turborepo
Turborepo Skill
Turborepo is a high-performance build system optimized for JavaScript and TypeScript monorepos, written in Rust. It provides intelligent caching, task orchestration, and remote execution capabilities to dramatically speed up development workflows.
Reference
https://turborepo.com/llms.txt
When to Use This Skill
Use this skill when:
- Setting up a new monorepo with multiple packages
- Optimizing build performance in existing monorepos
- Implementing task pipelines across packages
- Configuring intelligent caching strategies
- Setting up remote caching for teams
- Orchestrating tasks with dependency awareness
- Integrating monorepo with CI/CD pipelines
- Migrating from Lerna, Nx, or other monorepo tools
More from aia-11-hn-mib/mib-mockinterviewaibot
gemini-video-understanding
Analyze videos using Google's Gemini API - describe content, answer questions, transcribe audio with visual descriptions, reference timestamps, clip videos, and process YouTube URLs. Supports 9 video formats, multiple models (Gemini 2.5/2.0), and context windows up to 2M tokens (6 hours of video).
25imagemagick
Guide for using ImageMagick command-line tools to perform advanced image processing tasks including format conversion, resizing, cropping, effects, transformations, and batch operations. Use when manipulating images programmatically via shell commands.
14remix-icon
Guide for implementing RemixIcon - an open-source neutral-style icon library with 3,100+ icons in outlined and filled styles. Use when adding icons to applications, building UI components, or designing interfaces. Supports webfonts, SVG, React, Vue, and direct integration.
8obsidian-qa-saver
Save Q&A conversations to Obsidian notes with proper formatting, metadata, and organization. Use this skill when the user explicitly requests to save a conversation, question-answer exchange, or explanation to their Obsidian vault. Automatically formats content as document-style notes with timestamps, tags, and project links.
6repomix
Package entire code repositories into single AI-friendly files using Repomix. Capabilities include pack codebases with customizable include/exclude patterns, generate multiple output formats (XML, Markdown, plain text), preserve file structure and context, optimize for AI consumption with token counting, filter by file types and directories, add custom headers and summaries. Use when packaging codebases for AI analysis, creating repository snapshots for LLM context, analyzing third-party libraries, preparing for security audits, generating documentation context, or evaluating unfamiliar codebases.
5gemini-vision
Guide for implementing Google Gemini API image understanding - analyze images with captioning, classification, visual QA, object detection, segmentation, and multi-image comparison. Use when analyzing images, answering visual questions, detecting objects, or processing documents with vision.
5