按技能名称、说明或 GitHub 作者匹配的结果。
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...
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...
Python specialist for Faiston One Platform. Use when writing FastAPI endpoints, Google ADK agents, async patterns, Pydantic models, and Lambda handlers. PROACTIVE for code review and refactoring.
Converts Python report scripts (Elasticsearch queries + email output) into Grafana Jsonnet dashboards with dual-datasource support (ClickHouse + Elasticsearch ES7/ES8). Use when migrating scheduled email report...
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data mode...
ALWAYS USE when working with dbt models, SQL transformations, tests, snapshots, or macros. Use IMMEDIATELY when editing dbt_project.yml, profiles.yml, or creating SQL models. MUST be loaded before any transform...
Expert guidance for Polars dataframe manipulation in Python. Use this skill when working with dataframes, data processing, ETL pipelines, or any task involving tabular data manipulation. Provides best practices...
FastAPI + Pydantic v2 backend workflow: implement/modify API endpoints with thin handlers + service layer, add pytest tests, manage idempotent Alembic migrations, and implement streaming ETL/parsers with invali...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。