Skill UI

This guide sets up a fast, cost-effective local development loop for building applications powered by the Anthropic API (Claude). It includes instructions for hot reloading, cost-saving tips (e.g., using Haiku, token limits), and mock client implementation for robust unit testing. It supports both TypeScript/Node.js and Python environments, streamlining the AI development workflow.

Provides best practices for configuring Large Language Model (LLM) access, specifically for Anthropic Claude, across development, staging, and production environments. This guide details setting up separate API keys, selecting appropriate models (e.g., Haiku, Sonnet, Opus), and managing unique rate limits for robust, scalable, and secure LLM integration in enterprise systems.

This guide details essential best practices for securing applications integrated with Anthropic's Claude API. It covers critical security measures including secure API key management (server-side only), robust input validation to prevent cost attacks, defense mechanisms against prompt injection, and implementing per-user rate limiting. Essential reading for maintaining data privacy and system integrity in production environments.

Automate the execution of integration tests against a live ClickHouse database instance within a Continuous Integration (CI) pipeline using Docker containers. This setup eliminates the need for mocks, ensuring thorough schema validation and query reliability in environments mirroring production deployments. Ideal for robust CI/CD setup and schema enforcement.

A comprehensive guide and code pattern for configuring ClickHouse instances across development, staging, and production environments. It emphasizes best practices for infrastructure-as-code (IaC), secure secrets management (integrating AWS Secrets Manager, Vault, etc.), and ensuring environment-specific settings are correctly applied for reliable data analytics pipelines.

This guide provides a comprehensive strategy for configuring ClickUp API access across development, staging, and production environments. It emphasizes the critical importance of environment isolation using separate API tokens and dedicated workspaces to prevent data leaks and accidental destructive operations in live environments. Includes best practices for secret management (Vault, AWS, GCP) and implementing environment guards.

This comprehensive checklist guides developers through deploying ClickUp API v2 integrations to a production environment. It covers critical areas including secure authentication (secrets management, service accounts), robust error handling (rate limiting, exponential backoff, circuit breakers), monitoring setup, and defined rollback procedures, ensuring stable and reliable API deployments.

A comprehensive guide to securing ClickUp API usage. Learn best practices for managing API tokens, implementing least-privilege access, and auditing usage patterns. This includes secure token rotation procedures, using environment variables, setting up pre-commit hooks to prevent leaks, and structuring calls for robust audit logging.

A comprehensive guide to configuring robust CI/CD pipelines for Cohere API v2 applications. This skill covers setting up automated unit tests (mocked responses) and critical integration tests (real API calls) within environments like GitHub Actions. It ensures the stability and reliability of Cohere-powered features such as Chat, Embeddings, and Rerank across development cycles.

A comprehensive guide for configuring and integrating the Cohere API v2 across development, staging, and production environments. This pattern ensures environment-specific settings—including API keys, model selections, token limits, and caching strategies—are correctly applied. It covers best practices for secure secret management using tools like Vault, AWS Secrets Manager, and GCP Secret Manager, ensuring robust and scalable deployments.

Detailed guide on securing Cohere API integration. Covers best practices for API key management (using environment variables), implementing mandatory key rotation procedures, scrubbing Personally Identifiable Information (PII), and ensuring secure logging practices, helping developers build production-ready, secure applications.

This guide details setting up and managing CoreWeave GPU cloud infrastructure across Development, Staging, and Production environments. It ensures strict resource separation using dedicated Kubernetes namespaces for GPU quotas and scaling policies. Use this when deploying complex ML/AI workloads requiring robust environment isolation and controlled promotion workflows.