Skill UI

This comprehensive workflow analyzes the health status of various AWS resources (EC2, Lambda, RDS, DynamoDB, etc.). It uses AWS CLI to diagnose potential issues by analyzing CloudWatch logs, metrics, and performance data. The process culminates in classifying root causes and generating actionable, tiered remediation plans (Immediate, Short-term, Long-term) to ensure system resilience and stability.

This skill allows users to query the current state of various AWS resources (including EC2, S3, Lambda, RDS, VPC, etc.) using natural language. It translates user intent into strictly read-only AWS CLI commands (e.g., `describe-*`, `list-*`). Crucially, this tool can only view data and is contractually incapable of performing any write, modify, delete, or mutation actions, ensuring maximum safety.

Unship is a dedicated local workflow for front-end developers to compare multiple AI-generated UI alternatives (such as layouts, copy, or flows) directly within a running application environment. Instead of committing to one generated version, it adds temporary source-level variants, allowing for visual comparison. After the user selects the final version, the skill automatically cleans up all unused temporary code and attributes, ensuring a clean, production-ready codebase. Note: This tool is for local iteration only, not for production A/B testing or analytics.

This comprehensive guide details the programmatic management of semantic model refreshes using the Power BI Enhanced Refresh REST API and Fabric CLI. It covers the entire refresh lifecycle, including resolving model IDs, validating baseline data, triggering various refresh types (full, data-only, calculate), monitoring status, and performing robust post-refresh validation. Essential for automating ETL and data pipeline processes in a modern data platform.

This skill enables the generation of rich, inline SVG graphics directly within Power BI reports. By writing DAX measures that return SVG markup strings and setting the data category to ImageUrl, users can visualize complex charts (like sparklines, gauges, and progress bars) within standard visuals such as Tables, Cards, and Matrices. It guides users through the entire process, including recommended best practices like using existing UDF libraries and adhering to strict VAR-based DAX structures.

This skill allows users to mine their extensive coding history across various AI agents (Claude, Codex, Gemini, etc.) into a persistent, structured corpus. It surfaces reproducible workflows as evidence and interactively helps the user forge these past practices into reusable, installed skills across their agent ecosystem. It is designed to synthesize judgment from raw transcripts into actionable, portable skills.

Alex converts high-level requirements into a precise, dependency-aware, and actionable implementation checklist. It maps critical paths, breaks down features into atomic micro-tasks, and establishes clear Definitions of Done (DoD) across various layers. Ideal for bridging the gap between conceptual goals and step-by-step engineering execution.

Dep handles the entire journey from local code to production deployment. This skill automates containerization using Docker and docker-compose, establishes robust CI/CD pipelines (linting, testing, security scanning, deployment), manages environment variables and secrets, and generates Infrastructure as Code (Terraform/Pulumi) configurations. It ensures observability and provides rollback procedures.

A comprehensive reference guide providing quantitative benchmarks and formulas for system architects. It covers user-to-RPS conversion, storage estimation, bandwidth calculation, known scale limits of major technologies (databases, queues, caches), and capacity planning for various user loads (1K DAU to 10M DAU). Essential for designing scalable, high-availability applications.

A comprehensive reference guide detailing best practices for writing robust and efficient Bash shell scripts. It covers critical topics such as proper quoting (`"$var"`), safe conditional testing (`[[ ]]`), reliable loops, advanced piping techniques, and essential error handling using `set -euo pipefail`. Use this guide to elevate your scripting skills and write highly portable, production-ready shell code.

This skill provides a demonstration of interacting with external APIs and services using various command-line tools (CLI). It showcases core automation patterns, including fetching API documentation details and listing messages using specific application CLIs, making it ideal for testing and learning API integration flows.

A sophisticated automated loop that uses vision or video models to evaluate subjective aesthetic quality (e.g., timing, color grade, layout). Instead of relying on numeric metrics, the system renders multiple parameterized variants into one artifact, asks the AI to rate them, and suggests optimal values, repeating the process until convergence. Ideal for design iteration where human judgment is the primary success criteria.