Skill UI

A comprehensive guide to ensuring robust state management for LangGraph agents. This skill addresses common checkpointing pitfalls (like missing thread_id or non-JSON serializable state) and details best practices for implementing reliable state persistence using MemorySaver or PostgresSaver. It covers thread discipline, schema migration, and time-travel debugging for production-ready applications.

A comprehensive guide to advanced, production-ready LLM inference using LangChain 1.0. This skill addresses common pitfalls and bugs when integrating multiple providers (Claude, GPT-4o, Gemini), covering issues like structured output reliability, correct streaming token accounting, and robust handling of complex AIMessage content blocks. It teaches best practices for model initialization, provider routing, and version-safe code implementation.

This guide outlines a robust, two-tier Continuous Integration (CI) strategy for validating Linktree link-in-bio API integrations. It utilizes mock unit tests to verify core functionality (link CRUD, reordering) without needing a live API key. Furthermore, it implements dedicated integration tests on the main branch merge, authenticating with a real Bearer token to confirm link ordering, analytics endpoints, and rate limit handling against the live Linktree API, ensuring production-ready code quality.

A comprehensive, production-ready reference architecture for integrating with the Miro REST API v2. It implements modern layered design principles, managing OAuth 2.0 token lifecycles, processing webhooks, and providing robust services for board synchronization, item creation, and data caching. Ideal for building complex, scalable enterprise SaaS integrations.

A comprehensive guide providing production-ready, structured patterns for interacting with the Miro API. It covers best practices for both the high-level stateful client usage and the low-level REST API v2. Includes patterns for implementing robust Board Services (fetching, pagination) and Item Factories (creating various elements like sticky notes, shapes, and cards). Essential for developers building SaaS applications or complex automation workflows using Miro.

A comprehensive skill for deploying production-ready Node.js applications that utilize the Notion API to serverless platforms like Vercel, Railway, or Fly.io. This guide implements critical best practices including Notion client singletons for serverless environments, robust rate limit handling (3 req/sec), response caching strategies, and essential health check endpoints to ensure stability and scalability in production.

This guide provides production-ready patterns for integrating with the Notion API using official SDKs for TypeScript and Python. It covers advanced techniques including client initialization, executing complex database queries with filters and sorts, implementing cursor-based pagination for large datasets, constructing and manipulating rich text blocks, and ensuring robust, type-safe error handling.

A comprehensive, step-by-step guide for managing Notion API integrations. Learn how to upgrade both the Node.js (@notionhq/client) and Python (notion-client) SDKs, handle major version breaking changes, and properly manage API version pinning (e.g., 2022-06-28) to ensure stable, production-ready applications.

This skill provides a comprehensive Python guide to building a production-ready Virtual Cloud Network (VCN) on Oracle Cloud Infrastructure (OCI). It details the entire process from scratch, including creating the VCN, setting up Internet and NAT Gateways, configuring route tables, and defining Network Security Groups (NSGs). This is essential for engineers needing to provision complex, secure, and highly functional network architectures for development or production use.

Provides a comprehensive, production-ready standard 3-tier reference architecture for Oracle Cloud Infrastructure (OCI). The design covers essential components like VCN, public/private subnets, Internet Gateway, NAT Gateway, Service Gateway, and Autonomous Database. It includes deployment steps using Terraform and OCI SDK Python code, making it ideal for designing new cloud environments or migrating existing patterns from other major cloud providers.

This skill provides a comprehensive guide for deploying Palantir Foundry integrated applications to major cloud platforms, such as GCP Cloud Run, AWS Lambda, and Docker. It covers best practices including containerization using Docker, implementing robust secrets management via cloud secret managers, establishing health check endpoints, and configuring environment-specific scopes. This process ensures applications are production-ready, secure, and highly available.

This guide provides production-ready patterns for integrating with the Palantir Foundry Platform SDK. It covers essential best practices like implementing thread-safe singletons, structured error handling, automatic pagination for large data sets, and robust retry mechanisms with exponential backoff. Ideal for refactoring existing Foundry integrations or establishing team coding standards.