Skill UI

Produces production-ready Dataverse SDK code for Python, showcasing advanced error handling and retries, batch operations, OData query tuning, metadata lifecycle management, configuration/timeouts, cache invalidation, chunked file uploads, and Pandas integrations with references.

This skill provides comprehensive governance for Power Automate flows and Power Apps. It allows users to classify flows by business impact, detect orphaned resources, audit connectors, and enforce compliance by writing essential metadata to a cached store. It is ideal for IT governance teams needing centralized control and deep insight into automation assets without relying on Dataverse or the CoE Starter Kit.

A comprehensive guide for optimizing business growth motions. This framework helps founders determine the optimal Go-To-Market (GTM) strategy—whether Product-Led Growth (PLG) or sales-led—and build systematic, measurable growth engines. It covers advanced topics like mapping the growth equation, analyzing channel economics (CAC/LTV), and optimizing time to first value to ensure scalable adoption.

Provides comprehensive, enterprise-level monitoring for all Power Automate flows across an entire tenant. Using a cached store, it tracks failure rates, run health trends, asset inventory (makers, apps, connections), and compliance reports without hitting API rate limits. Ideal for governance teams needing an aggregated view of platform health and root-cause analysis.

This guide provides comprehensive best practices for creating optimized, secure, and efficient multi-stage Dockerfiles. Learn how to separate build environments (builder stage) from minimal runtime environments, significantly reducing image size and attack surface. Topics covered include layer caching optimization, security hardening (non-root users), and using minimal base images for reproducible builds.

Analyzes and generates a self-contained, explorable HTML report detailing usage metrics for Claude Code sessions. It tracks token consumption (input/output), subagent usage, skill calls, and cache efficiency across specified time ranges. This tool helps developers visualize resource waste and pinpoint areas for workflow optimization, ensuring cost-effective and efficient AI development cycles.

This skill helps developers accurately find and explore the correct Windows API for specific platform capabilities, such as file access, camera usage, notifications, or UI controls. It searches a comprehensive local cache of WinMD metadata, providing full technical details including methods, properties, events, and enumeration values for APIs sourced from the Windows Platform SDK and WinAppSDK. It is indispensable when building complex features requiring deep integration with the Windows operating system.

This advanced skill optimizes LLM context usage by implementing strict rules for prompt caching, efficient log pruning, AST-based code inspection, and compact data structuring. It minimizes token consumption and maximizes information density, suitable for highly technical and iterative development workflows.

This guide identifies and corrects the most common programming mistakes and anti-patterns when integrating with Adobe APIs. It covers critical topics such as migrating from deprecated JWT to OAuth, implementing token caching, handling asynchronous job polling, and secure file uploads. Essential reading for building robust, production-ready Adobe integrations.

A comprehensive guide for developers to optimize performance when integrating Adobe APIs (Firefly, PDF, Photoshop). Techniques covered include implementing token caching, parallelizing asynchronous job submissions, leveraging response caching (LRU), and optimizing connection handling to minimize latency and maximize throughput.

This comprehensive guide details advanced strategies for optimizing performance when interacting with blockchain data using the Alchemy SDK. Techniques covered include implementing TTL-based caching for data freshness, achieving parallel multi-chain fetches, utilizing batch API calls (e.g., NFT metadata) to reduce Compute Unit (CU) costs, and adopting WebSockets for real-time event subscriptions. Essential for scaling robust, low-latency dApps.

This skill provides actionable strategies and code patterns to significantly reduce Anima API costs. It focuses on optimizing usage through generation caching, detecting component changes for incremental generation, and implementing smart policies to minimize unnecessary API calls. Ideal for managing large-scale design-to-code workflows and controlling API budget.