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Quantaxis Data Platform
作者
Tang Weigang
· GitHub ↗
· v0.3.3
· MIT-0
125
总下载
0
收藏
0
当前安装
3
版本数
在 OpenClaw 中安装
/install quantaxis-data-platform
功能描述
提供 A 股市场的因子计算、存储与 tear sheet 分析能力,支持 Pandas/Polars 零拷贝数据转换和 QIFI 账户回测模拟,适用于多数据源量化研究。
安全使用建议
This skill is instruction-only and appears coherent for A‑share/factor research and backtesting. Before installing or letting the agent execute commands: (1) Review any proposed shell commands (especially pip install) and prefer using a virtualenv/container to avoid global package changes. (2) Expect the agent to ask for data-source credentials (eastmoney/joinquant/qmt) or DB connection strings later — do not share secrets until you confirm the exact use and endpoint. (3) Be prepared for disk writes (ZVT_HOME ~/.zvt) and potentially large data pulls (ClickHouse, full‑market downloads) — run initial experiments on a small universe. (4) If you need stricter isolation, run the skill actions in a disposable container or VM and inspect commands the agent requests before consenting.
功能分析
Type: OpenClaw Skill
Name: quantaxis-data-platform
Version: 0.3.3
The quantaxis-data-platform bundle is a legitimate quantitative trading research tool focused on the A-share market. It employs sophisticated prompt-engineering techniques, such as 'Semantic Locks' (SL-01 to SL-12) and 'Fatal Constraints' (finance-C-*), to ensure the AI agent generates realistic trading code that respects financial regulations like T+1 settlement and avoids common errors like look-ahead bias. The bundle includes a valuable database of cross-project anti-patterns (e.g., AP-QLIB-1930, AP-ZVT-183) to protect users from known bugs in popular quant libraries. No evidence of data exfiltration, malicious execution, or harmful instructions was found; the complex logic is entirely dedicated to enforcing domain-specific correctness and safety in financial simulations.
能力标签
能力评估
Purpose & Capability
The name/description (A‑share factor computation, storage, tear sheets, zero‑copy Pandas/Polars bridges, QIFI account backtests) match the provided SKILL.md and reference artifacts. Minor inconsistency: SKILL.md metadata says 'Requires Python 3.12+ with uv package manager' but the registry metadata lists no required binaries/install spec. That is likely an omission in the registry entry rather than malicious.
Instruction Scope
The SKILL.md + seed.yaml are detailed and scoped to data collection, factor computation, backtesting, and resource management. The seed.yaml execution_protocol and preconditions include commands that check for zvt and may recommend 'python3 -m pip install zvt' and touch ~/.zvt; these are expected for a runtime that needs local packages/data dirs but constitute local filesystem and package-manager operations the agent may propose to run. There are no instructions that request unrelated system secrets or to exfiltrate data to unknown endpoints.
Install Mechanism
No install spec or code files are bundled (instruction-only). No downloads, URLs, or archive extraction are present in the skill metadata. Any package installation would be via generic python/pip commands referenced in preconditions (not pre-populated install recipes).
Credentials
The skill does not declare required env vars, credentials, or config paths. The content references external services and databases (ClickHouse, MongoDB, RabbitMQ, Redis, brokers and data providers like eastmoney/joinquant/akshare) which in real use require connection strings/credentials — but none are requested up-front. This is reasonable for an instruction-only skill but means the agent will later ask the user to provide service credentials or connection details when needed.
Persistence & Privilege
always:false (normal). The seed.yaml instructs agents to re-read seed.yaml on decisions and run preconditions that may create/check ~/.zvt and run pip install commands; that implies the agent may perform local installs and write to the user's home directory. This is normal for a platform that initializes local data directories, but you should be aware it can modify disk and install Python packages if you allow it.
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 quantaxis-data-platform - 安装完成后,直接呼叫该 Skill 的名称或使用
/quantaxis-data-platform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
v0.3.3
v0.3.3: bilingual metadata injected. H1 shows QuantAxis 数据平台; tagline replaced with skill-specific Chinese hook; tags upgraded to Level 1-4.
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
Quantaxis Data Platform 是什么?
提供 A 股市场的因子计算、存储与 tear sheet 分析能力,支持 Pandas/Polars 零拷贝数据转换和 QIFI 账户回测模拟,适用于多数据源量化研究。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 125 次。
如何安装 Quantaxis Data Platform?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install quantaxis-data-platform」即可一键安装,无需额外配置。
Quantaxis Data Platform 是免费的吗?
是的,Quantaxis Data Platform 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Quantaxis Data Platform 支持哪些平台?
Quantaxis Data Platform 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 Quantaxis Data Platform?
由 Tang Weigang(@tangweigang-jpg)开发并维护,当前版本 v0.3.3。
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