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Found 22 Skills
Complete Convex development mastery — functions (queries, mutations, actions, HTTP actions), schema design, index optimization, argument/return validation, authentication, security patterns, error handling, file storage, scheduling, crons, aggregates, OCC handling, denormalization, TypeScript best practices, and production-ready code organization. The definitive Convex skill. Use when building any Convex backend: writing functions, designing schemas, optimizing queries, handling auth, adding real-time features, setting up webhooks, scheduling jobs, managing file uploads, or reviewing/fixing Convex code. Triggers on: convex, query, mutation, action, ctx.db, defineSchema, defineTable, v.id, v.string, v.object, withIndex, ConvexError, internalMutation, httpAction, ctx.scheduler, ctx.storage, OCC, convex best practices, convex functions, convex schema, convex performance, "how do I do X in Convex".
Guide for Convex schema design, validators, and TypeScript types. Use when defining database schemas, creating validators for function arguments/returns, working with document types, or ensuring type safety. Activates for schema.ts creation, validator usage, Id/Doc type handling, or TypeScript integration tasks.
Design database schemas with proper normalization, relationships, constraints, and indexes. Use when creating database tables, modeling data relationships, or designing database structure.
Best practices for Convex database queries, indexes, and filtering. Use when writing or reviewing database queries in Convex, working with `.filter()`, `.collect()`, `.withIndex()`, defining indexes in schema.ts, or optimizing query performance.
Comprehensive guide for Firestore enterprise native including provisioning, data model, security rules, and SDK usage. Use this skill when the user needs help setting up Firestore Enterprise with the Native mode, writing security rules, or using the Firestore SDK in their application.
Review and improve HelixDB query performance and query shape. Use when the task is to optimize a slow Helix query, improve anchor choice, tighten index usage, reduce traversal breadth, slim projections, fix BM25 or vector search scope, or decide between stored and dynamic routes.
Transform slow database queries into lightning-fast operations through systematic optimization, proper indexing, and query plan analysis.
MySQL and MariaDB schema, query, indexing, transaction, replication, and connection-pool patterns for production backends.
Optimizes ClickHouse queries for speed and efficiency. Helps with primary key design, sparse indexes, data skipping indexes (minmax, set, bloom filter, ngrambf_v1), partitioning strategies, projections, PREWHERE optimization, approximate functions, and query profiling with EXPLAIN. Use when writing ClickHouse queries, designing table schemas, analyzing slow queries, or implementing analytical aggregations. Works with columnar OLAP workloads.
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