Découvrez les skills tools data engineering, comparez leurs dépôts et consultez leurs instructions.
Parses complex problems into DAG (Directed Acyclic Graph) execution structures. Decomposes tasks into nodes with dependencies, identifies parallelization opportunities, and creates optimal execution plans. Acti...
Executes DAG waves with controlled parallelism using the Task tool. Manages concurrent agent spawning, resource limits, and execution coordination. Activate on 'execute dag', 'parallel execution', 'concurrent t...
End-to-end DAG execution orchestrator that decomposes arbitrary tasks into agent graphs and executes them in parallel. The intelligence layer that makes DAG Framework operational.
Expert in background job processing with Bull/BullMQ (Redis), Celery, and cloud queues. Implements retries, scheduling, priority queues, and worker management. Use for async task processing, email campaigns, re...
Review data handling for privacy and retention. Use when a senior developer needs governance validation.
Plan a zero-downtime migration for data or infrastructure. Use when a senior developer needs a safe migration strategy.
Deploying and managing Snowflake database objects using version control with schemachange. Use this skill when you need to manage database migrations for objects not handled by dbt, implement CI/CD pipelines fo...
Complete workflow for migrating legacy database DDL (views, tables, stored procedures) to dbt projects on Snowflake. This skill orchestrates the full migration lifecycle including discovery, planning, placehold...
Executing SQL, managing Snowflake objects, deploying applications, and orchestrating data pipelines using the Snowflake CLI (snow) command. Use this skill when you need to run SQL scripts, deploy Streamlit apps...
Configuring Snowflake connections using connections.toml (for Snowflake CLI, Streamlit, Snowpark) or profiles.yml (for dbt) with multiple authentication methods (SSO, key pair, username/password, OAuth), managi...
Managing dbt-core locally - installation, configuration, project setup, package management, troubleshooting, and development workflow. Use this skill for all aspects of local dbt-core development including non-...
Step-by-step setup guide for dbt Projects on Snowflake including prerequisites, external access integration, Git API integration, event table configuration, and automated scheduling. Use this skill when setting...
Deploying, managing, executing, and monitoring dbt projects natively within Snowflake using dbt PROJECT objects and event tables. Use this skill when you want to set up dbt development workspaces, deploy projec...
dbt testing strategies using dbt_constraints for database-level enforcement, generic tests, and singular tests. Use this skill when implementing data quality checks, adding primary/foreign key constraints, crea...
Writing dbt models with proper CTE patterns, SQL structure, and layer-specific templates. Use this skill when writing or refactoring dbt models, implementing CTE patterns, creating staging/intermediate/mart mod...
dbt command-line operations, model selection syntax, Jinja patterns, troubleshooting, and debugging. Use this skill when running dbt commands, selecting specific models, debugging compilation errors, using Jinj...
Developing, testing, and deploying Streamlit data applications on Snowflake. Use this skill when you're building interactive data apps, setting up local development environments, testing with pytest or Playwrig...
Optimizing dbt and Snowflake performance through materialization choices, clustering keys, warehouse sizing, and query optimization. Use this skill when addressing slow model builds, optimizing query performanc...
Choosing and implementing dbt materializations (ephemeral, view, table, incremental, snapshots, Python models). Use this skill when deciding on materialization strategy, implementing incremental models, setting...
Monitor dbt execution using the dbt Artifacts package. Use this skill when you need to track test and model execution history, analyze run patterns over time, monitor data quality metrics, or enable programmati...
Ultra-fast data discovery and loading skill for industrial finance datasets. Handles CSV, JSON, DuckDB, Parquet, and Feather with memory-efficient 2-step discovery and loading.
Tech Lead for Claude Orchestrator. Creates implementation instructions based on planning documents and design specifications. Use when asked to create developer instructions or technical implementation guides f...
EDA toolkit. Analyze CSV/Excel/JSON/Parquet files, statistical summaries, distributions, correlations, outliers, missing data, visualizations, markdown reports, for data profiling and insights.
Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.
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.