Skill UI

Automates user journey mapper tasks in the Visual Content domain by triggering whenever you mention user journey mapper needs, then guiding each step, applying best practices, and generating validated diagrams, charts, and documentation-ready material.

This expert skill validates the deployment readiness of Vertex AI Agent Engines. It executes a weighted audit across five critical dimensions: security, monitoring, performance, compliance, and best practices. The output provides a comprehensive 0-100% composite score, a detailed pass/fail report for each check, and a prioritized, actionable remediation plan, ensuring high-quality, production-grade deployments.

This advanced workflow orchestrates complex, multi-node GPU clusters on Vast.ai. It is designed for large-scale distributed machine learning training, automatically handling spot instance preemption and resuming jobs from checkpoints. Furthermore, it provides comprehensive cost analysis by tracking billing history, allowing users to optimize GPU spending and manage cluster teardown efficiently.

A comprehensive guide for deploying Machine Learning training jobs and inference services on the Vast.ai GPU cloud. This skill covers the entire deployment lifecycle, including optimizing Docker images for performance, creating automated provisioning scripts using the Vast.ai CLI, implementing robust data transfer strategies (SCP, rsync), and performing post-deployment health checks.

This guide details how to implement environment isolation (dev, staging, prod) for GPU cloud deployments on Vast.ai. It uses environment variables and configuration classes to enforce separate API keys, budget caps, instance limits, and GPU whitelists for each deployment tier, ensuring efficient resource management and cost control.

A comprehensive guide to optimizing cloud expenditure on the Vercel platform. It details how to understand the Fluid Compute pricing model, identify key cost drivers (such as function execution time, bandwidth, and middleware invocations), and implement best practices like edge caching, memory right-sizing, and aggressive asset caching. Use this when analyzing high Vercel billing, implementing cost controls, or managing a SaaS budget.

A comprehensive guide to optimizing Vercel deployment performance. This skill covers advanced techniques such as edge caching implementation (using Cache-Control headers), leveraging Incremental Static Regeneration (ISR), minimizing serverless function cold starts, and optimizing bundle size. Use this when facing slow page load times, needing to improve Core Web Vitals, or requiring robust, scalable deployment performance.

Vercel Engineering’s authoritative React and Next.js performance guide, offering prioritized rules for waterfalls, bundle size, data fetching, memoization, rendering, caching, and advanced patterns.

A comprehensive guide to implementing fault-tolerant patterns for Vercel serverless functions. Learn how to build resilient APIs using Circuit Breakers to handle external dependency failures, implementing Exponential Backoff for retries, and achieving Graceful Degradation by serving stale cache data. Essential for production-grade, highly available serverless architecture.

Orchestrate Wachete tasks via Composio’s Rube MCP workflow, covering tool discovery, connection checks, and schema-compliant execution with RUBE_MULTI_EXECUTE_TOOL while reusing sessions and honoring pagination.

A comprehensive guide for developers to measure, analyze, and optimize website and web application performance. Covers critical areas including Core Web Vitals (LCP, FID, CLS), reducing JavaScript bundle size, implementing effective caching, and optimizing rendering paths to boost user experience and SEO rankings.

Automates websocket handler setup for backend development, guiding Node.js, Python, and Go implementations while aligning with database, caching, messaging, and microservice architecture best practices to deliver production-ready code and validations.