Skill UI

This guide provides comprehensive instructions for deploying AssemblyAI-powered transcription services to major cloud platforms like Vercel, Google Cloud Run, and Fly.io. It covers essential steps including secure secret management, setting up webhook endpoints for asynchronous notifications, and implementing streaming token endpoints for real-time client use in production environments.

Implement robust handling for AssemblyAI's asynchronous transcription completion events via webhooks. This guides users on how to set up secure endpoints that receive POST requests upon job completion or failure. It covers submitting transcripts with webhook URLs, verifying authentication headers, and processing the final transcript data, including running subsequent analyses like summarization.

A comprehensive toolkit for debugging complex Adobe API issues that resist standard troubleshooting. Covers advanced techniques such as IMS token introspection, Firefly async job failure analysis, mapping PDF Services error codes, and deep network-layer diagnostics (DNS, TLS). Essential for resolving difficult, production-level integration bugs.

This guide implements production-grade reliability patterns for integrating with external APIs, specifically Adobe services. It demonstrates how to use circuit breakers to prevent cascading failures, implement graceful degradation with cached fallbacks, and utilize dead letter queues (DLQ) for reliable asynchronous job handling. It ensures your application maintains high availability even when external services are unstable or rate-limited.

A comprehensive guide to production-ready patterns for integrating with Adobe services (Firefly, PDF, etc.). This includes robust authentication with token caching, typed API wrappers with advanced error classification, exponential backoff retry mechanisms, and job polling for asynchronous tasks. Essential for building reliable and maintainable Adobe API integrations in TypeScript or Python.

A comprehensive guide to using the Apify Client SDK. Learn the fundamental pattern of executing remote web scraping Actors (like content crawling or general scraping), managing asynchronous run states, and retrieving structured data from resulting datasets and key-value stores. Essential for integrating powerful web scraping capabilities into applications.

Execute comprehensive, asynchronous transcription workflows using AssemblyAI. This tool handles file upload, queues jobs, and provides advanced audio intelligence features. Capabilities include speaker diarization, sentiment analysis, named entity recognition (NER), topic categorization (IAB), content safety moderation, and sensitive PII redaction. Ideal for processing meeting recordings, interviews, and large volumes of spoken content.

A comprehensive guide for developers on upgrading the assemblyai npm package and migrating between major SDK versions (e.g., v3 to v4). This resource details handling breaking changes, updating API calls, and transitioning between different transcription methods, including synchronous, asynchronous, and streaming setups, ensuring smooth integration with the latest features and models.

This skill provides comprehensive access to Bright Data's SERP API and Web Scraper API. It allows users to collect structured search engine results (Google, Bing, Yahoo) synchronously, or trigger large-scale, asynchronous data collections with webhooks. Ideal for market research, SEO analysis, and large-scale data scraping projects.

This skill provides advanced strategies for optimizing Canva Connect API performance. It covers implementing robust caching mechanisms (in-memory and Redis) to reduce redundant calls, handling pagination using continuation tokens, and implementing smart polling with progressive backoff for asynchronous operations like exports. It also details connection pooling and concurrency management to maximize request throughput and minimize latency for stable Canva integrations.

Utilize Anthropic Message Batches API for high-volume, asynchronous bulk processing of AI tasks. This method allows processing up to 10,000 requests per batch, ideal for summarizing large document sets or running repetitive tasks where immediate, synchronous results are not required. The process involves creating the batch, polling for status completion (within 24 hours SLA), and then retrieving detailed results, including success and error statuses for each item.

This comprehensive guide provides advanced strategies for optimizing throughput and reducing latency when interacting with the ClickUp API v2. Key techniques covered include implementing cache hierarchies, efficient asynchronous pagination, connection pooling, and rate limit adherence. Essential for building scalable and reliable automated integrations.