Skill UI

A comprehensive toolset for planning, validating, and executing complex system, database, and infrastructure migrations with zero downtime. It covers critical phases like schema evolution (Expand-Contract), API compatibility checks, risk assessment, and generating automated rollback runbooks. Essential for high-risk transitions where business continuity is paramount.

Automates migration guide creation by providing step-by-step documentation patterns, best practices, and validated snippets for APIs, user guides, and architecture docs.

A comprehensive guide for migrating existing AI integrations from providers like OpenAI or Anthropic to Mistral AI. This blueprint covers the entire lifecycle: initial assessment of AI touchpoints, detailed model mapping (e.g., gpt-4o to mistral-large), implementing a provider-agnostic adapter pattern, and executing controlled, feature-flag-controlled rollout plans for major refactoring projects.

This comprehensive skill guides developers through major version upgrades of the Mistral AI SDK. It specifically detects breaking changes, such as the shift from CommonJS to ESM, and provides detailed steps, automated code transformation scripts, and best practices for migrating existing code. Use this when jumping major SDK versions or refactoring complex Mistral integrations to ensure a smooth transition to the latest API.

Guides setting up modern Python projects with uv, ruff, ty, pytest, prek, and security checks, covering initialization, pyproject configuration, dependency and tool management, quick-start scripts, full project layout, and migrations from legacy tooling.

This skill provides a comprehensive decision framework and set of patterns for architects designing cloud-agnostic applications across major providers like AWS, Azure, and GCP. It details service comparisons (Compute, Storage, DB), multi-cloud patterns (e.g., Best-of-Breed, DR), cost optimization strategies, and structured migration plans, ensuring robust and resilient enterprise deployments.

This deep-dive tool automates the complex process of migrating notes and knowledge bases from various platforms (such as Notion, Evernote, Roam, etc.) into Obsidian. It handles critical conversions like stripping platform-specific UUIDs, converting internal links to optimized Obsidian wikilinks ([[...]]), and correctly formatting attachments and YAML frontmatter, ensuring a seamless transition and preserving the structural integrity of your knowledge base.

This guide provides essential, production-ready architectural patterns for building highly reliable Obsidian plugins. It addresses common development pitfalls such as managing typed settings with versioned migration, implementing safe vault operations (check-before-act), and handling event listeners to prevent memory leaks. Use these patterns when hardening your plugin for public release or refactoring for maximum stability.

A comprehensive guide for developers migrating and upgrading Obsidian plugins across major API versions. It covers critical steps such as auditing plugin compatibility, implementing version-aware settings migration logic (for user data persistence), replacing deprecated API calls (e.g., Vault, Editor, FileManager), and updating configuration files like manifest.json to ensure stability on new Obsidian releases.

This deep dive guide provides comprehensive strategies and detailed checklists for migrating to the OpenEvidence platform. It covers various migration methods, such as parallel run, Strangler fig, and Big bang approaches. The guide assists technical teams in planning the transition by addressing key areas including API mapping, data migration plans, rollback procedures, and performance baselines, ensuring a secure and smooth transition for healthcare IT systems.

This guide provides a comprehensive roadmap for migrating and upgrading integrations with the OpenEvidence clinical AI platform. It addresses critical API changes, such as schema restructuring (e.g., flat answers to structured evidence), version detection, and updated citation formats. Developers can use this knowledge to implement robust migration logic, ensuring that downstream clinical applications maintain high levels of accuracy and safety when accessing evolving medical evidence.

This skill guides developers on migrating their codebase from direct OpenAI API calls to using OpenRouter. By making minimal changes—primarily updating the base URL and API key—users gain access to over 400 models from multiple providers (including Anthropic and Google) through a unified SDK interface, ensuring high compatibility and flexible model switching.