Loading...
Loading...
Found 102 Skills
Database performance optimization for MongoDB, PostgreSQL, MySQL, Redis, and ORMs like Prisma and Mongoose. Covers indexes, query patterns, pagination, caching, connection pooling, migration safety, and scaling. Use when optimizing slow queries, designing indexes, reviewing database performance, or improving database scalability.
This skill should be used when user asks to "query MongoDB", "show database collections", "get collection schema", "list MongoDB databases", "search records in MongoDB", or "check database indexes".
MongoDB transaction correctness, consistency, and retry safety. Use when implementing multi-document writes, debugging transaction failures, choosing readConcern/writeConcern, handling TransientTransactionError or UnknownTransactionCommitResult, or deciding when transactions are required. Triggers on "transaction", "withTransaction", "session", "read concern", "write concern", "causal consistency", "snapshot", "retry commit", "ACID", "TransientTransactionError", and "UnknownTransactionCommitResult".
Administer MongoDB databases. Configure replica sets, sharding, and backups. Use when managing MongoDB deployments.
Full-stack Meteor 3.x development with React, MongoDB, async APIs, methods, pub/sub, and GraphQL. Use this skill when working on any Meteor project — writing methods, publications, subscriptions, React data containers, collection helpers, ORM patterns, REST APIs with accounts-express, Meteor-to-React integration via useTracker/withTracker, async migration from Fibers, optimistic UI, DDP, or debugging Meteor-specific issues like circular dependencies, method stubs, and simulation errors. Trigger on: Meteor, Meteor.js, Meteor 3, MeteorJS, callAsync, useTracker, withTracker, Meteor methods, Meteor publications, Meteor subscriptions, SubsManager, Minimongo, DDP, Mongo.Collection, Meteor.Error, optimistic UI, Fibers migration, meteor async, accounts-express.
Guides for configuring Prisma with different database providers (PostgreSQL, MySQL, SQLite, MongoDB, etc.). Use when setting up a new project, changing databases, or troubleshooting connection issues. Triggers on "configure postgres", "connect to mysql", "setup mongodb", "sqlite setup".
Design and optimize database schemas for SQL and NoSQL databases. Use when creating new databases, designing tables, defining relationships, indexing strategies, or database migrations. Handles PostgreSQL, MySQL, MongoDB, normalization, and performance optimization.
Drop-in pandas replacement with ClickHouse performance. Use `import chdb.datastore as pd` (or `from datastore import DataStore`) and write standard pandas code — same API, 10-100x faster on large datasets. Supports 16+ data sources (MySQL, PostgreSQL, S3, MongoDB, ClickHouse, Iceberg, Delta Lake, etc.) and 10+ file formats (Parquet, CSV, JSON, Arrow, ORC, etc.) with cross-source joins. Use this skill when the user wants to analyze data with pandas-style syntax, speed up slow pandas code, query remote databases or cloud storage as DataFrames, or join data across different sources — even if they don't explicitly mention chdb or DataStore. Do NOT use for raw SQL queries, ClickHouse server administration, or non-Python languages.
MySQL relational database. Covers queries, indexes, and optimization. Use when working with MySQL databases. USE WHEN: user mentions "mysql", "mariadb", asks about "AUTO_INCREMENT", "ON DUPLICATE KEY UPDATE", "GROUP_CONCAT", "mysql specific syntax" DO NOT USE FOR: PostgreSQL - use `postgresql` instead, MongoDB - use `mongodb` instead, Oracle - use `oracle` instead, SQL Server - use `sqlserver` instead
Generates Tzatziki-based Cucumber BDD tests (.feature files) from a functional specification. Use this skill whenever a user wants to write Cucumber tests, add BDD scenarios, create feature files, generate tests, or test application behaviors with Gherkin — especially in Java/Spring projects using Tzatziki step definitions for HTTP, JPA, Kafka, MongoDB, OpenSearch, logging, or MCP. Also use when the user mentions writing integration tests, acceptance tests, or end-to-end tests in a project that already has Tzatziki/Cucumber dependencies, including TestNG-based setups.
Manages Amazon DocumentDB end-to-end — serverless-on-8.0 cluster setup, TLS/VPC/driver config, flexible-schema and vector-search data modeling, MongoDB compatibility assessment, DMS-based migration, slow-query diagnosis, major version upgrades (4.0→5.0→8.0), Well-Architected reviews (41-check wa_review.py), cost estimation, and security hardening. Retrieve for every DocumentDB question and when the user asks to set up or migrate MongoDB to AWS — DocumentDB is AWS's MongoDB-compatible managed database. Triggers: JSON document store, document database, MongoDB on AWS, Nested fields, Lambda cannot connect, TLS handshake, VPC port 27017, IAM auth, Secrets Manager, encryption at rest, $graphLookup, flexible schema, COLLSCAN, compound index, DMS migration, CDC cutover, $vectorSearch, RAG, Global Clusters, DR replication, cost sizing, audit, health check, production-readiness.
Migrates databases between providers (Postgres, MySQL, Supabase, PlanetScale, MongoDB). Reads source schema, generates migration scripts, handles data type mapping, foreign keys, indexes, triggers, stored procedures. Validates migration with row counts and checksums. Generates migration-plan.md with step-by-step execution guide, rollback procedures, estimated downtime.