive usage examples and quick start guides for both the xtdata (market data) and xttrade (trading) modules.
- Significantly enhanced documentation to cover subscriptions, instrument info, financial data, and sector management.
- Detailed tables added for supported asset types, data periods, stock code formats, and module imports.
- Clarified setup and connection procedures for both market data and trading operations, with real-world code snippets.
- Separated and introduced new reference markdown files for quick reference and module-specific details (xtdata, xttrader).
- Initial public release of corresponding documentation files: README.md, QUICK_REFERENCE.md, xtdata.md, xttrader.md.
v1.0.0
XtQuant Python SDK for QMT/miniQMT — market data (xtdata) and trading (xttrade) interface for Chinese securities.quantitative, trading, china, stock, qmt, miniqmt, futures, options
Metadata
Frequently Asked Questions
What is xtquant?
XtQuant QMT Python SDK - 集成行情数据(xtdata)和交易接口(xttrade)，支持A股、期货、期权等中国证券市场。 It is an AI Agent Skill for Claude Code / OpenClaw, with 486 downloads so far.
How do I install xtquant?
Run "/install xtquant" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is xtquant free?
Yes, xtquant is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does xtquant support?
xtquant is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created xtquant?
It is built and maintained by coderwpf (@coderwpf); the current version is v1.0.3.
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