Patrones de FirestoreRepository: paths, subcolecciones, métodos CRUD, sanitización de timestamps. Trigger: Cuando se crea un repositorio, se trabaja con paths de Firestore, o se necesitan métodos custom.
Index a folder's contents into the context system for fast retrieval and discovery. Activate when: "index this folder", "catalog these files", folder contents indexed, build file index, scan folder Do NOT activate for: saving decisions to context (/context-save), recalling context (/context-recall), plugin setup (/setup)
Create a database cluster on KubeBlocks using the generic Cluster CR template. Supports all addons (MySQL, PostgreSQL, Redis, MongoDB, Kafka, Elasticsearch, Milvus, Qdrant, etc.) with various topologies. Use when the user wants to deploy, create, provision, or launch a new database cluster — especially for engines without a dedicated addon-* skill. For MySQL, PostgreSQL, Redis, MongoDB, or Kafka, prefer the engine-specific addon skill (kubeblocks-addon-mysql, kubeblocks-addon-postgresql, kubeblocks-addon-redis, kubeblocks-addon-mongodb, kubeblocks-addon-kafka) which provides topology guidance and tuned defaults. NOT for managing existing clusters (see Day-2 operation skills).
Deploy and manage Elasticsearch clusters on KubeBlocks for full-text search, log analytics, and observability. Use when the user mentions Elasticsearch, ELK stack, search engine, log analytics, Kibana, full-text search, or explicitly wants to create an Elasticsearch cluster. Provides single-node (dev/test) and multi-node cluster creation with connection methods. No backup/restore support in KubeBlocks currently. For generic cluster creation across all engines, see kubeblocks-create-cluster. For Day-2 operations (scaling, volume expansion, etc.), use the corresponding operation skill.
Schema Management is the discipline of defining, versioning, and evolving the structure of data. In a distributed system, a change in one service's schema can have a cascading "breaking" effect on doz
Comprehensive guide for vector search implementation covering HNSW (Hierarchical Navigable Small World), IVF (Inverted File Index), Flat Index implementations, distance metrics (cosine, Euclidean, dot
Redis performance optimization and best practices. Use this skill when working with Redis data structures, Redis Query Engine (RQE), vector search with RedisVL, semantic caching with LangCache, or optimizing Redis performance.
How the @repo/redis package works in this repo. ioredis wrapper with caching patterns. Use when: adding caching to controllers, building cache keys, invalidating cache, or debugging Redis issues.
Complete guide for Testcontainers NoSQL integration testing. Use when containerized integration testing for MongoDB or Redis. Covers MongoDB document operations, Redis five data structures, Collection Fixture pattern. Includes BSON serialization, index performance testing, data isolation strategy, and container lifecycle management. Keywords: testcontainers mongodb, testcontainers redis, mongodb integration test, redis integration test, nosql testing, MongoDbContainer, RedisContainer, IMongoDatabase, IConnectionMultiplexer, BSON serialization, BsonDocument, document model testing, cache testing, Collection Fixture
Master MongoDB aggregation pipeline for complex data transformations. Learn pipeline stages, grouping, filtering, and data transformation. Use when analyzing data, creating reports, or transforming documents.
Specialized skill for designing AWS DynamoDB single-table schemas with optimized access patterns. Use when modeling data, designing table structure, or optimizing DynamoDB queries for production applications.
Master MongoDB schema design and data modeling patterns. Learn embedding vs referencing, relationships, normalization, and schema evolution. Use when designing databases, normalizing data, or optimizing queries.
Drizzle ORM documentation covering queries, CRUD operations, schema definitions, migrations, caching (50 topics), custom types, and database connections. Includes integrations for PostgreSQL (Neon, Vercel, Supabase, AWS Data API, PlanetScale, Prisma), MySQL (AWS Data API, PlanetScale, TiDB), and SQLite (Bun, Cloudflare D1/Durable Objects, Expo, Turso, OP SQLite). Use when working with Drizzle queries, database schemas, migrations, type-safe SQL, ORM patterns, or connecting to supported databases.
Episodic Memory Archiver. Stores full conversation transcripts with embeddings and analysis into ArangoDB. Tracks UNRESOLVED sessions for reflection with structured failure episodes (trigger/diagnosis/action/outcome), K~4 similar failure retrieval, user behavioral profiling, and federated taxonomy classification.
Redis and Upstash Vector integration patterns for rate-limiting, vector search, embeddings, and memory systems. Use when implementing caching, rate-limiting, or semantic search features.
ZeroDB vector database best practices, semantic search patterns, RLHF workflows, and memory management. Use when working with ZeroDB APIs, vector search, or AI memory systems.
Master MongoDB replication, replica sets, and sharding for distributed deployments. Learn failover, shard keys, and cluster management. Use when setting up high availability or scaling horizontally.
