Total 54,046 skills, Data Processing has 2767 skills
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Builds Geographically Weighted Regression (GWR) workflows in CARTO. Triggers when the user mentions GWR, geographically weighted regression, spatially varying relationships, local regression, local coefficients, spatial regression, "what drives X in different areas", "why do prices vary spatially", "local factors affecting Y", varying coefficients, coefficient maps, spatial non-stationarity, or wants to model how the relationship between a dependent variable and predictors changes across geography. Produces per-cell regression coefficients that reveal how predictor importance shifts from place to place.
Find incomplete records, normalize field values in bulk, dedupe with `hubspot objects merge`, and audit custom properties. Builds on `bulk-operations` for JSONL piping and dry-run/digest/confirm.
Act as a Renaissance Tech-level quantitative systems engineer. Build unified feature engines instead of isolated strategies, rigorously test predictive variables, and assemble scoring models.
Obtain securities and financial information such as JoinQuant A-share market quotes, historical K-lines, financial data, and indicator data; Use this when users mention JoinQuant, jqdata, jqdatasdk and need to obtain A-share data
Find insurance payments, total annual premiums, and compare to benchmarks.
通过 EHunt Temu 店铺查询（网关路由 `ehunt/temu/storeQuery`）按多维度筛选 Temu 店铺（店名/ID、国家站点、后台类目、全托管/半托管、总/周/月销量与销售额、评分、评论、粉丝、商品数、开店时间等）。当用户提到 EHunt Temu 店铺、Temu 店铺分析、Temu seller、Temu 店铺排行、Temu 半托管店铺、Temu 销售额、temu stores、Temu store query 时触发。即使用户未写 EHunt，只要在 Temu 上找店铺、筛店铺数据或分析店铺表现，也应触发此技能。
Use when implementing data governance frameworks, building data catalogs, establishing data lineage, defining data quality rules, or setting up data stewardship programs - covers metadata management, data quality, and complianceUse when ", " mentioned.
Expert-level data mesh architecture, domain-oriented ownership, data products, federated governance, and self-serve platforms
Production-ready RNA-seq differential expression analysis using PyDESeq2. Performs DESeq2 normalization, dispersion estimation, Wald testing, LFC shrinkage, and result filtering. Handles multi-factor designs, multiple contrasts, batch effects, and integrates with gene enrichment (gseapy) and ToolUniverse annotation tools (UniProt, Ensembl, OpenTargets). Supports CSV/TSV/H5AD input formats and any organism. Use when analyzing RNA-seq count matrices, identifying DEGs, performing differential expression with statistical rigor, or answering questions about gene expression changes.
Use this skill when the user needs to set up a DataHub connection, install the DataHub CLI, configure authentication, verify connectivity, set default scopes, or create agent configuration profiles. Triggers on: "set up DataHub", "connect to DataHub", "install datahub CLI", "configure DataHub", "set default platform", "focus on domain X", "create profile", or any request to establish, configure, or troubleshoot DataHub connectivity.
Execute PostgreSQL queries and introspection with named project connections using `postgres-cli` V2. Use when the user asks to inspect data, run SQL, debug schema, validate config, or build schema cache artifacts.
Provides trading strategies for cryptocurrencies based on Binance market data, calculated technical analysis indicators, and aggregated market sentiment from crypto RSS news feeds. Use when users ask for trading advice, strategy recommendations, or analysis combining price data, TA, and sentiment for crypto assets like ETH, BTC, or altcoins.