context-engineering-collection
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
231 skills found
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Language-agnostic backend architectural patterns covering API design, authentication, security protocols, and database modeling.
Generate professional markdown newsletters from localized events stored in SQLite. Automates event aggregation, curation, and formatting for community or niche media newsletters.
Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.
Java development skill for writing clean, maintainable code using SOLID principles, pragmatic abstraction, and self-documenting practices.
Implement consumer-driven contract testing for microservices using Pact, schema validation, and API versioning to prevent breaking changes and ensure distributed team coordination.
Implement comprehensive TypeScript authentication and authorization using Better Auth, supporting OAuth, 2FA, passkeys, sessions, and multi-tenant features.
Executes SQL queries against the WordPress development database for inspection, troubleshooting, and audit log analysis.
Implement Linkerd service mesh patterns for security, traffic policy management, and zero-trust networking in Kubernetes environments.
Scaffold and build interactive MCP Apps with custom UIs for hosts like Claude Desktop. Supports React, Vanilla JS, and various framework templates for tool-resource integration.
Expert guidance for Neo4j Cypher queries and MCP server tools, focusing on schema introspection, graph operations, and efficient database development workflows.
Build RAG systems to ground LLMs in proprietary data. Includes vector database integration, embedding strategies, hybrid search, and advanced retrieval patterns for FastAPI backends.