Skill UI

This skill converts a single static image (PNG/JPG) into a short, animated MP4 video using the Ken-Burns zoom effect. It is specifically designed as a robust fallback mechanism for automated video workflows. If an upstream AI video generation step fails—often due to content moderation flags (e.g., facial recognition or audio safety issues)—this animator ensures a valid placeholder clip is generated. This allows downstream merging steps to complete the deliverable without interruption, maintaining the narrative flow.

This workflow systematically analyzes deployed AWS resources and Infrastructure-as-Code (IaC) definitions. It collects usage metrics from CloudWatch and Cost Explorer to identify over-provisioning, unused resources, and inefficient configurations (e.g., right-sizing EC2, S3 lifecycle policies). It generates actionable cost optimization recommendations and creates structured GitHub issues for tracking and implementing savings.

This automated workflow performs a comprehensive review against the AWS Well-Architected Framework (WAF). It scans IaC definitions (Terraform, CloudFormation, CDK) and deployed resources to identify compliance gaps, security risks, and optimization opportunities across six core pillars. Findings are structured and automatically generated as actionable GitHub issues with remediation code examples.

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 skill provides expert guidance on using the Fabric Command Line Interface (`fab`) to programmatically interact with Power BI and Fabric workspaces. It covers critical operations including resource listing, querying data using DAX, SQL, and DuckDB, managing permissions, setting properties, and handling deployments. Ideal for advanced automation, CI/CD pipelines, and data engineering tasks within the Microsoft Fabric ecosystem.

A comprehensive CLI tool for programmatically exploring, building, formatting, and managing Power BI reports. It supports the entire report lifecycle, including connecting to semantic models, running validations, creating mockups, and publishing reports to Fabric workspaces for reliable and structured report development.

A comprehensive reference for the Power BI Enhanced Report (PBIR) JSON format. This skill details the structure of report metadata, including visual configurations (visual.json), report-level settings, theme inheritance, and complex formatting rules. It is essential for developers needing to read, interpret, or programmatically interact with the internal workings and schema of Power BI reports.

Atlas Ledger is a critical companion designed to provide lasting 'memory' to project contracts. It automatically processes detected deviations or 'drift' (e.g., from audits or reviews) and distills these instances into formal, actionable contract clauses (WHEN/DON'T/INSTEAD). These clauses are written to a persistent project memory file, Atlas.md. This mechanism ensures that lessons learned from failure are systematically captured, allowing future contract cycles to incorporate these rules, thereby strengthening overall project governance and reliability.

Max is a specialized agent designed for safe, non-behavioral code improvement. It systematically refactors existing, working code by optimizing time complexity (Big-O), abstracting duplicated logic, removing dead code, and enhancing readability. It operates under a strict constraint: no change may alter the original functionality, requiring all refactored code to pass existing test suites flawlessly.

This guide helps developers audit and clean up Vite + React projects initialized using the Lovable scaffolding tool. It systematically removes all boilerplate artifacts, including placeholder assets, dedicated dependencies (like lovable-tagger), generated documentation, and unnecessary components (e.g., unused Radix deps). The goal is to deliver a clean, fully owned, and production-ready codebase.

This skill generates a complete React component structure following the industry-standard Container/Presentation pattern. It automatically scaffolds necessary files, including TypeScript, Storybook, and SCSS styles, ensuring adherence to project conventions. Use this when building new, scalable components, allowing you to properly classify whether the component is UI-focused (Presentation) or logic-heavy (Container).

This skill generates a comprehensive, actionable runbook for any service, designed specifically for on-call engineers. It structures critical incident response procedures, including alert definitions, escalation matrices, diagnostic commands, and rollback steps, significantly reducing Mean Time To Resolution (MTTR). It provides a single source of truth for responding confidently during high-stress incidents.