Total 53,790 skills, Data Processing has 2767 skills
Showing 12 of 2767 skills
Publication-ready matplotlib figures for Nature/high-impact journals and academic papers. Covers bar charts, grouped bars, heatmaps, line/trend plots, forest plots, microscopy-style image panels, schematic + quantitative composites, radar plots, and multi-panel layouts with Nature-style typography (Arial/sans-serif), restrained color systems, and SVG/PDF export conventions. Use when creating scientific figures that must match Nature publication standards. Do NOT use for interactive dashboards (Plotly, Bokeh) or Illustrator/Figma-first infographic workflows.
从智慧芽（PatSnap）获取专利权利要求数据。当用户提到专利权利要求、权利要求文本、独立权利要求、从属权利要求、权利要求数量、权利要求树、权利要求分析、权利要求范围、权利要求语言、想查看特定专利的权利要求部分、patent claims, independent claims, dependent claims, claims text, PatSnap时触发此技能。即使用户未明确提及"智慧芽"或"PatSnap"，只要其请求涉及通过专利ID或公开号获取或分析专利权利要求信息，也应触发此技能。
对产品标题进行分词分析，提取词频、场景词、人群词、材质词等属性维度。当用户想分析产品标题、提取标题高频词、进行标题分词、发现场景词或人群词、对比不同商品的标题关键词用法、基于词频优化Listing标题、识别一组ASIN中的常见属性规律、title tokenization, word frequency analysis, scene keyword extraction, audience keyword analysis, title optimization, attribute keyword extraction, keyword frequency时触发此技能。即使用户未明确说"标题分析"，只要其需求涉及将产品标题拆解为有意义的词组、统计关键词频率或按提取的属性对商品分组，也应触发此技能。
OpenAlgo indicator expert. Use when user asks about technical indicators, charting, plotting indicators, creating custom indicators, building dashboards, real-time feeds, scanning stocks, indicator combinations, or using openalgo.ta. Also triggers for indicator functions (sma, ema, rsi, macd, supertrend, bollinger, atr, adx, ichimoku, stochastic, obv, vwap, crossover, crossunder, exrem).
SaaS business metrics analysis - MRR, ARR, Churn, LTV, CAC, cohort analysis, and investor reporting
This skill provides routing guidance for all DataHub interaction skills. It is injected at session start and helps map user intent to the correct skill. Do not invoke this skill directly — it is loaded automatically.
Query Ethereum network data via ethpandaops CLI or MCP server. Use when analyzing blockchain data, block timing, attestations, validator performance, network health, or infrastructure metrics. Provides access to ClickHouse (blockchain data), Prometheus (metrics), Loki (logs), and Dora (explorer APIs).
Use this skill when designing data warehouses, building star or snowflake schemas, implementing slowly changing dimensions (SCDs), writing analytical SQL for Snowflake or BigQuery, creating fact and dimension tables, or planning ETL/ELT pipelines for analytics. Triggers on dimensional modeling, surrogate keys, conformed dimensions, warehouse architecture, data vault, partitioning strategies, materialized views, and any task requiring OLAP schema design or warehouse query optimization.
从Eureka专利数据库查询专利权利要求（Claims）信息。当用户提到专利权利要求、权利要求书、专利Claims、独立权利要求、从属权利要求、权利要求数量、专利保护范围、patent claims, claim data, independent claims, dependent claims, claim count, patent claim text, patent protection scope, Eureka patent claims时触发此技能。即使用户未明确提及"Eureka"或"权利要求"，只要其需求涉及获取专利的权利要求全文或权利要求数量，也应触发此技能。
Expert SQL query writing, optimization, and database schema design with support for PostgreSQL, MySQL, SQLite, and SQL Server. Use when working with databases for: (1) Writing complex SQL queries with joins, subqueries, and window functions, (2) Optimizing slow queries and analyzing execution plans, (3) Designing database schemas with proper normalization, (4) Creating indexes and improving query performance, (5) Writing migrations and handling schema changes, (6) Debugging SQL errors and query issues
Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset. - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset. Don't use for: - General BigQuery querying or data analysis (use BigQuery-related tools instead). - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage. - Creating or modifying lineage links directly.
Monitor dividend portfolios with Kanchi-style forced-review triggers (T1-T5) and convert anomalies into OK/WARN/REVIEW states without auto-selling. Use when users ask for 減配検知, 8-Kガバナンス監視, 配当安全性モニタリング, REVIEWキュー自動化, or periodic dividend risk checks.