ClawHub

A股短线交易决策 A Share Short Term Decision

A-share short-term trading decision skill for 1-5 day horizon. Use when you need real-data market sentiment, sector rotation, strong stock scanning, capital flow confirmation, date-based short-term signal scoring, prediction logging, and next-day market comparison for CN A-share momentum trading.

Audits

Pass
ClawScanPass

Agentic behavior and permission review.

Static analysisPass

Pattern checks against bundled files.

VirusTotalPass

Multi-engine malware detections and file reputation.

Install

openclaw skills install a-share-short-decision

A-Share Short-Term Decision Skill

Implement in sequence:

  1. Run short_term_signal_engine(analysis_date) for target date.
  2. If needed, persist prediction with run_prediction_for_date(analysis_date).
  3. Compare prediction vs actual market with compare_prediction_with_market(prediction_date, actual_date).
  4. Output report with generate_daily_report(analysis_date).

Tool Contracts

short_term_signal_engine(analysis_date=None)

  • analysis_date: YYYY-MM-DD or YYYYMMDD
  • Returns weighted short-term score and recommendation status.
  • Always returns friendly no_recommendation_message when no tradable candidate exists.

run_prediction_for_date(analysis_date)

  • Runs signal engine for the specified date.
  • Appends decision snapshot into data/decision_log.jsonl.

compare_prediction_with_market(prediction_date, actual_date=None)

  • Loads prediction from log (or auto-generates if missing).
  • Compares predicted candidates against real market closes on actual_date.
  • Returns per-stock return and summary statistics.

No-Recommendation Behavior

Required behavior:

  • Never return empty output.
  • If candidates is empty or signal is NO_TRADE, explicitly say: 当前暂无可执行短线买入标的.
  • Include reason and next action.

Runtime

python3 main.py short_term_signal_engine --date 2026-02-12
python3 main.py run_prediction_for_date --date 2026-02-12
python3 main.py compare_prediction_with_market --prediction-date 2026-02-12 --actual-date 2026-02-13
python3 main.py generate_daily_report --date 2026-02-12

Subskills Workflow

For recurring optimize-then-recommend flow, run:

python3 subskills/config-optimization/optimize_from_aggressive.py --analysis-period "2026-02-01 to 2026-02-12"
python3 subskills/daily-recommendation/generate_daily_recommendation.py --date 2026-02-14

All generated artifacts are stored under data/.