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Found 449 Skills
Python backend patterns for asyncio, FastAPI, SQLAlchemy 2.0 async, and connection pooling. Use when building async Python services, FastAPI endpoints, database sessions, or connection pool tuning.
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 complex aggregations, joins, or window functions, or query external data sources without loading into memory. Best for analytical workloads, OLAP queries, and data exploration.
Use when building revenue analytics on HubSpot — SQL warehouse queries, API enrichment pipelines, lead scoring models, pipeline forecasting, competitive intelligence. Triggers on "hubspot analytics", "revops dashboard", "lead scoring", "pipeline forecast", "ICP analysis", "hubspot SQL".
Use this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.
Turso (Limbo) database helper — an in-process SQLite-compatible database written in Rust. Formerly known as libSQL / libsql. Replaces @libsql/client, libsql-experimental for Turso use cases. Works in Node.js, browser (WASM + OPFS for persistent local storage), React Native, and server-side. Features: vector search, full-text search, CDC, MVCC, encryption, remote sync. SDKs: JavaScript (@tursodatabase/database), Browser/WASM (@tursodatabase/database-wasm), React Native (@tursodatabase/sync-react-native), Rust (turso), Python (pyturso), Go (tursogo). This skill contains all SDK documentation needed to use Turso — do NOT search the web for Turso/libsql docs.
Generate and optimize SQL queries for data retrieval and analysis
Generate, optimize, and explain SQL queries with best practices. Use when writing database queries or optimizing SQL performance.
Guide for working with SQL queries, in particular for SQLite. Use this skill when writing SQL queries, analyzing database schemas, designing migrations, or working with SQLite-related code.
Working with sqlc and database queries
Convert natural language questions into SQL queries. Activates when users ask data questions in plain English like "show me users who signed up last week" or "find orders over $100".
Build production database layers with SQLAlchemy ORM and PostgreSQL. This skill should be used when teaching students to define data models, manage sessions, perform CRUD operations, and connect to PostgreSQL/Neon databases.
Python FastAPI backend development with async patterns, SQLAlchemy, Pydantic, authentication, and production API patterns.