Skills correspondant au nom, à la description ou à l’auteur GitHub.
PyTiDB (pytidb) setup and usage for TiDB from Python. Covers connecting, table modeling (TableModel), CRUD, raw SQL, transactions, vector/full-text/hybrid search, auto-embedding, custom embedding functions, and...
Analyze datasets to extract insights, identify patterns, and generate reports. Use when exploring data, creating visualizations, or performing statistical analysis. Handles CSV, JSON, SQL queries, and Python pa...
Expert assistance for using pytd (Python SDK) to query and import data with Treasure Data. Use this skill when users need help with Python-based data analysis, querying Presto/Hive, importing pandas DataFrames,...
Creates bauplan data pipeline projects with SQL and Python models. Use when starting a new pipeline, defining DAG transformations, writing models, or setting up bauplan project structure from scratch.
Run Earthly E2E validation for YAML schema contracts. Use when validating YAML schema changes, testing schema contracts against live ClickHouse, or regenerating Python types, DDL, and docs from YAML. For SQL sc...
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, real-time streaming, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, Flink, Kinesis, and...
Execute code on Databricks clusters using MCP Command Execution API. Supports stateless quick validation and stateful iterative development. Use when testing Python/SQL code on clusters, debugging pipelines, or...
Python DAG workflow orchestration using Apache Airflow for data pipelines, ETL processes, and scheduled task automation
Expert agent for debugging Keboola Python components using Keboola MCP tools, Datadog logs, and local testing. Specializes in identifying root causes of failures and providing actionable fixes.
Python FastAPI patterns, Alembic migrations, Pydantic v2, and AI Engineering (raw patterns, LangChain, Google ADK). This skill should be used when working with Python APIs, database migrations, or AI/LLM applic...
Generates production-ready BAML applications from natural language requirements. Creates complete type definitions, functions, clients, tests, and framework integrations for data extraction, classification, RAG...
Chunked N-D arrays for cloud storage. Compressed arrays, parallel I/O, S3/GCS integration, NumPy/Dask/Xarray compatible, for large-scale scientific computing pipelines.
Use this skill when writing or updating SQL queries (query.sql) or Python ETL scripts (query.py) following Mozilla BigQuery ETL conventions. ALWAYS checks for and updates existing tests when modifying queries....
Build, deploy, monitor, and troubleshoot production Nexla data pipelines via Python SDK or REST API. Use for flow setup, data transformation pipelines, schema management, access control, credential rotation, ba...
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...
Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts. Use when you need to analyze datasets, perform statistical tests, create...
This skill should be used when the user asks to "work with polars", "create a dataframe", "use lazy evaluation", "migrate from pandas", "optimize data pipelines", "read parquet files", "group by operations", or...
Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts. Use when you need to analyze datasets, perform statistical tests, create...
Python dataclass best practices: slots, frozen, validation. Trigger when optimizing dataclasses or creating config classes.
Use the domino-data Python SDK (dominodatalab-data) for programmatic data access in Domino. Covers DataSourceClient for SQL queries and object storage, DatasetClient for dataset files, TrainingSets for ML data...
Perform comprehensive data analysis, statistical modeling, and data visualization by writing and executing self-contained Python scripts. Use when you need to analyze datasets, perform statistical tests, create...
Fast in-process analytical database for SQL queries on DataFrames, CSV, Parquet, JSON files, and more. Use when user wants to perform SQL analytics on data files or Python DataFrames (pandas, Polars), run compl...
Comprehensive Python data engineering patterns for AWS Data Lake, including PySpark, Pandas, Apache Airflow, AWS Glue, ETL pipelines, data quality, schema management, performance optimization, FastAPI services,...
A skill for using Databricks SQL (SQL Warehouse) via SDK. Supports both Python (databricks-sql-connector) and Node.js (@databricks/sql). Use when: - Connecting to SQL Warehouse from Databricks Apps to execute...
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.