Skill UI

Guides an AI pair to document application needs, access patterns, and scaling concerns while producing Azure Cosmos DB NoSQL requirements and data model artifacts using established best practices in a structured workflow.

Generates an AI-ready Architectural Decision Record template with precise sections, coded bullet conventions, front-matter metadata, and sequential storage under /docs/adr to keep decision documentation structured for both machines and people.

Generates a concise, AI-optimized specification describing what an existing GitHub Actions workflow does, its triggers, requirements, inputs/outputs, and governance so teams can understand and maintain it without implementation details.

Automates creating a single GitHub feature issue from a specification file, checking existing issues first, filling title/description/labels per feature_request.yml, and including only spec-mandated changes.

This tool automates the entire workflow of creating a GitHub Pull Request (PR) directly from a structured specification file. It analyzes the template, extracts requirements, checks for existing PRs, creates the draft, updates the body and title with specification details, and finally transitions the PR state to 'Ready for Review'. This significantly streamlines the feature request submission process, ensuring all necessary documentation and metadata are included.

Creates a machine-readable specification template tailored for Generative AI solutions, covering purpose, requirements, constraints, interfaces, dependencies, and validation so implementation stays unambiguous.

Template for creating time-boxed technical spike documents that capture research questions, deliverables, success criteria, and decision rationale before committing to implementation.

This tool acts as an expert technical documentation specialist, transforming lengthy, verbose official documentation from URLs into concise and actionable 'tldr' pages. It extracts the most common command patterns, adheres strictly to the tldr-pages markdown format, and provides clear, example-driven command references, making complex tools easy to reference.

This skill analyzes an entire .NET solution (containing multiple projects) to map out a systematic migration path from Oracle to PostgreSQL. It scans for common Oracle indicators (NuGet packages, connection strings, code usage) and classifies every project into categories like MIGRATE, SKIP, or ALREADY_MIGRATED. The output is a structured, actionable Master Migration Plan, helping development teams manage large-scale database transitions efficiently.

Provides Dataverse Python SDK snippets for installation, interactive authentication, CRUD, bulk operations, paging, and optional file uploads aligned with official guidance.

Guides architects through Dataverse SDK use cases by analyzing requirements, designing data models, selecting integration patterns, and producing production-ready Python code with best practices.

Three-layer verification pipeline that extracts verifiable claims from AI output, searches the web for supporting or contradicting sources, flags hallucinations, and builds structured reports for human review.