Skill UI

Detects discrepancies between current infrastructure and desired configurations by running drift-detect, helping DevOps teams ensure Terraform-managed environments stay consistent and report configuration differences.

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.

Controls headful browsers via a CLI that runs sandboxed JavaScript, keeping page state persistent while navigating, form-filling, screenshots, scraping, or web testing flows.

This skill defines a senior engineer specializing in the entire software development lifecycle (SDLC). It covers building robust CI/CD pipelines (e.g., GitHub Actions), containerizing applications with Docker, and managing infrastructure using Infrastructure as Code (IaC) tools like Terraform or Pulumi. Key areas include Kubernetes deployment (GitOps), cloud platform configuration (AWS/GCP/Azure), release automation, and incident response planning.

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.

An expert AI assistant specializing in modern Django 5.x development. It provides best practices, architectural guidance, and actionable steps for building scalable, secure, and highly performant web applications. Expertise covers async views, DRF, Celery, Channels, and comprehensive CI/CD integration. Use this when building enterprise-grade Django systems.

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.

This skill analyzes existing codebases to create comprehensive, long-form technical documentation. It captures the architecture, design patterns, implementation details, and rationale (the 'why') behind complex systems. Ideal for creating definitive technical manuals, system overviews, and internal knowledge bases for onboarding and maintenance.

A comprehensive toolkit for diagnosing and troubleshooting Documenso integration issues. It includes connectivity tests (Bash), TypeScript diagnostics (API key, connection, write access), and debug logging wrappers.Use this to collect detailed diagnostic information necessary for resolving complex API problems and filing accurate support tickets.