Total 53,816 skills, Data Processing has 2767 skills
Showing 12 of 2767 skills
Model viral spread dynamics using SIR/SIS/SEIR compartmental models. Use this skill when the user needs to predict content spread patterns, estimate viral thresholds, or model information cascades in social networks — even if they say 'will this go viral', 'epidemic model for content', or 'spread prediction'.
Apply Grounded Theory (Glaser and Strauss) to build theory inductively from qualitative data through open, axial, and selective coding. Use this skill when the user needs to develop new theory from data rather than test existing hypotheses, conduct theoretical sampling and constant comparison, determine when theoretical saturation is reached, or when they ask 'what theory explains this phenomenon', 'how do I code qualitative data systematically', or 'when do I stop collecting data'.
Export trade history and tax calculations in formats compatible with Koinly, CoinTracker, CoinLedger, TokenTax, and IRS Form 8949
When the user wants to model inventory systems with uncertain demand, optimize safety stock levels, implement (s,S) or (Q,r) policies, or analyze service levels under uncertainty. Also use when the user mentions "stochastic inventory," "probabilistic inventory," "(Q,r) policy," "(s,S) policy," "base stock policy," "safety stock optimization," "service level constraints," "lead time demand distribution," "fill rate calculation," or "inventory with demand uncertainty." For deterministic models, see economic-order-quantity or lot-sizing-problems. For single-period uncertainty, see newsvendor-problem.
Execute read-only SQL queries against Databricks. Use when you need to run a specific SQL query, aggregate data, join tables, or answer analytical questions about Databricks data.
Calculate ETF premium or discount relative to Net Asset Value (NAV) using Yahoo Finance data. Use this skill whenever the user asks about an ETF's premium or discount, NAV comparison, whether an ETF is trading above or below its fair value, or wants to compare market price vs NAV. Triggers: "ETF premium", "ETF discount", "NAV premium", "is SPY trading at a premium", "AGG premium to NAV", "market price vs NAV", "ETF mispricing", "BITO premium", "IBIT premium", "bond ETF discount", "trading above/below NAV", "ETF premium screener", "which ETFs have biggest discount", "compare ETF NAV", "ETF arbitrage", or any request involving the gap between an ETF's market price and its underlying value. Also triggers when analyzing leveraged, inverse, international, bond, commodity, or crypto ETFs where premium/discount is a known concern.
美股K线数据查询。获取日线行情。 当用户询问"苹果日K""特斯拉周线""美股K线走势"时触发。
Outscraper integration. Manage Organizations. Use when the user wants to interact with Outscraper data.
Elasticsearch expert for queries, mappings, aggregations, index management, and cluster operations
Nasdaq Data Link integration. Manage Datasets. Use when the user wants to interact with Nasdaq Data Link data.
Specialist in self-healing data pipelines — uses air-gapped local SLMs and semantic clustering to automatically detect, classify, and fix data anomalies at scale. Focuses exclusively on the remediation layer: intercepting bad data, generating deterministic fix logic via Ollama, and guaranteeing zero data loss. Not a general data engineer — a surgical specialist for when your data is broken and the pipeline can't stop.
Use this skill to use Liquid variables in LookML for dynamic SQL, HTML, and Links, including advanced patterns for query optimization.