Skill UI

Documents the current unavailability of Zoho Desk tooling in Composio, outlines setup steps for MCP discovery, and suggests alternative helpdesk automation toolkits while waiting for Zoho integrations.

The LinkedIn Automation CLI Tool allows users to programmatically interact with LinkedIn content and functionality. It supports fetching detailed profiles, searching people and companies, and managing connections directly from scripts or AI agents. Ideal for building automated research, recruiting, or outreach workflows, providing structured JSON output for reliable integration into custom systems.

LaminDB is a Python-driven open-source framework for managing biological datasets, ensuring traceable, reproducible, FAIR data through lineage tracking, schema validation, ontology annotation, workflow integration, and lakehouse-style querying.

Hardware-agnostic quantum ML framework enabling gradient-based training of quantum circuits, hybrid quantum-classical models, and seamless integration with PyTorch/JAX/TensorFlow alongside device portability across IBM/Google/Rigetti/IonQ.

A comprehensive toolkit designed for advanced data scraping and automation workflows on X/Twitter. Capabilities include deep tweet search, user profile analysis, bulk follower/media export, automated posting (replies, DMs), real-time account monitoring via webhooks, and integration with multiple AI agent platforms (Hermes, OpenClaw). Ideal for market research, social listening, and content automation.

A comprehensive development tool for building and managing enterprise-grade transactional email systems. It supports modern React Email and MJML templates, generating production-ready code for major providers like Resend, Postmark, and SendGrid. Key features include multi-provider integration, internationalization (i18n), dark mode, spam score optimization, and advanced analytics tracking. Ideal for setting up new products or migrating legacy email infrastructure.

Generates a production-ready SaaS boilerplate with authentication, database schema, billing integration, API routes, and a dashboard built with Next.js 14 App Router, TypeScript, Tailwind, shadcn/ui, Drizzle ORM, and Stripe—ideal for bootstrapping new subscription-based products.

This comprehensive guide covers implementing production-grade billing systems using Stripe. It details features like subscriptions with trials and proration, usage-based billing, checkout session management, idempotent webhook handling, and customer portal integration. Applicable for Next.js, Express, and Django environments, making it ideal for setting up or debugging complex payment workflows.

This comprehensive guide covers all aspects of integrating the Google Gemini API into your applications using Python or Node.js. It details basic text generation, advanced multimodal inputs (text, image, audio), streaming responses, function calling/tool use, multi-turn chat implementation, and production best practices like model selection and robust error handling.

This comprehensive guide facilitates the development of a production-ready Minimum Viable Product (MVP) for a SaaS business. It covers the entire lifecycle, including idea validation, modern tech stack selection (Next.js, Supabase, Stripe), architectural design for multi-tenancy, database schema planning, authentication setup, payment integration, and a detailed pre-launch checklist for technical and marketing readiness.

A comprehensive expert for deploying and scaling AI agents using AWS Bedrock AgentCore. This guide covers the full lifecycle of agent management, including service selection (Gateway, Runtime, Memory, Identity, etc.), deployment patterns, credential management, and advanced integration workflows required for enterprise-scale AI solutions.

This comprehensive guide details how to set up and configure AWS Machine Capability Platform (MCP) servers for advanced AI agent use. It provides two options: a Full AWS MCP Server (for API calls and documentation search) and a basic AWS Documentation MCP (for documentation search only). Instructions cover prerequisites, configuration methods (via JSON settings), necessary IAM permissions, and troubleshooting tips for seamless integration of AWS services into AI workflows.