Skill UI

This skill provides a comprehensive workflow to export images, icons, and assets directly from Figma files using the REST API. It enables users to render specific frames or components as high-quality PNG, SVG, JPG, or PDF files. Ideal for building automated asset pipelines, generating documentation previews, or batch exporting large icon libraries.

This comprehensive guide details the ten most common mistakes and anti-patterns encountered when integrating with the Figma REST and Plugin APIs. It covers critical topics such as preventing oversized data fetches, managing rate limits, securing tokens, handling color format conversions, and optimizing data sync using webhooks instead of polling. Essential for code reviews and onboarding. Use when reviewing Figma code, onboarding new developers, or auditing an existing Figma integration.

A comprehensive guide to optimizing performance when integrating with the Figma REST API. Techniques cover aggressive response caching (LRU), reducing payload size using depth parameters, batching multiple node fetches, and implementing webhook-driven cache invalidation. Essential for handling large, complex Figma files efficiently.

A collection of production-ready patterns for interacting with the Figma REST API and Plugin API. It provides type safety, robust error handling, and reusable abstractions for tasks like building client wrappers, extracting design tokens, and traversing complex node trees. Essential for building scalable, enterprise-grade Figma integrations.

This guide manages critical migrations for the Figma REST API, addressing scope deprecations (e.g., migrating 'files:read' to granular scopes) and upgrading from Webhooks V1 to V2. It is essential for developers updating existing integrations to ensure compatibility with the latest API standards and security features.

This comprehensive guide serves as a quick reference for diagnosing and fixing common Flexport API v2 errors. It covers standard HTTP status codes (e.g., 401, 403, 422, 429, 5xx), detailing the causes and providing actionable fixes, including cURL examples and validation best practices. Essential for developers integrating supply chain solutions with Flexport.

This skill provides instructions for deploying Flexport logistics integrations across various cloud platforms, including Vercel, Fly.io, and Google Cloud Run. It is essential for setting up reliable, always-on webhook receivers, shipment tracking dashboards, and background workers necessary for comprehensive supply chain automation services in a production environment.

A comprehensive guide to optimizing cloud spending on Fly.io. Learn advanced strategies for cost reduction, including implementing auto-stop/suspend features, correctly right-sizing Virtual Machines (VMs), managing and cleaning up orphaned volumes, and utilizing proper billing monitoring tools. Essential for efficient cloud resource management.

A comprehensive guide to installing the flyctl CLI and setting up secure authentication for Fly.io edge compute deployments. This guide covers both interactive login and API token methods (User, Deploy, Org, Machines), which are essential for CI/CD pipelines and advanced resource management via the Machines API.

Outlines a comprehensive, fast local development loop for applications hosted on Fly.io. It guides users through testing Docker containers locally, proxying remote services like Postgres and Redis to localhost, configuring dev environments, and performing fast deployment cycles. Essential for modern edge computing development.

This guide walks users through verifying the complete setup of their Fondo account. It covers essential financial checks, including synchronizing bank transactions, reviewing automated transaction categorization (payroll, software, office), and confirming eligibility and data needed for R&D tax credits. Use this when initially setting up or auditing your core financial data flow.

This skill creates and synchronizes prompt-based AI agents directly into Azure AI Foundry using the Agent Service REST API. By defining agents in a local JSON manifest, the skill registers them server-side, making them instantly available for evaluation and invocation within the Foundry ecosystem. It is essential for deploying, updating, or managing AI agents at scale within the Azure cloud environment.