Skill UI

A comprehensive guide for diagnosing and fixing common Deepgram API errors. Covers HTTP error codes, WebSocket issues, optimal audio preparation using ffmpeg, and implementing robust retry patterns for reliable Speech-to-Text integration.

Implements best practices for secure audio transcription using Deepgram. This guide covers PII redaction (built-in and custom patterns), secure audio upload to S3 with encryption, managing data retention policies, and ensuring compliance with major regulations like GDPR and HIPAA. It provides a comprehensive pipeline for handling sensitive audio data in enterprise applications.

This guide provides minimal working examples for Deepgram speech-to-text transcription. It demonstrates how to transcribe audio from a URL or a local file using both TypeScript and Python. Users can learn basic API patterns, implement advanced features like diarization (speaker identification), and compare various model options (e.g., nova-3, nova-2). Ideal for initial integration and testing.

This utility provides comprehensive patterns for reliably integrating with the Deepgram API. It implements concurrency-aware rate limiting (using p-limit), exponential backoff with jitter for retries, and a circuit breaker pattern. Use this when building high-volume, mission-critical applications that must handle API quotas, 429 rate limit errors, and temporary service disruptions gracefully.

Provides reference architectures for building high-scale, reliable transcription systems using Deepgram. It covers four main patterns: synchronous REST for short files, async queues (BullMQ) for batch processing, WebSocket for real-time streaming, and a hybrid router for mixed workloads. Use this when designing production-grade audio processing pipelines.

Provides production-ready coding patterns for integrating Deepgram using TypeScript and Python. This guide covers essential best practices, including implementing singleton client management, performing text-to-speech synthesis with Aura, and setting up advanced audio intelligence pipelines (e.g., summarization, topic detection, sentiment analysis). Use this when establishing robust Deepgram integration standards, refactoring existing SDK usage, or migrating to newer SDK versions.

Definition Of Done Generator auto-activates within Enterprise Workflows, guiding requests toward project management, compliance, and governance patterns while producing production-ready code, configurations, and validated outputs.

Automates dependency vulnerability checks within the Security Fundamentals skill set, guiding users through best practices, secure coding patterns, and remediation-ready output validation.

A comprehensive guide to deployment patterns and strategies for modern cloud environments. Covers techniques like Blue/Green, Canary, and Rolling Deployments, ensuring zero-downtime upgrades when deploying to Kubernetes, Docker, or various cloud providers. Includes best practices for health checks, logging, and rollback planning.

This guide outlines advanced architectural patterns for building multi-stage CI/CD pipelines. It covers best practices for implementing robust deployment gates, including manual approvals, time-based triggers, and multi-approver workflows. It details various deployment strategies like Rolling, Blue-Green, and Canary releases, ensuring controlled, zero-downtime, and highly reliable software releases.

Automates the creation of deprecation notices for technical documentation, guiding users through patterns, best practices, and validation steps when writing API docs, user guides, or architecture notes.

Automates guidance when requesting design doc templates, covering patterns, best practices, and example triggers across API, user, and architecture docs to streamline technical documentation.