Total 54,890 skills, Data Processing has 2815 skills
Showing 12 of 2815 skills
Мультиаккаунтный дашборд. Статистика по всем аккаунтам с детализацией до уровня объявлений.
Detects market top probability using O'Neil Distribution Days, Minervini Leading Stock Deterioration, and Monty Defensive Sector Rotation. Generates a 0-100 composite score with risk zone classification. Use when user asks about market top risk, distribution days, defensive rotation, leadership breakdown, or whether to reduce equity exposure. Focuses on 2-8 week tactical timing signals for 10-20% corrections.
Analyzes market breadth using Monty's Uptrend Ratio Dashboard data to diagnose the current market environment. Generates a 0-100 composite score from 5 components (breadth, sector participation, rotation, momentum, historical context). Use when asking about market breadth, uptrend ratios, or whether the market environment supports equity exposure. No API key required.
Interactive tutorial that teaches Snowflake Dynamic Tables hands-on. The agent guides users step-by-step through building data pipelines with automatic refresh, incremental processing, and CDC patterns. Use when the user wants to learn dynamic tables, build a DT pipeline, or understand DT vs streams/tasks/materialized views.
Firecrawl web scraping API via curl. Use this skill to scrape webpages, crawl websites, discover URLs, search the web, or extract structured data.
Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.
Smart Excel/CSV file parsing with intelligent routing based on file complexity analysis. Analyzes file structure (merged cells, row count, table layout) using lightweight metadata scanning, then recommends optimal processing strategy - either high-speed Pandas mode for standard tables or semantic HTML mode for complex reports. Use when processing Excel/CSV files with unknown or varying structure where optimization between speed and accuracy is needed.
Query APIs, files, and live sources using Coral SQL. Use when the user asks about data from GitHub, Slack, Linear, Datadog, Sentry, or other connected sources.
Seasonality and calendar-effect strategy via Longbridge Securities — uses historical OHLCV data to compute month-of-year returns (January Effect), day-of-week returns (Monday / Friday effect), pre/post-holiday drift, and earnings-season effect; identifies statistically significant patterns and generates trading signals. Triggers: "季节性", "日历效应", "月份效应", "周一效应", "年初效应", "节假日效应", "财报季效应", "时间模式", "季節性", "日曆效應", "月份效應", "周一效應", "年初效應", "節假日效應", "財報季效應", "seasonality", "calendar effect", "January effect", "day of week effect", "holiday effect", "earnings season effect", "seasonal pattern", "time series anomaly", "月度效应", "月度效應", "monthly seasonality".
On-chain data analysis framework — covers active addresses, whale behaviour, TVL (total value locked), DEX liquidity, and on-chain valuation metrics: MVRV (market cap / realised value), NVT (network value / transaction volume), SOPR. Longbridge provides spot crypto quotes (.HAS); raw on-chain data requires external sources (Glassnode / Dune Analytics). Triggers: "链上数据", "链上分析", "MVRV", "NVT", "活跃地址", "鲸鱼地址", "TVL", "SOPR", "链上指标", "链上估值", "鏈上數據", "鏈上分析", "活躍地址", "鯨魚地址", "鏈上指標", "鏈上估值", "on-chain data", "on-chain analysis", "MVRV ratio", "NVT ratio", "active addresses", "whale activity", "TVL", "SOPR", "on-chain valuation", "DeFi TVL", "crypto on-chain".
中国国家统计局公开数据查询技能，当用户想查询经济、CPI、GDP、人口、房价指数等数据时触发。
Develop and deploy Data Cloud Code Extensions using SF CLI plugin. Use this skill when creating custom Python transformations for Data Cloud, deploying code extensions, or testing data transformations. Supports init, run, scan, and deploy operations.