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Plugin data from marketplace errorproof-skills in errorproofdev/skills. Commands read from the repo's manifest — 5 days ago.

Skills (15)

• bigquery-basics

  Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis.

• claimable-postgres

  Provision instant temporary Postgres databases via Claimable Postgres by Neon (pg.new). No login or credit card required. Use for quick Postgres environments and throwaway DATABASE_URL for prototyping.

• database-migration

  Master database schema and data migrations across ORMs (Sequelize, TypeORM, Prisma), including rollback strategies and zero-downtime deployments.

• database-migrations-migration-observability

  Migration monitoring, CDC, and observability infrastructure

• database-migrations-sql-migrations

  SQL database migrations with zero-downtime strategies for PostgreSQL, MySQL, and SQL Server. Focus on data integrity and rollback plans.

• datasets

  Use when the data is already collected and sold as a download, a huge generic corpus needed once where a few months old is fine ("every US company with more than 50 staff", a one-time training set). Also when the user holds a dataset_id that turns out to be a marketplace row, or asks what a ready da

• hugging-face-dataset-viewer

  Query Hugging Face datasets through the Dataset Viewer API for splits, rows, search, filters, and parquet links.

• jq

  Expert jq usage for JSON querying, filtering, transformation, and pipeline integration. Practical patterns for real shell workflows.

• kpi-dashboard-design

  Comprehensive patterns for designing effective Key Performance Indicator (KPI) dashboards that drive business decisions.

• neon-postgres

  Expert patterns for Neon serverless Postgres, branching, connection pooling, and Prisma/Drizzle integration

• polars

  Fast in-memory DataFrame library for datasets that fit in RAM. Use when pandas is too slow but data still fits in memory. Lazy evaluation, parallel execution, Apache Arrow backend. Best for 1-100GB datasets, ETL pipelines, faster pandas replacement. For larger-than-RAM data use dask or vaex.

• postgresql-optimization

  PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.

• scikit-learn

  Machine learning in Python with scikit-learn. Use for classification, regression, clustering, model evaluation, and ML pipelines.

• sql-pro

  Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

• statsmodels

  Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods.

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