rag-implementation
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
241 skills found
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
TypeScript development standards for LobeHub, covering type safety, async patterns, import organization, UI component integration, and performance optimization.
Systematic methodology for reproducing published academic papers using provided data, including sample selection, statistical verification, and automated reporting.
Generate, validate, and refine Mermaid diagrams including flowcharts, sequence diagrams, ERDs, and architecture maps to visualize complex software systems and workflows.
A comprehensive library of 305+ modular instruction packages, Python CLI tools, and agent workflows designed to extend the capabilities of AI coding assistants like Claude Code, Cursor, Aider, and Gemini CLI.
Fetch real-time financial signals, transmission-chain reasoning, and market confidence metrics directly from the DeepEar Lite platform.
A security scanner for Claude Skills to detect malicious code, data exfiltration risks, and unauthorized system access before installation.
Optimizes Prisma Client connection pool settings for production databases, serverless environments, and high-concurrency architectures to prevent connection exhaustion and performance bottlenecks.
Provision and manage Railway database services (Postgres, Redis, MySQL, MongoDB) with automated configuration and environment wiring.
A comprehensive Next.js 15 development and project management skill for Claude Code, featuring Supabase integration, RBAC, and automated quality validation.
Parses and processes SARIF files from static analysis tools. Enables aggregation, deduplication, filtering, and CI/CD integration of scan results.
Write, structure, and maintain technical documentation like READMEs, API docs, runbooks, and architecture specs to keep your team aligned and informed.