upstash-vector-db-skills
Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
98 skills found
Upstash Vector DB setup, semantic search, namespaces, and embedding models. Ideal for building high-performance vector search features in Next.js 16/Vercel projects.
High-performance in-memory DataFrame library for Python and Rust. Features lazy evaluation, parallel execution, and an Apache Arrow backend for efficient ETL, data processing, and faster pandas alternatives.
Execute implementation plans in separate sessions with review checkpoints, ensuring task-by-task verification and robust code quality.
A rigorous, four-phase methodology to enforce systematic root cause analysis before applying any code fixes.
Senior backend architecture expert specializing in Hexagonal Architecture, DDD, SOLID principles, clean code, and refactoring to guide development, reviews, and architectural problem-solving.
React Native performance optimization guide covering FPS, TTI, bundle size, memory leaks, and profiling patterns based on Callstack's industry-standard expertise.
Operate Railway infrastructure: manage projects, services, databases, object storage, deployments, environments, variables, logs, and performance metrics.
Implement ReasoningBank adaptive learning with AgentDB's ultra-fast vector backend. Features trajectory tracking, verdict judgment, memory distillation, and pattern recognition for self-learning autonomous agents.
Architectural guidance and pattern implementation for Java Spring Boot backends, covering REST API design, JPA, caching, async processing, and logging.
Implementation guide for Prisma v7 SQL driver adapters, covering SqlDriverAdapter, transaction protocols, error mapping, and verification contracts.
AWS RDS management for provisioning, scaling, and operational maintenance of managed relational databases including MySQL, PostgreSQL, and Aurora.
An intelligent gateway that analyzes, scores, and routes user requests across 27 agents, 27 skills, and 14 MCPs to optimize Claude Code execution.