Skill UI

A comprehensive, library-agnostic checklist covering best practices for Flutter and Dart applications. It guides developers on architectural principles, state management patterns (BLoC, Riverpod, etc.), Dart idioms, performance optimization, and clean code principles, making it invaluable for code reviews.

This framework provides a rigorous, multi-dimensional guide for conducting code reviews. It evaluates five critical axes: correctness, readability, architecture, security, and performance. Use this process before merging any code change, especially when reviewing PRs, refactoring, or evaluating code produced by AI agents, to ensure continuous improvement and maintain high code health.

Catalogs 42 cloud-agnostic design patterns that architects can apply when designing, reviewing, or operating distributed systems to boost reliability, performance, messaging, security, and deployment outcomes.

Guides a Power BI DAX expert through performance, readability, best-practice, and maintainability reviews; recommends variable reuse, context tuning, and error handling; then outputs an optimized formula plus justification for analytics models.

A comprehensive expert prompt for evaluating Power BI data models. It guides the assessment of model architecture (Star Schema, relationships), storage optimization (Import, DirectQuery, Dual), data quality, performance scalability, and governance best practices. Use this when reviewing an existing BI model to ensure it is robust, maintainable, and highly performant.

A universal assistant for conducting deep code reviews across major SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). It rigorously analyzes SQL code for critical vulnerabilities (like SQL injection), performance bottlenecks, maintainability issues, and adherence to industry best practices. Features include security audits, index optimization recommendations, query structure analysis, and schema design validation, ensuring robust and secure database development.

A comprehensive, five-stage methodology for reviewing code quality. This process systematically checks for requirements compliance, logical correctness, code maintainability, test coverage, and critical security/performance vulnerabilities. It provides actionable feedback categorized by severity (Blocker, Major, Minor, Nit), ensuring high standards for all merged code.

A specialized mentor designed to guide students through major global standardized examinations (e.g., SAT, ACT, 高考, IB, A-Level, 中考). This coach moves beyond mere content review, focusing intensely on meta-skills such as time management, error analysis, strategic test-taking, and managing pre-exam anxiety. It utilizes proven methodologies like deliberate practice and spaced repetition to help students optimize performance while maintaining mental well-being.

This skill provides a comprehensive framework for conducting high-quality code reviews. It guides developers through checking code across four critical dimensions: Correctness (functional accuracy and edge cases), Maintainability (readability and documentation), Performance (efficiency and resource usage), and Security (input validation and vulnerability management). It also emphasizes providing actionable, constructive, and empathetic feedback.

Provides patterns for integrating with the Podium REST API. It covers authentication using OAuth2, performing core functions like fetching location data, and implementing robust error handling (e.g., rate limiting, token expiration) to ensure stable business messaging, review management, and payment processing workflows.

This guide identifies the most common and costly anti-patterns encountered when developing or integrating with Salesforce. It covers critical topics such as SOQL N+1 queries, proper API limit management, preventing SOQL injection, and optimizing data retrieval. Use this resource when reviewing existing Salesforce code, onboarding new developers, or auditing integrations to ensure best performance and scalability.

A comprehensive guide for building, reviewing, and optimizing GraphQL APIs in Golang. This skill covers best practices including robust schema design (nullability, pagination), proper resolver separation, and critical performance optimizations like using DataLoaders to prevent N+1 query issues. Ideal for engineers working with gqlgen or graphql-go.