Skill UI

This skill provides comprehensive guidance on implementing HIPAA-compliant security measures for Abridge clinical AI integrations. It covers critical areas such as enforcing TLS 1.3 encryption in transit, AES-256 encryption at rest, implementing role-based access controls (RBAC), detailed PHI-safe audit logging, and best practices for secrets management, ensuring full compliance with HIPAA regulations.

Implements robust rate limiting, backoff logic, and quota management for the Anthropic Claude API. It handles 429 errors and optimizes request throughput by managing Requests Per Minute (RPM), Input Tokens Per Minute (ITPM), and Output Tokens Per Minute (OTPM). This skill provides advanced strategies including SDK retries, custom header awareness, queue-based throttling, and batch processing for stable, high-throughput production applications.

A comprehensive guide for building applications with Claude, ensuring responsible data handling. This skill covers critical patterns such as PII redaction (stripping sensitive data like emails, phone numbers, and card numbers), optimizing the 200K token context window through conversation trimming, and implementing best practices for data retention and privacy compliance when interacting with the Anthropic API.

This skill provides comprehensive guides for deploying stateless, serverless API wrappers powered by Claude (Anthropic). It details how to integrate and stream responses from the Messages API across major cloud environments, including Vercel Edge Functions, Fly.io, and Google Cloud Run. It is essential for productionizing AI applications that require robust secret management, scalable infrastructure, and real-time streaming capabilities.

This skill provides comprehensive deployment guides for Cohere API v2 applications across major cloud platforms including Vercel, Fly.io, and Google Cloud Run. It covers critical aspects like secret management, setting up reliable health checks, optimizing performance, and implementing streaming chat endpoints to ensure production readiness.

This skill guides the secure handling and lifecycle management of large-scale data artifacts, including training datasets, model weights, and checkpoint snapshots, within GPU cloud environments. It provides best practices for data pipelines, covering secure import via Kubernetes PVCs, compliant export, and stringent data validation, ensuring adherence to encryption standards (AES-256) and regulatory requirements (PII masking, RBAC).

This skill provides advanced techniques for robust prompt engineering within LangChain applications. It solves common production issues, such as f-string template breakage when user input contains literal curly braces, and guides developers on consolidating scattered prompts. Crucially, it details how to use the LangSmith Prompt Hub to version, pin, and A/B test prompts using immutable commit hashes, ensuring stable, reproducible LLM deployments.

This skill provides a production-grade, containerized integration service for connecting to the Together AI platform. It facilitates high-performance inference, fine-tuning, and model deployment across over 100 open-source models using Together's OpenAI-compatible API. Includes comprehensive Docker setup, environment variable management, health checks, and zero-downtime rolling update strategies for robust, real-time LLM serving.