Skills your agents can run

Analyze Reddit threads for sentiment, consensus opinions, top arguments, and discussion patterns. Use this when users want to understand Reddit community opinions, analyze discussions, or gather insights from subreddit conversations.

Automatically generate Excel reports from data sources such as CSV files, databases, or Python data structures. Supports data analysis reports, business reports, data export, and template-based report generation using pandas and openpyxl/xlsxwriter. Trigger when users mention Excel, spreadsheets, report generation, data export, or business reporting.

Query FRED (Federal Reserve Economic Data) API for 800,000+ economic time series from 100+ sources. Access GDP, unemployment, inflation, interest rates, exchange rates, housing, and regional data. Use for macroeconomic analysis, financial research, policy studies, economic forecasting, and academic research requiring U.S. and international economic indicators.

Twitter 数据采集到数据库的完整自动化工作流（采集→筛选→Grok 转换→数据库录入）

Setup and use text-to-SQL capabilities for SQL databases (SQLite, PostgreSQL, MySQL, MariaDB, etc.). Use when: (1) User wants to query databases using natural language, (2) User asks to setup text-to-sql project, (3) User mentions extracting data from database, (4) User has .sqlite/.db file or database credentials and wants to work with data. This skill sets up project structure, extracts database schema, and enables natural language to SQL conversion.

Run IV, DiD, and RDD analyses in R with proper diagnostics

Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, and 7 programming languages (Python, R, Julia, JavaScript, C++, Java, Go) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.

Scientific research and analysis skills

Inventory management, demand forecasting, replenishment strategy, and supply chain optimization. Codified expertise for demand forecasting, safety-stock optimization, replenishment planning, and promotional lift estimation at multi-location retailers. Informed by demand planners with 15+ years of experience managing hundreds of SKUs. Includes forecasting method selection, ABC/XYZ analysis, seasonal transition management, and vendor negotiation frameworks. Use when forecasting demand, setting safety stock, planning replenishment, managing promotions, or optimizing inventory levels.

Visualization Best Practices - Auto-activating skill for Data Analytics. Triggers on: visualization best practices, visualization best practices Part of the Data Analytics skill category.

Football (soccer) data across 13 leagues — standings, schedules, match stats, xG, transfers, player profiles. Zero config, no API keys. Covers Premier League, La Liga, Bundesliga, Serie A, Ligue 1, MLS, Champions League, World Cup, Championship, Eredivisie, Primeira Liga, Serie A Brazil, European Championship. Use when: user asks about football/soccer standings, fixtures, match stats, xG, lineups, player values, transfers, injury news, league tables, daily fixtures, or player profiles. Don't use when: user asks about American football/NFL (use nfl-data), college football (use cfb-data), NBA (use nba-data), WNBA (use wnba-data), college basketball (use cbb-data), NHL (use nhl-data), MLB (use mlb-data), tennis (use tennis-data), golf (use golf-data), Formula 1 (use fastf1), or betting odds (use polymarket or kalshi). Don't use for live/real-time scores — data updates post-match. Don't use get_season_leaders or get_missing_players for non-Premier League leagues (they return empty). Don't use get_event_xg for leagues outside the top 5 (EPL, La Liga, Bundesliga, Serie A, Ligue 1).

Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.

March Madness, playoff brackets, tournament picks. Upset potential, chalk vs contrarian strategies, historical trends, confidence levels.

Identify EMERGING trends by connecting dots across unrelated sources. Monitor niche communities, academic research, GitHub, patents, funding, regulatory changes. Predict what will trend in 3-6 months based on weak signals.

Use Health Board communicable disease bulletins for outbreak, surveillance, and public-health operations indicators.

Marker gene–based taxonomic profiling using MetaPhlAn 4. Provides accurate species-level relative abundances using clade-specific markers. Use when accurate taxonomic profiling is needed and computational resources are limited, or for comparison with HMP/other MetaPhlAn studies.

Process perform on-chain analysis including whale tracking, token flows, and network activity. Use when performing crypto analysis. Trigger with phrases like "analyze crypto", "check blockchain", or "monitor market".

Use when building dbt models, adding tests, or designing data models. Covers dimensional modeling, model organization (staging/intermediate/marts), testing patterns, and warehouse-specific configurations.

Comprehensive plugin for SAP Datasphere development with three specialized agents, five slash commands, and validation hooks. Use when building data warehouses on SAP BTP, creating analytic models, configuring data flows and replication flows, setting up connections to SAP and third-party systems, managing spaces and users, implementing data access controls, using the Datasphere CLI, creating data products for the marketplace, or monitoring data integration tasks. Covers Data Builder (graphical/SQL views, local/remote tables, transformation flows), Business Builder (business entities, consumption models), analytic models (dimensions, measures, hierarchies), 40+ connection types (SAP S/4HANA, BW/4HANA, HANA Cloud, AWS, Azure, GCP, Kafka, Generic HTTP), real-time replication, task chains, content transport, CLI automation, catalog governance, and data marketplace. Includes 2025 features: Generic HTTP connections, REST API tasks in task chains, SAP Business Data Cloud integration. Keywords: sap datasphere, data warehouse cloud, dwc, data builder, business builder, analytic model, graphical view, sql view, transformation flow, replication flow, data flow, task chain, remote table, local table, sap btp data warehouse, datasphere connection, datasphere space, data access control, elastic compute node, sap analytics cloud integration, datasphere cli, data products, data marketplace, catalog, governance

Generate professional data reports with charts, tables, and visualizations