Skill UI

This skill teaches the critical principles and decision-making processes for safe production releases. It covers platform selection (e.g., Kubernetes, Vercel), mandatory pre-deployment verification (Code Quality, Environment), structured workflows (Prepare, Backup, Deploy, Verify), and advanced strategies like Blue-Green and Canary deployments. Focuses on thinking through risk mitigation, not just executing scripts.

This meta-skill coordinates the entire design lifecycle, ensuring that ideas are systematically refined through mandatory stages: brainstorming, risk assessment, and multi-agent review. It acts as a process gatekeeper, enforcing adherence to structured steps and mitigating risks before allowing implementation, thus preventing premature or flawed execution.

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.

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.

A comprehensive guide detailing essential security best practices for integrating with Documenso document signing. Covers critical topics such as secure API key management (using environment variables), robust webhook secret verification (preventing timing attacks), implementing least privilege document access control, and setting up secure self-hosted signing certificates and secrets.

This guide provides comprehensive templates and best practices for structuring all types of technical documentation. It covers essential formats including README files, REST API endpoints, code comments (JSDoc), Changelogs, Architecture Decision Records (ADR), and AI-optimized documentation. Use these templates to ensure your project documentation is standardized, scannable, and easily consumable by both human developers and AI agents.

Use the Rube MCP Composio DocuSign toolkit to orchestrate templates, create and send envelopes, monitor signing status, and append documents, making it easy to automate routine e-signature workflows.

Generates tailored domain ideas and availability checks across .com, .io, .dev, .ai, and more, helping founders, makers, and agencies secure a memorable brand quickly.

Provides comprehensive, step-by-step guides for developers to set up complete development environments from scratch. It covers installing dependencies (Node.js, Python, Docker), configuring environment variables, and using platform-specific commands for macOS, Linux, and Windows. Ideal for starting new projects, onboarding team members, or troubleshooting setup issues.

This skill provides expert-level diagnostic capabilities for complex distributed systems. It specializes in analyzing production incidents, identifying deep root causes, and designing comprehensive observability solutions. Use this when investigating recurring errors, reviewing system logs/traces, and implementing preventative reliability measures.

A comprehensive, AI-assisted methodology for diagnosing complex software errors in production environments. This skill guides users through the entire debugging lifecycle, from initial triage and gathering observability data (Sentry, DataDog, Jaeger) to generating hypotheses, selecting appropriate debugging strategies (Time-Travel, Chaos Engineering), and performing AI-powered root cause analysis. It culminates in proposing validated fixes and prevention measures.

A comprehensive toolkit for evaluating the performance of code generation models. It supports benchmarking against industry standards like HumanEval, MBPP, and MultiPL-E across multiple languages. Use this tool to quantitatively compare different LLM coding abilities and measure code synthesis quality using pass@k metrics.