🏆 Vibe Ranking Top 500
The definitive ranking across Skills, MCP Servers, Plugins, and Marketplaces in the Claude Code ecosystem
The definitive ranking across Skills, MCP Servers, Plugins, and Marketplaces in the Claude Code ecosystem
Microsoft🎯Skillmicrosoft/azure-skillsA Claude Code skill from Microsoft for querying and analyzing data using Azure Data Explorer (Kusto) with KQL query assistance.
Microsoft🎯Skillmicrosoft/azure-skillsA Claude Code skill from Microsoft for working with Azure messaging services including Service Bus, Event Hubs, and Event Grid.
A model-invoked productivity skill that interviews users relentlessly about a plan or design until every branch of the decision tree is resolved. It serves as the reusable interview loop behind the grill-me and grill-with-docs skills.
A collection of composable engineering skills by Matt Pocock designed to fix common AI coding agent failure modes: misalignment via grilling sessions, verbosity through shared domain language (CONTEXT.md), code quality with TDD red-green-refactor loops, and codebase entropy with architecture improvement workflows.
Anthropic🔌Pluginanthropics/claude-codeInteractive learning mode that requests meaningful code contributions at decision points (mimics the unshipped Learning output style)
Official best practices for Remotion, a React-based video creation framework. Provides domain-specific knowledge for video composition, animations, captions, 3D content, audio, fonts, and rendering.
Microsoft🎯Skillmicrosoft/azure-skillsA Claude Code skill from Microsoft for managing Azure Role-Based Access Control, including role assignments, custom roles, and permission auditing.
Microsoft🎯Skillmicrosoft/azure-skillsA Claude Code skill from Microsoft for managing Azure compute resources including VMs, App Services, Functions, and Container Instances.
Microsoft🎯Skillmicrosoft/azure-skillsA Claude Code skill from Microsoft for adding Application Insights telemetry to your apps, enabling performance monitoring and error tracking on Azure.
Microsoft🎯Skillmicrosoft/azure-skillsA Claude Code skill from Microsoft that generates visual maps of Azure resource relationships, dependencies, and architecture diagrams.
Anthropic🔌Pluginanthropics/claude-codeComprehensive toolkit for developing Claude Code plugins. Includes 7 expert skills covering hooks, MCP integration, commands, agents, and best practices. AI-assisted plugin creation and validation.
A model-invoked engineering skill that actively builds and sharpens a project's domain model by challenging terms against the glossary, stress-testing with edge-case scenarios, and updating CONTEXT.md and ADRs inline.
Microsoft🎯Skillmicrosoft/azure-skillsA Claude Code skill from Microsoft that assists with planning and executing cloud migration strategies from on-premises or other clouds to Azure.
A model-invoked engineering skill that provides shared discipline and vocabulary for designing deep modules: maximizing behavior behind small interfaces, placing code at clean seams, and ensuring testability through public APIs.
A model-invoked skill that guides coding agents through a disciplined diagnosis loop for hard bugs: reproduce, minimise, hypothesise, instrument, fix, and regression-test.
A helper skill in the RigorPilot suite that resolves gaps between a deep learning repository's README and its associated research paper, helping agents understand the paper context needed for faithful reproduction.
A RigorPilot helper skill that scans deep learning repositories and extracts README commands to build an initial reproduction plan, typically invoked by the main reproduction orchestrator.
Anthropic🔌Pluginanthropics/claude-codeEasily create custom hooks to prevent unwanted behaviors by analyzing conversation patterns or from explicit instructions. Define rules via simple markdown files.
A RigorPilot trusted-lane skill for conservatively running documented evaluation, inference, smoke tests, and sanity checks in deep learning repositories without introducing unaudited changes.
A RigorPilot trusted-lane skill for conservatively setting up deep learning environments, including datasets, pretrained weights, checkpoints, and cache assumptions required for research reproduction.