Skill UI

This skill provides a comprehensive guide to configuring CodeRabbit for advanced, security-focused code reviews. It teaches how to implement rules for detecting hardcoded secrets, common vulnerabilities (like SQL injection and XSS), and enforcing secure coding standards across APIs, databases, and infrastructure code. Use this when hardening a codebase's security posture or ensuring compliance with industry standards.

Guides chaos engineering experiments by defining objectives, choosing tools such as Chaos Mesh, Gremlin, Toxiproxy, or AWS FIS, injecting failures, monitoring metrics, and recommending fixes to harden services and APIs.

This skill automatically fetches the latest official documentation for programming libraries and frameworks (such as React, Next.js, or Prisma) via the Context7 API. It is essential for developers who require accurate, up-to-date technical reference material to ensure their code adheres to the most current best practices.

Automates contributing guide creation in technical documentation; triggers on explicit requests, follows best practices, offers step-by-step help, generates code/config samples, and validates outputs for API docs, user guides, and architecture docs.

Guides using Rube MCP via Composio to discover Convertapi tool schemas, manage toolkit connections, and execute safe multi-step conversions without hardcoded slugs.

Combines model routing, immutable budget tracking, retry policies, and prompt caching so LLM API calls stay on-budget without sacrificing quality, ideal for batch workloads with mixed complexity.

Automates Countdown API workflows through Composio’s Countdown toolkit using Rube MCP, emphasizing tool discovery, connection checks, and schema-compliant execution for reliable integration.

Automates Currents API operations through Composio’s Rube MCP, guiding tool discovery, connection checks, schema compliance, and multi-tool execution so clients can run reliable workflows without hardcoding schemas.

This tool optimizes the codebase indexing within Cursor. It processes your entire codebase, converting code chunks into vector embeddings stored in a vector database. This enables advanced @Codebase semantic search, allowing users to ask natural language questions (e.g., "Where is authentication handled?") and retrieve the most relevant code snippets, significantly improving AI context awareness across chat and coding tasks.

A powerful AI tool designed for complex, coordinated programming tasks. It enables developers to generate, refactor, and scaffold entire features across multiple files (e.g., schema, API routes, service layers, tests) while maintaining consistency with existing codebase patterns. It supports agent mode for autonomous, multi-step changes and allows systematic migration and review of all affected files via detailed diffs.

A comprehensive guide on configuring and selecting the optimal AI model within the Cursor IDE. It details the strengths of various providers (OpenAI, Anthropic, Google) for specific coding tasks—from quick bug fixes to complex architecture planning—and guides users through model selection, API key setup (BYOK), and cost optimization strategies.

A comprehensive reference guide for structuring development projects within the Cursor IDE. It details best practices for directory layout, defining layered rules (covering global conventions, security constraints, and technology-specific patterns like API routes and database access), and optimizing indexing strategies. This ensures maximum AI effectiveness, improves code maintainability, and streamlines the entire development workflow.