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Qlib Ai Quant
作者
Tang Weigang
· GitHub ↗
· v0.3.2
· MIT-0
109
总下载
0
收藏
0
当前安装
3
版本数
在 OpenClaw 中安装
/install qlib-ai-quant
功能描述
基于微软 qlib 的 AI 量化平台：覆盖预测模型、因子挖掘（Alpha158/TFT）、 组合优化、多频回测。支持 A 股 + 美股 + 港股多市场。
安全使用建议
This skill's files claim a qlib-based platform but the runtime instructions heavily reference ZVT, expect Python package installs, and touch a local ZVT home directory — none of which are declared in the registry. Before installing or running: (1) Inspect SKILL.md and seed.yaml yourself and confirm you are comfortable with any pip installs; (2) run it inside an isolated virtual environment or sandbox and set ZVT_HOME to a dedicated directory to avoid contaminating your real ~/.zvt; (3) do NOT provide any API keys or credentials until you confirm which provider is actually used and why; (4) if you want to proceed, request the author/source (homepage is missing) or ask for an explicit install manifest and a minimal example showing only qlib usage — the current package is internally inconsistent and should be treated with caution.
功能分析
Type: OpenClaw Skill
Name: qlib-ai-quant
Version: 0.3.2
The skill bundle is a highly structured knowledge pack for an AI agent to perform quantitative finance tasks using Microsoft Qlib and the ZVT library. It contains extensive documentation on financial modeling best practices, including 25 'Anti-Patterns' (e.g., AP-QLIB-2090 regarding look-ahead bias) and 12 'Semantic Locks' (e.g., SL-01 enforcing sell-before-buy ordering) designed to prevent common algorithmic trading errors. The instructions in SKILL.md and seed.yaml are focused on ensuring code quality, temporal data integrity, and proper multi-index handling. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the bundle appears to be a legitimate tool for financial research and backtesting.
能力标签
能力评估
Purpose & Capability
Name/description claim a qlib-based AI quant platform, but the runtime files and seed.yaml include many ZVT-specific preconditions (python checks for zvt, ZVT_HOME directory, zvt.recorders commands) and references to multiple ecosystems. The required/env/installer metadata declares no env vars or installs, yet the instructions imply installing and using ZVT and other providers — this is disproportionate to a standalone 'qlib' helper and indicates incoherence between claimed purpose and required components.
Instruction Scope
SKILL.md/seed.yaml direct the agent to run runtime checks and commands (e.g., python3 -c 'import zvt...', pip install zvt if missing, create/check ZVT_HOME and touch files) and to reload seed.yaml before any behavioral decision. The skill's prose references reading/writing ~/.zvt and running recorders; it also directs the agent to consult many large reference files. These instructions access filesystem paths and environment variables (ZVT_HOME) that were not declared in requires.env and go beyond a simple 'write code for qlib' helper.
Install Mechanism
There is no declared install spec in registry metadata (instruction-only). However, seed.yaml/execution_protocol and SKILL.md imply installing packages (pip install zvt) and running host_adapter.install_recipes[]. The absence of an explicit install recipe in the registry while the instructions expect package installation is a mismatch and increases operational risk if the agent or user follows those steps automatically.
Credentials
Declared requirements list no environment variables or credentials, but the runtime instructions reference ZVT_HOME and require creating/writing to it. The skill also asks users to choose data providers (eastmoney, joinquant, qmt, etc.), some of which require API keys/accounts; those credentials are not declared. This mismatch means the skill expects access to filesystem locations and possibly external service credentials that were not declared up-front.
Persistence & Privilege
always:false (normal). The skill does instruct creating/checking a local data directory (~/.zvt) and suggests running pip install and recorders which will write local artifacts. It does not request to modify other skills or global agent config, but it does expect persistent local data directories and can cause environment changes if followed.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install qlib-ai-quant - 安装完成后，直接呼叫该 Skill 的名称或使用
/qlib-ai-quant触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v0.3.2
v0.3.2: inject bilingual metadata per naming spec. H1 now shows Qlib AI 量化 + slug; tagline and description replaced with CTO-authored copy (fixes tagline pollution for non-ZVT skills).
v0.3.1
Remove install.sh — knowledge-only bundle. Host AI consumes directly from URL; no user-side installation needed. Fixes ClawHub suspicious flag.
v0.3.0
Doramagic crystal portfolio v0.3.0. Full 5-layer bp-009 standard. github.com/tangweigang-jpg/doramagic-skills
元数据
常见问题
Qlib Ai Quant 是什么？
基于微软 qlib 的 AI 量化平台：覆盖预测模型、因子挖掘（Alpha158/TFT）、 组合优化、多频回测。支持 A 股 + 美股 + 港股多市场。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 109 次。
如何安装 Qlib Ai Quant？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install qlib-ai-quant」即可一键安装，无需额外配置。
Qlib Ai Quant 是免费的吗？
是的，Qlib Ai Quant 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Qlib Ai Quant 支持哪些平台？
Qlib Ai Quant 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Qlib Ai Quant？
由 Tang Weigang（@tangweigang-jpg）开发并维护，当前版本 v0.3.2。
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