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Openclaw Quant Skill
by
Justin Liu
· GitHub ↗
· v0.1.0
434
Downloads
0
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0
Active Installs
1
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Install in OpenClaw
/install openclaw-quant-skill
Description
Professional quantitative trading system for cryptocurrency - backtesting, paper trading, live trading, and strategy optimization
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install openclaw-quant-skill - After installation, invoke the skill by name or use
/openclaw-quant-skill - Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Frequently Asked Questions
What is Openclaw Quant Skill?
Professional quantitative trading system for cryptocurrency - backtesting, paper trading, live trading, and strategy optimization. It is an AI Agent Skill for Claude Code / OpenClaw, with 434 downloads so far.
How do I install Openclaw Quant Skill?
Run "/install openclaw-quant-skill" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Openclaw Quant Skill free?
Yes, Openclaw Quant Skill is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Openclaw Quant Skill support?
Openclaw Quant Skill is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Openclaw Quant Skill?
It is built and maintained by Justin Liu (@zhenstaff); the current version is v0.1.0.
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