Smart Lottery Prediction
Paste the following prompt into your AI chat to install this skill:
Please follow https://skillhub.cn/install/skillhub.md and install @user_fc770a5f/lottery-prediction.
About this skill
Problem addressed
When a user asks for Double Color Ball predictions, Pailie 3 predictions, hot-number analysis, or missing-value analysis, the skill turns draw history into a readable number recommendation. It targets data-analysis workflows: read draw records, rank candidates under several statistical rules, and emit a compact summary suitable for direct display.
How it works
The skill runs a self-contained script and depends on Python 3.8+ standard library features; the update command needs network access to fetch the latest draw data. It computes six strategies: frequency weighting, recent hot numbers, gap replenishment, interval balance, cold/hot combination, and time-decay weighting, then compresses the result into a concise summary. Double Color Ball red balls are marked with 🔴, blue balls with 🔵, and ★ indicates the backtest-optimal main strategy. The source states that all strategies are validated with Walk-Forward backtesting.
Boundaries
This skill is for entertainment and data-analysis demos, not for forecasting random lottery outcomes. Every output should keep the disclaimer: lottery draws are independent random events, buy responsibly, and people under 18 must not purchase tickets.
Use Cases
- When users ask for Double Color Ball picks, generate marked candidate numbers using frequency, hot numbers, and gap rules.
- When reviewing Pailie 3 draw history, extract recent hot numbers and long gaps into a comparable statistical summary.
- When draw data needs refreshing, run the online fetch command to update records and recalculate recommendations.
- When writing entertainment-style prediction copy, produce display-ready text with 🔴🔵 marks, a ★ strategy, and disclaimer.
Best For
- chatbot developers adding Double Color Ball or Pailie 3 recommendation logic
- data-analysis interns turning draw frequency, gaps, and hot/cold numbers into readable summaries
- content editors producing entertainment-style prediction copy with disclaimers and mark formatting
- script authors testing historical draw rules with Python standard-library tooling
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