Skill UI

Frontend Blueprint is an AI design consultant that structures discovery before coding, asking targeted questions, collecting references, and validating direction to deliver pixel-faithful UI components only when the context is clear.

Uses the GitHub CLI to inspect failing PR checks in GitHub Actions, collect log snippets, draft a fix plan, and implement changes only after explicit approval so CI failures are resolved with clear context.

A comprehensive guide to production-grade concurrency patterns in Go. It details the proper use of goroutines, channels, sync primitives, and context management. Use this skill when building highly concurrent applications, implementing worker pools, managing goroutine lifecycles, or debugging race conditions in Go.

This utility automatically collects comprehensive diagnostic data for the Granola application, including system specifications, audio configurations, network connectivity tests, and application metadata. It packages all findings into a single ZIP file for support teams. Use this when preparing a detailed support ticket or troubleshooting complex, persistent issues. The process is designed to collect diagnostic context without exposing sensitive meeting content, transcripts, or private API keys.

This utility provides programmatic access to Granola meeting data, enabling developers to build automated post-meeting workflows. Users can read meeting notes from the local cache, integrate with MCP servers for AI context, automatically extract action items and assignees, and sync outcomes directly into coding tasks, project documentation, or issue trackers like GitHub. Ideal for automating the development lifecycle from meeting insights.

Guidance lets you wrap LLM calls with grammars, regex, and selection constraints to ensure valid JSON/XML/code, enforce formats, heal tokens, and orchestrate multi-step workflows via Pythonic context managers for production-ready automation.

A comprehensive guide detailing Apple's Human Interface Guidelines (HIG) for integrating apps into system surfaces. Covers best practices for widgets, Live Activities, notifications, complications, App Clips, and other system components, ensuring apps provide glanceable, contextual utility outside the main app environment.

This skill automatically gathers and structures comprehensive context for Apple product development. It analyzes existing project files (like README, Info.plist, and code) and prompts the user for details across product overview, target platforms, technology stack, design system, and accessibility requirements. The output is a structured context document used by other specialized skills to ensure consistent, informed design and development decisions.

This skill leverages Google Gemini's advanced image generation model to create high-quality, context-specific visuals. It is essential for developers needing placeholder images for UIs, generating detailed diagrams for technical documentation, or visualizing abstract concepts, logos, and assets across cross-platform projects (Windows, macOS, Linux).

This module provides production-grade patterns for integrating the Juicebox AI-powered people search API. It includes a singleton client for centralized rate-limit handling, a robust request builder for complex criteria (location, company, experience years), and structured error wrappers for reliable API calls (retries, error context). Ideal for building scalable recruitment, market research, or data enrichment tools.

This skill provides step-by-step guidance for creating production-ready Kubernetes manifests. It covers essential resources including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims. Use this skill when defining complete, robust containerized application architectures, managing network connectivity, stateful workloads, and ensuring adherence to Kubernetes best practices like resource limits and security contexts.

Master the art of building robust, production-grade LLM chains using LangChain Expression Language (LCEL). This guide covers advanced composition patterns, including sequential, parallel, and conditional branching chains. It also details prompt templating, structured output parsing (JSON/Zod), and context injection, enabling the creation of complex, multi-step AI pipelines.