Skill UI

A comprehensive, expert-level workflow for debugging complex software issues in production environments. This skill guides users through initial triage, advanced observability data collection (APM, distributed traces, logs), intelligent hypothesis generation, and full root cause analysis. Use it when dealing with intermittent failures, performance bottlenecks, or needing a complete fix and prevention plan.

Guides developers through reproducing issues, isolating failure cases, testing hypotheses, and verifying fixes with regression safeguards, while referencing tools, logs, stack traces, and git bisect workflows to expose stubborn root causes.

Creates step-by-step decomposition plans and migration roadmaps to guide the transition from monolithic applications to distributed architectures, prioritizing risk, value, and dependencies while tracking progress through pattern-based phases.

A comprehensive workflow for production-grade, pre-recorded Speech-to-Text (STT) transcription using the Deepgram API. This skill supports transcribing audio from URLs or local files, offering advanced features such as speaker diarization, automatic summaries, sentiment analysis, and topic detection. It also includes robust batch processing methods for handling large datasets.

Collects environment metadata, API connectivity tests, request/response logs, audio analysis, and reproduction scripts into a single archive for Deepgram support tickets and troubleshooting workflows.

Guides deploying Deepgram integrations into production-ready Docker, Kubernetes, serverless, and cloud environments with containerization, secret handling, autoscaling, and scripted rollout steps for reliable infrastructure releases.

Guides engineers through triage, severity classification, fallback activation, and post-incident review for Deepgram outages, with steps for API checks, retries, and communications during production failures.

Guides teams migrating transcription workloads from AWS, Google, Azure, Whisper, or similar providers to Deepgram with adapter interfaces, migration routers, validation scoring, and phased rollout plus rollback safeguards.

This skill provides a comprehensive and isolated setup for managing Deepgram API integrations across different deployment stages (Development, Staging, Production). It includes typed configuration management, a client factory pattern, and Docker Compose profiles, ensuring that each environment uses specific credentials, models, and feature settings (like diarization or PII redaction) without conflict. Ideal for robust, multi-stage application deployment.

Sets up metrics, tracing, logging, dashboards, and alerts for Deepgram integrations, enabling teams to monitor request throughput, latency, costs, and service health for production deployments.

This guide provides advanced techniques to optimize Deepgram API performance. Learn how to preprocess audio using ffmpeg (resampling, noise reduction), select optimal transcription models (speed vs. accuracy), and implement efficient streaming or parallel batch processing to achieve high throughput and low latency.

Guided checklist ensures Deepgram integrations are production-ready by verifying API keys, error handling, performance tuning, health endpoints, monitoring metrics, and alert rules for go-live stability.