dst-join-analysis
Perform SQL joins and multi-table analysis on DST data in DuckDB. Use when research requires combining multiple tables on common dimensions (time, region). Provides patterns for common DST dimension joins and m...
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Perform SQL joins and multi-table analysis on DST data in DuckDB. Use when research requires combining multiple tables on common dimensions (time, region). Provides patterns for common DST dimension joins and m...
Fetch actual data from Danmarks Statistik API and store in DuckDB. Use when user wants to download and store specific DST table data for analysis.
Proactively analyzes Parquet file operations and suggests optimization improvements for compression, encoding, row group sizing, and statistics. Activates when users are reading or writing Parquet files or disc...
Check data freshness and age for DST tables in DuckDB. Use when determining if data needs refreshing or validating data currency before analysis.
Design database schemas, plan migrations, optimize queries, and manage data models. Covers relational databases (PostgreSQL, MySQL, SQLite), document databases (MongoDB), and ORM integration (Prisma, Drizzle, T...
Write SQL queries, optimize database performance, design schemas, and debug SQL issues. Use for database operations, query optimization, and schema design.
Parse, analyze, transform, and manipulate CSV files. Use for data processing, cleaning, and CSV operations.
Designs and builds Axiom dashboards via API. Covers chart types, APL patterns, SmartFilters, layout, and configuration options. Use when creating dashboards, migrating from Splunk, or configuring chart options.
Translates Splunk SPL queries to Axiom APL. Provides command mappings, function equivalents, and syntax transformations. Use when migrating from Splunk, converting SPL queries, or learning APL equivalents of SP...
GCP access for developers - BigQuery data analysis, GCS viewing, GKE info (GCP开发者访问:BigQuery、GCS、GKE)
Write, test, deploy, and troubleshoot Ray Data jobs for large-scale data processing with GPU/CPU coordination
Use dtctl CLI tool for querying observability data in Dynatrace via DQL (logs, metrics, traces, ...) and to manage Dynatrace platform resources (workflows, dashboards, notebooks, SLOs, settings, buckets, lookup...
Generate a data specification from a tech spec covering schemas, lifecycle, retention, and access controls. Use when data contracts must be explicit before implementation.
Decide when and how to index Solana data vs direct RPC reads. Covers event design, backfill, storage, and performance. Use for data architecture decisions.
CTO observability stack expertise - Prometheus metrics, Loki logs, Grafana dashboards. Use when querying logs, metrics, or debugging via telemetry.
Implement high-performance virtualization strategies for massive datasets without sacrificing UX.
Generate interactive validation reports with quality scoring, missing data analysis, and type checking. Combines Pandas validation, Plotly visualization, and YAML configuration for comprehensive data quality re...
Process data files through transformation pipelines with validation, cleaning, and export. Use for CSV/Excel/JSON data processing, encoding handling, batch operations, and data transformation workflows.
Execute data processing workflows defined in YAML configuration files. Supports data loading, transformation, validation, and reporting pipelines.
Design schemas, write queries for MongoDB and PostgreSQL. Use for database design, SQL/NoSQL queries, aggregation pipelines, indexes, migrations, replication, performance optimization, psql CLI.
Data engineering agent for ETL pipelines, data warehousing, and analytics
Backend architecture agent for API design, database schema, and microservices
Author SEA-DSL specifications with proper CQRS annotations, validation, and namespace conventions. Use when creating .sea files with entities, flows, and policies that require @cqrs, @tx, @outbox, and @idempote...
Expert data science guidance for analytics, data processing, visualization, statistical analysis, machine learning, and AI integration. Use when analyzing data, building ML models, creating visualizations, proc...
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.