database-operations
Manage MongoDB database operations including backup, restore, and maintenance
Manage MongoDB database operations including backup, restore, and maintenance
Redis caching patterns, cache-aside, write-through, TTL strategies, and invalidation. Activate on: caching, Redis, cache invalidation, cache-aside, write-through, TTL, CDN cache, stale-while-revalidate. NOT for: CDN/reverse proxy setup (use api-gateway-reverse-proxy-expert), database query optimization (use data-warehouse-optimizer).
Firestore/データベースに関する作業で必ずFIRESTORE.mdを読み込むためのルール。DB設計、コレクション追加、Firestore変更、スキーマ更新、データベース設計・作成・更新・書き換えなどの依頼時に使う。
libresource - Typed resource management with access control. ResourceIndex stores and retrieves resources with policy-based authorization. toInstance converts objects to typed instances. toResourceId parses URI strings. createResourceIndex factory. Use for persisting structured data, managing entities, and enforcing access control.
libindex - Base index class for storage-backed data. Index class provides JSONL storage operations and filtering logic. BufferedIndex adds high-volume write support with periodic flushing. Use for building custom indexes, implementing data stores, and managing persistent collections.
Use for the public module API, DataSync integration, and MongoDB-related configuration for this content store.
Practical guidance for content-hash caching patterns in AI/data systems.
Use when adding new SQLAlchemy 2 models in libs/db/skillhub_db/models/
Redis caching strategies, pub/sub, sessions, and performance optimization.
Database modeling, migrations, queries, and performance optimization with Prisma.
LlamaIndex for document processing, indexing strategies, and retrieval optimization.
Create MongoDB models using Typegoose following project conventions. Use when defining database schemas, creating new models, working with embedded documents, adding indexes for query optimization, or exporting type-safe model instances.
Manage redis cache manager operations. Auto-activating skill for Backend Development. Triggers on: redis cache manager, redis cache manager Part of the Backend Development skill category. Use when working with redis cache manager functionality. Trigger with phrases like "redis cache manager", "redis manager", "redis".
Implement intelligent API response caching with Redis, Memcached, and CDN integration. Use when optimizing API performance with caching. Trigger with phrases like "add caching", "optimize API performance", or "implement cache layer".
Use wagl (DB-first memory) via plugin tools: wagl_recall, wagl_store, wagl_search, wagl_forget.
Use when configuring LibreChat's MongoDB database, Redis caching, MeiliSearch message search, file storage strategy (local vs CDN/S3), or PGVector for RAG. Also use when asked about database backup, connection strings, or storage scaling.
Guidelines for implementing new database backends for rhosocial-activerecord - dialect, type adapter, config, and storage backend
RuVector-powered graph database CLI with Cypher queries, hyperedges, ACID persistence, and 150x faster vector search. Use when managing graph data stores, running Cypher queries, performing vector similarity search, managing database schemas, or building knowledge graphs for AI agents.
Distributed clustering and auto-sharding for RuVector with Raft consensus, node discovery, and rebalancing. Use when building distributed vector databases, adding horizontal scaling to vector search, or coordinating multi-node RuVector deployments with automatic failover.
High-performance HNSW vector database core built in Rust with N-API bindings - 50k+ inserts/sec, sub-ms search. Use when building vector search applications, adding nearest-neighbor indexing to Node.js projects, or needing a fast embedded vector store with metadata filtering.
HNSW vector indexing engine with 50k+ inserts/sec via Rust NAPI bindings. Use when the user needs to build high-performance vector search in Node.js, create HNSW indexes, perform batch vector operations, or integrate similarity search into backend applications.
Advanced extensions for RuVector: embedding generation, admin UI, data export, temporal versioning, and persistence adapters. Use when adding embedding pipelines, visualizing vector data, exporting indexes, or tracking vector changes over time.
Native Node.js graph database bindings with hypergraph support, Cypher queries, and persistence. Use when the user needs a graph database in Node.js, Cypher query execution, vertex/edge CRUD operations, graph traversals, shortest path algorithms, or hypergraph data modeling.