Skill UI

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.

A comprehensive guide detailing security best practices for Deepgram API integration. It covers critical topics such as implementing scoped API keys, key rotation strategies, enabling built-in PII redaction for sensitive data, generating temporary client-side keys, and validating audio URLs to prevent SSRF attacks. Use this when building robust, production-grade applications requiring high data security and compliance.

A powerful tool for comprehensive, offline dependency auditing across 8+ programming ecosystems (e.g., Node, Python, Go, Rust). It identifies critical CVE vulnerabilities, license conflicts, and calculates safe upgrade paths, making it essential for pre-release security checks, legal compliance reviews, and major version migrations.

A comprehensive expert for configuration management, specializing in validating, testing, and ensuring the correctness of application settings. It creates robust validation schemas (e.g., JSON Schema) and performs critical checks, including identifying potential security secrets (API keys, passwords), ensuring data consistency across different environments (development, staging, production), and enforcing type safety for reliable deployments.

Detects memory usage issues by scanning code for common leak patterns, such as lingering listeners, closures holding references, or runaway caches, and provides recommendations to fix them before performance degrades.

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.

Automatically analyzes CI/CD performance metrics, compares them against baselines and thresholds, and flags statistical regressions so teams catch response-time or throughput degradations before deployment.

Personalized reports that analyze recent Claude Code chats to surface recurring challenges, highlight learning gaps, curate HackerNews resources, and deliver actionable development insights directly to your Slack DMs for targeted growth.

Provides practical advice on Dockerfiles, CI/CD pipelines, deployment strategies, infrastructure-as-code, and observability, helping teams containerize apps, configure GitHub Actions, plan production rollouts, and keep deployments secure and observable.

A comprehensive guide for advanced DevOps troubleshooting. It covers modern observability practices (ELK, Prometheus, Jaeger), deep debugging for Kubernetes and containers, complex network analysis, CI/CD pipeline failure resolution, and multi-cloud platform issues. Ideal for performing root cause analysis and building highly resilient systems.

Performs security-focused differential review of PRs, commits, and diffs, adapting depth to repo size, tracing git history, estimating blast radius, checking coverage, and producing detailed markdown reports to stop regressions.

This skill provides comprehensive guidance on implementing distributed tracing using industry standards like OpenTelemetry and tools such as Jaeger/Tempo. It enables developers to monitor the end-to-end lifecycle of a request across multiple microservices. Use this skill to debug latency issues, visualize complex service dependencies, pinpoint performance bottlenecks, and accurately trace error propagation in highly distributed systems.