Skill UI

Guides tuning Databricks clusters, Spark settings, and Delta Lake tables so teams can speed slow jobs, balance workloads, and improve query responsiveness through sizing, config, and storage optimizations.

This skill guides users in transforming chaotic debugging efforts into a structured, systematic process. It provides a methodology for tracking down elusive bugs, investigating complex performance degradation, and resolving critical production incidents. Users learn to capture necessary logs, formulate testable hypotheses, narrow the scope using techniques like binary search, and methodically verify fixes in distributed systems environments.

Guides teams through audio preprocessing, connection pooling, model selection, streaming workflows, concurrency controls, and caching to accelerate Deepgram transcription and cut latency across large-scale pipelines.

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.

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.

Coordinates a repeatable pre-PR or pre-release workflow for Django apps, covering environment validation, linting, formatting, migrations, tests with coverage, security scans, performance validation, and static asset readiness to ensure deployment confidence.

Speed up Documenso integrations by combining caching, batching, queueing, pagination, and monitoring to slash response times, reduce API calls, and keep bulk document workflows reliable in production.

Expert .NET backend architect guidance for C#, ASP.NET Core, Entity Framework, Dapper, caching, testing, and DevOps so teams can build production-grade APIs, microservices, and enterprise applications with clear patterns and performance best practices.

Provides expert .NET/C# backend work for ASP.NET Core 8+ APIs, covering EF Core data access, authentication/authorization, background services, performance tuning, and production-ready patterns for enterprise services.

Guides writing idiomatic Elixir code with OTP patterns, supervision trees, Phoenix LiveView, Ecto, concurrency, distributed systems, and BEAM performance tuning while insisting on best practices, actionable checks, and validation steps for resilient services.