发现最适合你需求的 AI 技能
阿联酋航空公司介绍和航班查询
163邮箱发送工具。使用授权密码(授权码)进行SMTP认证发送邮件。支持文本邮件、HTML邮件、带附件邮件、抄送/密送。当用户需要发送邮件时使用此技能。
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Email management and automation. Send, read, search, and organize emails across multiple providers.
Create segmented email sequences for abandoned carts, post-purchase follow-up, win-back campaigns, and seasonal promotions for online stores.
Automated email outreach campaign builder and optimizer. Use when asked to write cold emails, build outreach sequences, create follow-up cadences, personalize email templates at scale, audit existing email copy for deliverability and response rates, generate subject line variants, or build lead lists. Triggers on phrases like "cold email", "outreach sequence", "email campaign", "follow-up emails", "personalize emails", "email templates", "improve open rates", "sales emails", "lead outreach".
Multi-email management assistant supporting Gmail, 163, QQ, Outlook, and Hotmail. Features: (1) Fetch inbox and summarize emails (2) Keyword-based important email detection (3) Auto-extract calendar events from emails. Use when: users need unified email management across multiple accounts, want to avoid missing important emails, or need to extract schedules from email content.
Use when the user wants to sell or buy an NFT on Element, create or accept a bid or offer, query public collection orders or account orders, cancel an Element order, get the configured trading wallet address, or use a supported custom payment token on a supported Element EVM network. Supported custom payment tokens are BSC USDT/USD1, Base USDC, and Polygon ETH. Other chains should use native or wrapped native token flow.
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Comprehensive electricity load and demand forecasting framework. Supports statistical methods (ARIMA, SARIMA), machine learning (XGBoost, LightGBM, Random Forest), and deep learning (LSTM, GRU, Transformer, TFT). Use when building short-term load forecasting (STLF) systems, predicting electricity demand for energy trading, analyzing consumption patterns, integrating weather features, evaluating forecasts with MAPE/RMSE/MAE, or deploying production pipelines with uncertainty quantification.
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