Skill UI

This guide details how to integrate Vast.ai's GPU provisioning capabilities into automated CI/CD pipelines, such as GitHub Actions. It enables developers to run GPU-accelerated tests, model benchmarks, and validations automatically. Key features include robust instance lifecycle management (provisioning, running, and cleanup) and advanced cost-control mechanisms (e.g., setting budget limits) to ensure reliable and efficient testing in a cloud environment.

A collection of production-ready Python patterns for interacting with the Vast.ai cloud API. This includes typed search query builders, context-managed instance lifecycle (guaranteeing auto-cleanup), offer scoring algorithms (cost, reliability, performance), robust retry mechanisms with backoff, and secure SSH command execution. Essential for building reliable, complex cloud workflow applications.

This comprehensive guide outlines security best practices for utilizing Vast.ai's cloud environment. It covers secure API key management, hardening SSH access to GPU instances, implementing proper data cleanup before instance destruction, and adhering to robust network security protocols. Use this when setting up, auditing, or deploying sensitive AI/ML workloads on shared cloud hardware.

Automates spoken-word video editing by transcribing footage, detecting mispronunciations or pauses with AI, generating review pages, and surfacing actionable deletion lists for user approval before trimming.

An expert agent focused on enhancing code clarity, consistency, and maintainability. It simplifies complex code structures, eliminates redundant logic, and applies project-specific best practices, all while guaranteeing that the original functionality and behavior remain absolutely unchanged. Ideal for code reviews, cleanup tasks, or improving readability.

A specialized tool for auditing source code (C/C++/Rust) to ensure sensitive data (keys, passwords, PII) is properly zeroized. It analyzes memory handling at the assembly and IR level to detect if compiler optimizations, such as dead-store elimination, have accidentally removed or weakened the secure cleanup process. Essential for maintaining security in critical codebases.

This skill enforces best practices for managing Go modules, focusing on stability, security, and maintainability. It guides users through essential workflows like dependency addition, safe upgrading (e.g., patch updates), cleanup (go mod tidy), and critical vulnerability scanning (govulncheck). Use this when initializing, updating, or auditing a Go project's dependency tree to ensure supply chain safety.

A comprehensive guide for deploying, configuring, and maintaining the OpenViking server in production environments. It covers service configuration management, environment setup using `uv` for virtual environments, reliable startup procedures using `nohup`, graceful shutdown methods, and critical data cleanup workflows. This resource is essential for DevOps engineers and system administrators managing OpenViking services.

Converts text-based documentation into structured Markdown by following explicit instructions, documented options, or reference files, supporting header levels, patterns, platforms, and cleanup steps for polished technical documents.

Guides React 19 test migrations by outlining act import changes, Simulate-to-fireEvent replacements, full react-dom/test-utils cleanup, and StrictMode call-count verification strategies.

This skill generates a detailed, multi-phase plan for complex, multi-file refactoring projects. It ensures safety by first analyzing the codebase, identifying dependencies, and structuring changes in a safe sequence (e.g., Types first, then implementations, followed by tests and cleanup). It forces the AI to output a comprehensive plan, including rollback steps and verification points, and waits for user confirmation before making any actual code changes.

This skill guides developers through the structured completion of a feature branch. It enforces running comprehensive tests, detects the current Git environment (e.g., common repository vs. worktree), and presents clear options (merge, PR, retain, discard). It ensures safe integration, manages worktree cleanup, and enforces best practices for version control workflows.