Claude Skills by LoopyLuci

Use when integrating beauty and wellness.

Use when implementing BDD with Gherkin and Cucumber.

Use when applying beneficial ownership best practices.

Use when applying beneficial ownership fundamentals.

Use when applying beneficial ownership implementation.

Use when applying beneficial ownership troubleshooting.

Use when implementing ROV/ROA.

Use when implementing BGP routing and traffic engineering.

Use when applying bible study groups best practices.

Use when applying bible study groups fundamentals.

Use when applying bible study groups implementation.

Use when applying bible study groups troubleshooting.

Use when applying big data best practices.

Use when applying big data fundamentals.

Use when applying big data implementation.

Use when applying big data pipelines best practices.

Use when applying big data pipelines fundamentals.

Use when applying big data pipelines implementation.

Use when applying big data pipelines troubleshooting.

Use when building big data pipelines.

Use when for big data processing best practices.

Use when for big data processing fundamentals.

Use when for big data processing implementation.

Use when for big data processing troubleshooting.

Use when applying big data troubleshooting.

**Trigger**: Use when working with Google Cloud Bigquery Ai Ml — setup, configuration, and best practices. BigQuery integrates with Vertex AI to provide powerful machine learning and generative AI capabilities directly within SQL queries using built-in functions like `AI.FORECAST`, `AI.KEY_DRIVERS`, `AI.DETECT_ANOMALIES`, and `AI.GENERATE`.

Use when applying bigquery analytics best practices.

Use when applying bigquery analytics fundamentals.

Use when applying bigquery analytics implementation.

Use when applying bigquery analytics troubleshooting.

Use when querying with BigQuery.

Use when querying with BigQuery.

**Trigger**: Use when working with Google BigQuery — querying, partitioning, clustering, cost controls, and best practices. BigQuery is a serverless, AI-ready data platform that enables high-speed analysis of large datasets using SQL and Python. Its disaggregated architecture separates compute and storage, allowing them to scale independently while providing built-in machine learning, geospatial analysis, and business intelligence capabilities.

Use when for bigquery best practices.

**Trigger**: Use when working with Google Cloud Bigquery Bigframes — setup, configuration, and best practices. BigFrames is a Python library that lets you take advantage of BigQuery data processing by using familiar Python APIs.

Use when applying bigquery fundamentals best practices.

Use when applying bigquery fundamentals fundamentals.

Use when applying bigquery fundamentals implementation.

Use when applying bigquery fundamentals troubleshooting.

Use when for bigquery fundamentals.

Use when applying bigquery implementation best practices.

Use when applying bigquery implementation fundamentals.

Use when applying bigquery implementation implementation.

Use when applying bigquery implementation troubleshooting.

Use when for bigquery implementation.

Use when applying bigquery troubleshooting best practices.

Use when applying bigquery troubleshooting fundamentals.

Use when applying bigquery troubleshooting implementation.

Use when applying bigquery troubleshooting troubleshooting.

Use when for bigquery troubleshooting.