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Found 626 Skills
Develops and executes Spark code on Dataproc Clusters and Serverless. Reads and writes data using BigLake Iceberg catalogs, BigQuery and Spanner. Debugs execution failures. Use when: - Writing Spark ETL pipelines on GCP. - Training or running inference with ML models with spark on GCP. - Managing Spark clusters, jobs, batches, and interactive sessions. Don't use when: - Writing generic Python scripts that don't use Spark. - Performing simple SQL queries that can be done directly in BigQuery.
Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Redshift, Snowflake, and BigQuery. Gathers connection hints from user, discovers existing connections and RDS/Redshift candidates, registers credentials in Secrets Manager or IAM DB auth, configures VPC, and tests. Triggers on: connect to database, set up Glue connection, register data source, connect to Snowflake/BigQuery/RDS, connection timeout, test connection, troubleshoot connection. Do NOT use for moving data (use ingesting-into-data-lake), creating tables (use creating-data-lake-table), queries (use querying-data-lake), catalog exploration (use exploring-data-catalog), or SaaS (Salesforce, ServiceNow, SAP, MongoDB, Kafka).
Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.
World-class database schema design - data modeling, migrations, relationships, and the battle scars from scaling databases that store billions of rowsUse when "database schema, data model, migration, prisma schema, drizzle schema, create table, add column, foreign key, primary key, uuid, auto increment, soft delete, normalization, denormalization, one to many, many to many, junction table, polymorphic, enum type, index strategy, database, schema, migration, data-model, prisma, drizzle, typeorm, postgresql, mysql, sqlite" mentioned.
Security-focused code review checklist and automated scanning patterns. Use when reviewing pull requests for security issues, auditing authentication/authorization code, checking for OWASP Top 10 vulnerabilities, or validating input sanitization. Covers SQL injection prevention, XSS protection, CSRF tokens, authentication flow review, secrets detection, dependency vulnerability scanning, and secure coding patterns for Python (FastAPI) and React. Does NOT cover deployment security (use docker-best-practices) or incident handling (use incident-response).
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 reference templates/snippets (vector/hybrid/image) plus agent-oriented examples (RAG/memory/text2sql).
SmartACE (Agentic Context Engineering) workflow engine with MCP-B (Master Client Bridge) and AMUM-QCI-ETHIC module. Dual database architecture using DuckDB (analytics) + SurrealDB (graph). Uses Blender 5.0 (bpy) and UE5 Remote Control. Use when (1) MCP-B agent-to-agent communication (INQC protocol), (2) AMUM 3→6→9 progressive alignment, (3) QCI quantum coherence states, (4) ETHIC principles enforcement (Marcel/Anthropic/EU AI Act), (5) SurrealDB graph relationships, (6) DuckDB SQL workflows, (7) ML inference with infera/vss, (8) Blender 5.0 headless processing, (9) UE5 scene control, (10) DuckLake time travel.
Run Psalm with taint analysis on PHP code. Detects SQL injection, XSS, command injection, path traversal, and other taint-flow vulnerabilities in PHP applications.
Run gosec SAST scans on Go code. Detects SQL injection, hardcoded credentials, insecure TLS, command injection, and other Go security issues.
Security auditing for code vulnerabilities (OWASP Top 10, XSS, SQL injection) and dependency scanning (pnpm audit, Snyk). Use when handling user input, adding authentication, before deployments, or resolving CVEs.
Provides comprehensive Google Cloud Platform (GCP) guidance including Compute Engine, Cloud Storage, Cloud SQL, BigQuery, GKE (Google Kubernetes Engine), Cloud Functions, Cloud Run, VPC networking, load balancing, IAM, Cloud Build, infrastructure as code (Terraform, Deployment Manager), security configuration, cost optimization, and multi-region deployment. Produces infrastructure code, deployment scripts, configuration guides, and architecture designs. Use when deploying to Google Cloud, designing GCP infrastructure, migrating to GCP, configuring GCE instances, setting up Cloud Storage, managing Cloud SQL databases, working with BigQuery, deploying to GKE, or when users mention "Google Cloud", "GCP", "Compute Engine", "Cloud Storage", "BigQuery", "GKE", "Cloud Run", "Cloud Functions", "VPC", "Cloud SQL", or "Google Cloud Platform".
Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode.