A professional decision-oriented A-share analysis skill that converts market tape and macro data into actionable next-session trading plans.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install uwillberich
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install uwillberich using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is uwillberich?
uwillberich is a sophisticated framework designed for traders and analysts focusing on the A-share market. Unlike basic tracking tools, this skill prioritizes discretionary decision-making by synthesizing market structure, overnight global shocks, and domestic policy shifts into a concrete execution strategy. It helps users distinguish between true market repair and mere defensive concentration, providing a clear lens through which to view volatility.
By leveraging integration with professional financial APIs and custom scripts, uwillberich automates the heavy lifting of data collection. It transforms raw indices, sector breadth, and capital flow data into a structured scenario tree, allowing for disciplined trading during the critical opening windows of the Chinese market.
uwillberich Use Cases
- Formulating next-session A-share outlooks and identifying high-probability repair sectors.
- Monitoring the opening checklist during the 09:00, 09:25, and 09:30-10:00 volatility windows.
- Mapping high-attention news and policy shifts into specific watchlist overlays and event-driven stock pools.
- Analyzing main-force capital flows to confirm market-wide risk tone and leadership rotation.
How uwillberich Works
- The skill confirms environment configurations and initializes market data retrieval using professional financial endpoints.
- It executes scripts to fetch indices, sector breadth, and overnight macro data (PBOC, Fed, Geopolitics).
- Data is classified across three layers: External Shocks, Domestic Policy/Liquidity, and Internal Market Structure.
- A scenario tree is constructed, providing Base, Bull, and Bear paths with explicit triggers and invalidation points.
- The workflow generates a time-boxed execution checklist for the next trading session, including specific observation gates.
uwillberich Setup
To get started with this skill, ensure you have python3 installed and follow these steps:
- Obtain your mandatory API key from the official provider:
[https://ai.eastmoney.com/mxClaw](https://ai.eastmoney.com/mxClaw). - Store your credential in the local environment file:
echo "EM_API_KEY=your_key_here" > ~/.uwillberich/runtime.env
- Verify the installation and connectivity using the included smoke test:
python3 scripts/smoke_test.py
- For persistent news monitoring on macOS, install the launchd job:
python3 scripts/install_news_iterator_launchd.py
uwillberich Data Schema & Taxonomy
uwillberich organizes data into a structured hierarchy for rapid retrieval during trading hours:
| Data Type | Source / Format | Purpose |
|---|---|---|
| Watchlists | assets/default_watchlists.json |
Core tracking lists for daily quotes. |
| Presets | assets/mx_presets.json |
Pre-defined workflows for policy and risk scans. |
| Chains | assets/industry_chains.json |
Theme-to-stock mapping for industry expansion. |
| Runtime | ~/.uwillberich/runtime.env |
Stores API keys and local configuration. |
uwillberich Advanced Features
- Persistent news iteration via RSS polling with automated classification and mapping to stock pools.
- Sentiment scoring engine that classifies the tape into specific regimes like tech repair or defensive concentration.
- Industry-chain expansion tools that turn event themes into fresh, actionable stock pools through live screens.
- Benchmarking system for comparing public versus enhanced data sources to ensure high-fidelity decision inputs.
SKILL.md
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