Skill UI

Automates Neon serverless Postgres workflows via the Composio MCP, letting you list projects and branches, inspect databases, manage roles, and retrieve connection URIs for pipelines and tooling integrations.

Automates NestJS module scaffolding with best-practice templates for backend services, covering Node.js, Python, Go, databases, caching, messaging, and microservices architecture.

Expert guidance on designing highly scalable, distributed NoSQL databases, specifically covering Apache Cassandra and Amazon DynamoDB. This skill emphasizes the 'Query-First' modeling approach, teaching best practices like partitioning, denormalization, single-table design, and avoiding common anti-patterns (e.g., hot partitions, joins) to ensure optimal read/write performance at massive scale.

Guides automation of Notion via Composio’s Rube MCP toolkit, covering setup, tool sequences, parameter expectations, and common pitfalls for pages, databases, blocks, schemas, users, and comments.

Automates capturing chat insights into structured Notion pages by extracting key concepts, organizing content by type, and linking newly created entries into the right wikis and databases for easy discovery.

A comprehensive workflow for systematically reviewing medical evidence. It allows users to search databases for clinical studies, build curated citation collections, grade evidence using established frameworks like GRADE, and generate professionally formatted, structured reports in academic citation styles (e.g., AMA). Ideal for conducting literature reviews and supporting clinical research. This tool helps transform raw medical data into actionable, structured knowledge.

This skill provides comprehensive expertise for senior database administrators to optimize and manage PostgreSQL databases at an advanced level. Use it for deep query analysis via EXPLAIN ANALYZE, implementing advanced features like JSONB indexing, configuring streaming or logical replication, and maintaining database health through VACUUM tuning and monitoring pg_stat views. Ideal for building highly available, high-performance, and resilient system architectures.

A specialized, comprehensive workflow designed for optimizing PostgreSQL databases. It guides users through performance assessment, advanced query tuning (using EXPLAIN ANALYZE), defining optimal indexing strategies, fine-tuning configuration parameters (like shared_buffers), and setting up robust maintenance and monitoring practices for production environments.

This comprehensive workflow guides the end-to-end implementation of Retrieval-Augmented Generation (RAG) systems. It covers critical stages, including selecting optimal embedding models, setting up vector databases, designing chunking strategies, implementing hybrid retrieval, integrating Large Language Models (LLMs), and performing rigorous evaluation. Use this when building knowledge-grounded AI applications or advanced semantic search systems.

Automatically collects comprehensive diagnostic information for Replit workspaces, deployments, and databases. This tool gathers system state, runtime versions, environment variables, network logs, and package details. It is essential for troubleshooting persistent issues or preparing detailed evidence for support tickets.

This comprehensive guide details how to optimize the Replit development environment. It covers setting up run commands, implementing hot reloading for various languages (Node.js, Python), configuring ports, managing development vs. production databases, and leveraging the Replit Agent for powerful AI-assisted coding. Use this guide when setting up a new project or refining your entire dev workflow.

This comprehensive guide outlines the necessary steps for major Replit environment upgrades and data migration. It covers updating Nix channels, upgrading runtimes (Node.js, Python), and migrating critical data from Replit KV databases to PostgreSQL or Object Storage. It also details switching between deployment types, ensuring a smooth and stable transition for production applications.