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Openclaw Quant Skill
作者
Justin Liu
· GitHub ↗
· v0.1.0
434
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install openclaw-quant-skill
功能描述
Professional quantitative trading system for cryptocurrency - backtesting, paper trading, live trading, and strategy optimization
安全使用建议
This package is internally inconsistent and needs verification before use. Recommended actions: 1) Do not run commands that clone or pip/npm install the repositories until you inspect the upstream GitHub projects (https://github.com/ZhenRobotics/openclaw-quant and the video repo referenced) and review their code. 2) Ask the publisher to fix the packaging (remove unrelated SKILL-EN.md or explain why it’s included). 3) If you plan to use live trading, only use API keys with minimal permissions (no withdraw permission) and prefer testnet keys; require explicit confirmation before any live order. 4) Start with paper trading and audit logs/commands the agent would run. 5) If you’re not comfortable reviewing the repos, avoid installing and consider a vetted alternative. 6) Request an updated manifest that explicitly lists required environment variables and clearly documents the live-trading confirmation flow.
功能分析
Type: OpenClaw Skill
Name: openclaw-quant-skill
Version: 0.1.0
The skill bundle exhibits a major discrepancy: while '_meta.json' and 'SKILL.md' define a quantitative trading skill ('openclaw-quant'), 'SKILL-EN.md' contains instructions for an entirely different 'video-generator' skill. Both skills require high-risk operations, including 'git clone' from external repositories (github.com/ZhenRobotics) and the execution of shell scripts and package managers (pip, npm) on the host system. While these capabilities are plausibly needed for the stated purposes, the inconsistent documentation and the requirement for sensitive environment variables (BINANCE_API_KEY, OPENAI_API_KEY) without a unified purpose make the bundle suspicious.
能力评估
Purpose & Capability
The SKILL.md describes a crypto quant trading system (backtest/paper/live trading) which reasonably needs exchange API keys and access to external repos, but one of the included files (SKILL-EN.md) is for a completely different 'video-generator' skill (front matter name: video-generator). Including unrelated skill docs in the same package is an inconsistency that could indicate sloppy packaging or intentional misdirection.
Instruction Scope
Instructions tell the agent to clone external GitHub repos and run pip/npm installs and CLI commands; they reference environment variables (BINANCE_API_KEY, BINANCE_API_SECRET and, in the video doc, OPENAI_API_KEY) and include examples for running live trades. The skill metadata declares no required env vars, yet the runtime instructions assume API credentials for live trading — the agent could be directed to perform actions (including real trades) that require secrets not declared in the manifest.
Install Mechanism
This is instruction-only (no install spec), so nothing is written by the skill itself. However, the instructions direct the user/agent to git clone repositories and run pip/npm installs from external GitHub repos, which will execute/introduce third-party code. That behavior is expected for such tools but increases risk and requires verifying the upstream repository before installation.
Credentials
The manifest lists no required environment variables/primary credential, yet SKILL.md references BINANCE_API_KEY/BINANCE_API_SECRET for live trading and SKILL-EN references OPENAI_API_KEY. A trading skill that can place real orders should explicitly declare required credentials and document least-privilege usage (testnet keys, withdraw-disabled keys). The absence of declared credentials is disproportionate and reduces transparency.
Persistence & Privilege
always:false (no forced inclusion) which is normal. The skill allows autonomous invocation (platform default). Combined with the ability to trigger live trading, autonomous invocation increases blast radius — verify confirmation behavior and that the agent will not place live orders without explicit user consent.
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 openclaw-quant-skill - 安装完成后,直接呼叫该 Skill 的名称或使用
/openclaw-quant-skill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
v0.1.0
Initial release of openclaw-quant: a professional quantitative trading system for cryptocurrency.
- Supports backtesting, paper trading, live trading, and strategy optimization for crypto markets.
- Built-in performance analytics (Sharpe ratio, max drawdown, win rate, etc.).
- 50+ technical indicators and several ready-to-use strategies included.
- Multi-exchange support via ccxt library.
- Natural language and command-line interface usage documented.
- Integrated risk management and comprehensive example guides provided.
元数据
常见问题
Openclaw Quant Skill 是什么?
Professional quantitative trading system for cryptocurrency - backtesting, paper trading, live trading, and strategy optimization. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 434 次。
如何安装 Openclaw Quant Skill?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install openclaw-quant-skill」即可一键安装,无需额外配置。
Openclaw Quant Skill 是免费的吗?
是的,Openclaw Quant Skill 完全免费(开源免费),可自由下载、安装和使用。
Openclaw Quant Skill 支持哪些平台?
Openclaw Quant Skill 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 Openclaw Quant Skill?
由 Justin Liu(@zhenstaff)开发并维护,当前版本 v0.1.0。
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