A data-driven decision engine for CN A-share momentum trading with a 1-5 day horizon.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install a-share-short-decision
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 a-share-short-decision 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 A-Share Short-Term Decision?
This skill provides a specialized framework for short-term trading decisions in the Chinese A-share market, focusing on a 1-5 day horizon. By integrating Openclaw Skills into your trading environment, you can automate market sentiment analysis, identify sector rotations, and generate date-based signal scoring for high-momentum stocks. It serves as a systematic bridge between raw market data and actionable trading strategies, ensuring all decisions are backed by capital flow confirmation and historical prediction logging.
A-Share Short-Term Decision Use Cases
- Scanning for high-potential momentum stocks in the CN A-share market based on daily capital flow.
- Automating daily market sentiment and sector rotation reports using Openclaw Skills.
- Tracking trading prediction accuracy by comparing automated forecasts against actual market performance.
- Implementing systematic risk management through explicit signal-based trade recommendations and NO_TRADE warnings.
How A-Share Short-Term Decision Works
- The system executes the signal engine for a specific analysis date to evaluate market health and sector strength.
- A weighted short-term score is calculated, generating recommendation statuses for individual tickers.
- The skill persists decision snapshots into a structured log for auditing and backtesting.
- Real market closing data is compared against previous predictions to calculate per-stock returns.
- A comprehensive daily report is generated to summarize signals, market stats, and recommended next actions.
A-Share Short-Term Decision Setup
To deploy this skill within your Openclaw Skills environment, follow these runtime commands:
# Generate signals for a specific date
python3 main.py short_term_signal_engine --date 2026-02-12
# Persist the prediction to logs
python3 main.py run_prediction_for_date --date 2026-02-12
# Compare prediction results with actual market data
python3 main.py compare_prediction_with_market --prediction-date 2026-02-12 --actual-date 2026-02-13
# Generate a summary report
python3 main.py generate_daily_report --date 2026-02-12
A-Share Short-Term Decision Data Schema & Taxonomy
The skill organizes trading intelligence within the data/ directory using the following structures:
| File/Path | Description |
|---|---|
data/decision_log.jsonl |
Append-only log storing date-based snapshots of signal scores and recommendations. |
data/*.json |
Individual daily report artifacts and strategy performance statistics. |
subskills/ |
Contains configuration optimization scripts and recurring daily recommendation logic. |
A-Share Short-Term Decision Advanced Features
- Intelligent No-Recommendation logic that explicitly prevents trading during weak signals to preserve capital.
- Automated strategy optimization scripts that refine parameters based on historical aggressive periods.
- Built-in support for Openclaw Skills subskills, allowing for automated daily recommendation workflows.
- Detailed performance summary statistics including per-stock return tracking and hit-rate analysis.
SKILL.md
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