Skill UI

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.

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.

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.

This comprehensive guide diagnoses and fixes common Clari API errors, including 401 Unauthorized, empty exports, job timeouts, and data mismatches. It provides step-by-step solutions for debugging data extraction and forecasting issues using API calls.

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.

This comprehensive guide presents three validated architectural blueprints for integrating Adobe services (Firefly, PDF, etc.). It helps developers decide between simple direct SDK integration (suitable for MVPs), native Adobe App Builder (serverless functions), or robust, high-throughput dedicated microservices, based on team size, complexity, and required scalability.

A comprehensive guide and implementation pattern for handling rate limits and quotas across various Adobe APIs (Firefly, PDF Services, Photoshop, etc.). This includes implementing exponential backoff, honoring `Retry-After` headers, and proactive quota tracking to ensure stable, high-throughput batch operations and reliable integration.

A utility designed for robust blockchain interactions using the Alchemy API. It implements CU-aware throttling based on Compute Unit costs, manages concurrent requests, and includes advanced retry logic for handling 429 Too Many Requests errors. Ideal for optimizing high-volume, reliable Web3 applications that must adhere to strict API rate limits and usage budgets.

A comprehensive guide to troubleshooting the most common Algolia API errors, including 400, 403, 404, and 429. This document details the root causes and provides step-by-step fixes for issues related to invalid API keys, rate limits, missing indexes, and data structure validation, ensuring reliable search functionality.

This integration automates the critical process of converting design assets from Figma into production-ready code using Anima. It establishes a full CI/CD pipeline via GitHub Actions, enabling scheduled or manual component generation. Use this when automating design system handoffs, maintaining code synchronization with design changes, or implementing robust, reliable development workflows.

A suite of utilities designed to significantly boost Anima code generation performance. It implements file-based caching with Time-To-Live (TTL) management, enables incremental updates by tracking only changed Figma components, and optimizes output size by cleaning up comments and excess whitespace. Ideal for optimizing large batch generations or speeding up production build pipelines.