Skill UI

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.

This guide demonstrates how to implement robust, real-time, low-latency streaming transcription using Deepgram's WebSocket API. It covers advanced audio handling, including microphone input capture (via Sox), speaker diarization, utterance boundary detection, and implementing automatic reconnection logic. Essential for building professional voice AI applications, live captioning services, or voice interfaces.

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.

Enables Claude to apply anomaly-detection-system workflows for spotting outliers, fraud, or unusual patterns across datasets, selecting tailored algorithms like Isolation Forest and summarizing deviations for any data monitoring or security use case.

Detect, analyze, and resolve production database deadlocks via the database-deadlock-detector plugin, which runs `/deadlock` to monitor lock contention, report transaction patterns, and suggest fixes for recurring issues.

Analyzes CPU, memory, I/O, and database traces to find and fix bottlenecks, offering remediation strategies when diagnosing slow applications, optimizing resource use, or preventing performance issues.

Detect SQL injection weaknesses by running the sql-injection-detector plugin against codebases, identifying risky queries, and providing remediation guidance to secure applications.

This skill is designed for advanced error detective work. It analyzes complex log streams, correlates stack traces across distributed systems, and detects anomalous error patterns. It helps identify root causes by correlating errors with system deployments and changes, providing actionable findings for immediate fixes and long-term prevention strategies.

Build robust, event-driven integrations with Exa using scheduled monitoring and content alerts. This skill allows users to establish competitive intelligence pipelines, track content changes over time, and automate research digests. It supports new article detection, similarity monitoring, and reliable webhook delivery via background queues.

Auto-activated guidance for flaky test detection within automated testing workflows, covering best practices, mocking, and configuration to stabilize unit and integration suites.

Comprehensive Go guidance for browser automation and web scraping using Rod’s direct Chrome DevTools Protocol integration plus stealth anti-detection patterns, ideal for headless SPA testing, concurrent scraping, and request interception.

This skill simulates a senior Go developer, specializing in writing high-performance, production-grade Go applications. It covers advanced topics like concurrent programming using goroutines and channels, designing robust microservices with gRPC/REST, and optimizing code using pprof and benchmarks. It enforces idiomatic Go patterns, context propagation, and strict testing practices (table-driven, fuzzing, race detection).