Skill UI

This skill provides a comprehensive guide for deploying LangChain chains and agents into production-grade APIs. It supports multiple development stacks, including Python (LangServe/FastAPI) and Node.js (Express). Topics covered include containerization using Docker, setting up robust health checks, and deploying to major cloud platforms like Google Cloud Run and AWS Lambda. Learn how to build scalable, observable, and enterprise-grade API endpoints for advanced LLM applications.

This comprehensive guide provides step-by-step instructions for integrating Langfuse LLM observability into various cloud and serverless environments. It covers best practices for deployment on platforms such as Vercel, AWS Lambda, Google Cloud Run, and self-hosted Docker, ensuring robust tracing and monitoring of entire AI workflows.

Diagnoses and fixes Prisma connection pool exhaustion in serverless deployments (Vercel, Lambda, Netlify) by routing through pooling services, limiting client connections, and tuning timeouts to stop P2024/too many connection errors under load.

A comprehensive guide to configuring Sentry error tracking and performance monitoring across modern application architectures. Learn how to implement coherent, end-to-end distributed tracing for monoliths, microservices, serverless functions (Lambda/Cloud Functions), event-driven systems, SPAs, and mobile applications, ensuring all application hops are monitored from a single source.

Comprehensive guide and expert assistance for building, refactoring, and validating AWS cloud infrastructure using the AWS Cloud Development Kit (CDK). Covers best practices for TypeScript and Python, including resource naming conventions, Lambda function development, and multi-layer pre-deployment validation using tools like cdk-nag.

A comprehensive guide for designing and building scalable, resilient serverless applications and event-driven architectures on AWS. It covers best practices using Lambda, API Gateway, DynamoDB, Step Functions, and adheres to the AWS Well-Architected Framework principles, ensuring optimal performance, cost-efficiency, and maintainability.

Build automated pipelines to respond to AWS GuardDuty findings. This solution uses EventBridge to detect high-severity threats and triggers a Lambda function. The function automatically quarantines compromised resources (e.g., EC2 instances), creates forensic EBS snapshots, and sends detailed notifications via SNS, drastically reducing Mean Time To Respond (MTTR). Ideal for proactive cloud security posture management.

A comprehensive guide to securing serverless compute platforms (AWS Lambda, Azure Functions, Google Cloud Functions). It covers critical security aspects including enforcing least-privilege IAM roles, integrating secrets management, vulnerability scanning of dependencies, input validation, and implementing runtime monitoring for robust DevSecOps practices.

Provides step-by-step techniques for assessing AWS security, covering IAM enumeration, privilege escalation, SSRF metadata attacks, S3/Lambda exploitation, and red-team persistence workflows with recommended tools and commands.

This skill provides blueprints for deploying Clari data export pipelines into robust, production-grade cloud environments. It guides users on setting up reliable, scheduled, and serverless data syncs using major platforms like Airflow DAGs, AWS Lambda, and Google Cloud Functions. Ideal for automating revenue forecasting and business intelligence data extraction.

A comprehensive index of 46 production-grade test automation skills, covering E2E, unit, mobile, BDD, and cloud testing across 15+ languages. This skill equips AI coding assistants to act as senior QA architects, generating structured, real-world test code for major frameworks like Playwright, Selenium, Cypress, and Jest. It supports project setup, CI/CD integration, and cross-platform debugging.

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.