Skill UI

This skill deploys a containerized integration service to programmatically manage and manipulate Lucidchart diagram documents. It handles sophisticated tasks like manipulating shapes, updating connectors, and synchronizing visual collaboration data using the Lucid API. Ideal for integrating automated diagram generation and maintenance into CI/CD pipelines and enterprise workflows.

This document provides a comprehensive guide to managing rate limits when interacting with the Lucidchart API. It details specific limits for various operations (e.g., shape creation, document listing, exporting) and offers implementation patterns, including a token bucket rate limiter class and robust retry strategies. Use this knowledge to build automated workflows that reliably handle high-volume batch processing and prevent API throttling.

A comprehensive technical guide for developers managing integrations with Lucidchart. It details strategies for handling API version changes, including version detection, schema migration (e.g., flat shapes to page-grouped hierarchies), rollback mechanisms, and common error troubleshooting (e.g., permission model updates, coordinate system shifts). Essential for maintaining compatibility when using Lucidchart's evolving diagramming platform.

This skill provides comprehensive knowledge on setting up and handling real-time webhook events from Lucidchart. It details how to receive notifications—such as document creation, updates, sharing, and shape additions—via signed JSON payloads over HTTPS. Users can implement robust integrations for compliance auditing, triggering CI/CD pipelines, or notifying external collaboration tools like Slack.

A comprehensive debugging tool designed for diagnosing complex and intermittent issues within the Canva Connect API. It systematically tests various connection layers (DNS, TLS, Authentication, Scopes), monitors stuck or failed export jobs by polling job status, and verifies the OAuth token lifecycle. Use this when standard troubleshooting fails or when preparing detailed evidence for developer support.

A comprehensive developer resource for diagnosing and resolving common Canva Connect API errors and HTTP status codes. It details issues such as expired tokens (401), insufficient permissions (403), rate limiting (429), and validation failures (400), providing specific causes, error payloads, and code-level fixes for seamless integration development.

This workflow provides an end-to-end programmatic solution for managing the Canva design lifecycle. It allows users to create new designs via the API, redirect users to the editor for modifications, retrieve design metadata, and finally, export finished assets in various high-quality formats (PDF, PNG, JPG, etc.). Ideal for integrating design capabilities into external applications like CMS or marketing automation tools.

A collection of production-ready patterns for wrapping the Canva Connect REST API, supporting both TypeScript and Python implementations. These patterns ensure robust API integration by handling automatic OAuth token refresh, implementing retry logic with exponential backoff, ensuring type safety, and supporting multi-tenant architectures. Use this when building resilient, reusable API wrappers for Canva services.

A comprehensive diagnostic guide for common issues encountered with CAST AI agents, Kubernetes autoscaling, API connectivity, and resource provisioning. Covers scenarios like agent crashes, 401 errors, and scaling failures, providing specific commands (kubectl, curl, helm) and detailed fixes for robust troubleshooting.

This skill guides the setup and configuration of the CAST AI Workload Autoscaler, enabling dynamic right-sizing of pod resource requests (CPU and Memory). It automatically adjusts resources based on actual usage, significantly reducing cloud over-provisioning costs. Use this guide to implement workload scaling policies, configure resource limits via Kubernetes annotations, and monitor scaling events in Kubernetes environments.

This guide sets up a robust local development loop for integrated Kubernetes infrastructure using CAST AI. It allows developers to test autoscaler policies, validate Terraform modules, and measure potential cloud cost savings in a dev environment before deploying to production. This is essential for building cost-aware and efficient CI/CD pipelines.

A set of production-ready wrappers and patterns for interacting with the CAST AI REST API. This package provides robust client implementations in TypeScript and Python, handling critical features such as typed responses, singleton management, automatic retry logic with backoff, and managing cloud resources (e.g., Kubernetes clusters, node optimization). Use it when building reusable, reliable clients for cost optimization and infrastructure management.