Skill UI

Generates implementation-ready JSON-LD schema markup for 10 types (e.g., FAQPage, Product, Article). It validates all fields against Google rich result eligibility rules, flags missing data with fix instructions, and provides clean, ready-to-paste script blocks to optimize search engine visibility and achieve rich results.

A comprehensive guide on integrating and calling Firebase Callable Cloud Functions within Flutter applications. Covers setup, passing structured data, robust error handling, performance optimization (timeouts, caching), and local testing using the Firebase Emulator Suite.

Improves Go error handling by treating errors as structured data. This utility adds critical context—such as domain, user IDs, stack traces, and machine-readable error codes—to standard Go errors. This capability is vital for enhancing observability, enabling APM tools (like Sentry or Datadog) and on-call engineers to diagnose complex issues quickly without relying on manual log correlation.

A comprehensive collection of composable handlers and middlewares for Go's standard slog package. This skill enables developers to build robust, multi-stage logging pipelines by implementing critical steps like log sampling (throughput control), attribute formatting (PII stripping), advanced routing, and sinking logs to various professional backends (e.g., Sentry, Loki, Datadog). Ideal for production-grade services requiring high observability.

This advanced prompt acts as a structured guide for generating comprehensive, enterprise-grade technical implementation plans. It forces the detailed breakdown of a feature based on a PRD, covering system architecture (Mermaid diagrams), database schema design, API specifications, frontend component hierarchy, and deployment strategies, all while adhering to a monorepo structure. Ideal for large-scale SaaS development.

Learn how to add Adaptive Card response templates to MCP-based API plugins. This guide details static, dynamic, and combined templates, enabling developers to enhance data presentation and ensure a visually rich, structured user experience within Microsoft 365 Copilot.

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.

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.

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.

This guide outlines the process and mandatory structure for documenting defects found during an Oracle-to-PostgreSQL migration. It details how to write actionable bug reports, covering required elements like Severity, Root Cause, Scenario, and Solution. It emphasizes treating Oracle as the source of truth and handling data layer nuances (e.g., NULL vs. empty string) to ensure accurate defect tracking and remediation.

Bulk migrate repo labels and Project V2 metadata into GitHub org issue fields, converting label-based tags into typed fields, optionally removing old labels, and syncing project field values for cleaner structured issue tracking.