Skill UI

This expert skill converts static or modern frameworks (React, Next.js, HTML) into fully dynamic, pixel-perfect, and SEO-optimized WordPress themes. It functions as a senior architect, ensuring absolute fidelity to the source while integrating core WordPress functionalities like ACF, custom hooks, and technical SEO best practices. Ideal for large-scale website migrations.

This skill outlines how to implement and manage Role-Based Access Control (RBAC) and namespace isolation for multi-team GPU workloads running on CoreWeave's Kubernetes platform. It provides guidance on setting strict resource quotas, preventing noisy-neighbor issues, and defining granular roles (e.g., ML Engineer, Inference Operator). This is essential for maintaining resource isolation, ensuring compliance (SOC 2, HIPAA), and managing access across large-scale cloud deployments.

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.

This guide provides a comprehensive walk-through of making the first REST API calls to Figma. Users learn how to fetch core file metadata (name, version, pages) and traverse the complex document structure (nodes, frames, components). It's ideal for developers starting a new Figma integration, setting up API connectivity tests, or understanding the fundamental relationships between design elements within a Figma file.

A comprehensive guide to optimizing the Finta fundraise workflow. This document addresses critical performance bottlenecks, including pagination issues with large investor datasets, latency in multi-stage round data aggregation, and slow CRM synchronization. Optimization strategies cover cursor-based fetching, strategic caching (TTL management), connection pooling, and robust rate limit handling, aiming to reduce pipeline load times by 50-70% and maintain dashboard responsiveness.

This comprehensive guide assists developers in maintaining and upgrading integrations with the Finta fundraising CRM API. It covers critical areas such as API version detection, handling schema evolution (e.g., structured stage objects), best practices for data migration, and troubleshooting common breaking changes (like field renames, permission changes, or enum changes) to ensure continuous and reliable data synchronization.

This skill guides users through setting up robust, production-grade infrastructure on Fly.io. It covers creating and connecting to Fly Postgres clusters for reliable data storage, provisioning persistent NVMe Volumes for durable file storage, and configuring private internal networking (6PN) for secure service-to-service communication. It is essential for modern microservices requiring stable databases and persistent state.

This tool provides comprehensive observability for enterprise search systems (Glean). It tracks critical metrics such as search latency (p95), zero-result query rates, indexing throughput, and stale content ratios. By monitoring connector sync status and detecting indexing degradation, it allows teams to proactively maintain search relevance and ensure sub-second response times, preventing silent data quality decay.

This document outlines the reference architecture for integrating diverse enterprise knowledge sources (such as Confluence, Jira, Notion, and Slack) into the Glean search index. It details the end-to-end data flow, covering connector frameworks, message queuing, permission synchronization (ACLs), and client-side search APIs. Designed to ensure continuous, reliable, and low-latency unified search across all corporate data.

This skill demonstrates how to build a robust, event-driven indexing system for Glean. It processes real-time webhooks received from various source systems (like GitHub, Notion, Confluence), handling events such as document indexing, permission changes, and search anomalies. The solution includes critical components like signature verification and idempotent message handling to ensure data consistency and reliability.

This guide provides techniques to optimize Grammarly API interactions, focusing on reducing latency and improving throughput. Learn how to implement efficient caching strategies (like LRU cache) for repeated score checks and how to execute multiple API calls in parallel using Promise.all. Use this when experiencing slow response times or needing cost/performance improvements in Grammarly integrations.

A comprehensive guide and implementation pattern for handling rate limits, backoff, and idempotency when integrating with the Grammarly Text API. It provides a custom rate limiter and robust retry logic to manage API throughput, ensuring reliable processing of high volumes of documents and stable interaction with various endpoints (e.g., writing score, plagiarism checks).