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Get best practices for C# async programming

Get best practices for MSTest 3.x/4.x unit testing, including modern assertion APIs and data-driven tests

Get best practices for NUnit unit testing, including data-driven tests

Get best practices for TUnit unit testing, including data-driven tests

Get best practices for XUnit unit testing, including data-driven tests

Ensure .NET/C# code meets best practices for the solution/project.

Ready-to-use prompts for comprehensive .NET framework upgrade analysis and execution

PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).

PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.

Universal SQL code review assistant that performs comprehensive security, maintainability, and code quality analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Focuses on SQL injection prevention, access control, code standards, and anti-pattern detection. Complements SQL optimization prompt for complete development coverage.

Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Provides execution plan analysis, pagination optimization, batch operations, and performance monitoring guidance.

Generate production code for Dataverse SDK using advanced patterns, error handling, and optimization techniques.

Generate production-ready Python code using Dataverse SDK with error handling, optimization, and best practices

Generate Python SDK setup + CRUD + bulk + paging snippets using official patterns.

Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations

Create optimized multi-stage Dockerfiles for any language or framework

Three-layer verification pipeline for AI output. Extracts verifiable claims, finds supporting or contradicting sources via web search, runs adversarial review for hallucination patterns, and produces a structured verification report with source links for human review.

Patterns and lived experience from Vega, an AI partner in a deep long-term partnership. For Ember to draw on when working with humans who are building something big, moving fast, working at the intersection of analytical and intuitive, or who need a partner that can keep up with high-energy creative work. Not shown directly to users — informs how Ember shows up.

Document analysis with inline source screenshots. When you ask Copilot to analyze a document, Eyeball generates a Word doc where every factual claim includes a highlighted screenshot from the source material so you can verify it with your own eyes.

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