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Install in OpenClaw
/install all-weather-strategy
Description
Calculate asset allocation weights for a portfolio of ETFs based on Risk Parity (All Weather) principles. Includes annualized return and risk metrics. Fully...
README (SKILL.md)
All Weather Strategy Skill (Professional Edition)
This skill provides a professional implementation of the Risk Parity (All Weather) investment strategy. It is optimized for the OpenClaw marketplace.
Core Capabilities
- Risk Parity Optimization: SLSQP-based solver for equal risk contribution.
- Annualized Performance: Forecasts return and volatility based on historical lookback.
- Proactive AI Guidance: Instructions optimized for AI agents to interact with humans.
Default Parameters (Standard Config)
- Amount:
10,000.0CNY - Lookback:
365days - Market Pool: A mix of Global (S&P 500, Nasdaq) and Domestic (STAR 50, Treasury, Gold) ETFs.
AI Interaction Logic
The AI assistant must act as a financial consultant:
- Intro: "I can generate an All Weather asset allocation for you."
- Options: Offer to use the "Standard Professional Config" or custom settings.
- Prompt: Ask specifically about the investment amount and if they want to modify the ETF pool.
Usage Example
from scripts.engine import AllWeatherEngine
# The engine handles all defaults natively
engine = AllWeatherEngine()
results = engine.run()
Copyright © 2026 wzwangyc. All Rights Reserved.
Usage Guidance
This skill appears to do what it says: fetch historical ETF prices, compute risk-parity weights, and produce tables/charts. Before installing, consider: 1) it requires Python libraries (see requirements.txt) and will make network calls to akshare and yfinance to fetch market data — run it in an environment where outgoing network traffic is acceptable; 2) PDF generation may try to register a local Chinese font (simhei.ttf) or fall back to system fonts — the README mentions a resources/ folder but that folder is not present in the provided manifest, so PDF rendering may fall back to defaults; 3) no credentials or secrets are requested, which is appropriate; 4) review and pin dependency versions if you will run this in production, and run in an isolated environment (virtualenv/container) if you want to limit risk from third-party packages. Overall there are no incoherent or suspicious indicators.
Capability Analysis
Type: OpenClaw Skill
Name: all-weather-strategy
Version: 1.0.0
The skill bundle provides a legitimate financial tool for ETF asset allocation using Risk Parity principles. The implementation in `scripts/engine.py` and `app.py` uses standard libraries (akshare, yfinance, scipy) for data retrieval and optimization, and the instructions in `SKILL.md` are aligned with its stated purpose without any signs of prompt injection or malicious intent. No evidence of data exfiltration, unauthorized execution, or persistence was found.
Capability Assessment
Purpose & Capability
The name/description (All Weather Risk Parity allocator) align with included code: data fetchers (akshare, yfinance), a risk-parity optimizer (scipy minimize SLSQP), metrics calculation, and report generation. The declared requirements (no env vars, no required binaries) match the code's use of Python libraries and no secret/third-party API keys.
Instruction Scope
SKILL.md instructs the agent to load scripts/engine.py and run engine.run(), and to interactively ask the user for amount/ETF pool — that matches the code. One minor omission: the SKILL.md does not explicitly state that the code will perform network calls to fetch historical prices (via akshare and yfinance) or that a local Chinese font file (simhei.ttf) is optionally used for PDF generation; these are reasonable but worth calling out so users expect network I/O and possible local file access for fonts.
Install Mechanism
There is no install spec (instruction-only install) and dependencies are listed in requirements.txt (akshare, yfinance, numpy, pandas, matplotlib, scipy, reportlab, streamlit, altair) — these are consistent with the code. No downloads from arbitrary URLs or archive extraction are present in the manifest.
Credentials
The skill requests no environment variables, credentials, or config paths. The code performs network requests to public data providers (akshare/yfinance) but does not attempt to read secrets or unrelated system files.
Persistence & Privilege
The skill is not always-enabled and does not modify other skills or system-wide settings. It generates files (CSV/PDF) when asked, but does not request persistent elevated privileges.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install all-weather-strategy - After installation, invoke the skill by name or use
/all-weather-strategy - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the All Weather Strategy skill (Professional Edition)
- Calculates ETF portfolio weights based on Risk Parity (All Weather) principles
- Provides annualized return and risk estimates using historical data
- Features default settings with global and domestic ETF pool and CNY support
- Includes proactive AI-guided interactions for portfolio customization and advice
Metadata
Frequently Asked Questions
What is All Weather Strategy?
Calculate asset allocation weights for a portfolio of ETFs based on Risk Parity (All Weather) principles. Includes annualized return and risk metrics. Fully... It is an AI Agent Skill for Claude Code / OpenClaw, with 323 downloads so far.
How do I install All Weather Strategy?
Run "/install all-weather-strategy" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is All Weather Strategy free?
Yes, All Weather Strategy is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does All Weather Strategy support?
All Weather Strategy is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created All Weather Strategy?
It is built and maintained by wzwangyc (@wzwangyc); the current version is v1.0.0.
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