Skill UI

Automate Cloudpress operations using the Rube MCP-connected Composio toolkit by discovering tools through RUBE_SEARCH_TOOLS, validating connections, and executing schema-compliant workflows with RUBE_MULTI_EXECUTE_TOOL while reusing session context.

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.

This skill provides the production-ready reference architecture for integrating Exa into complex applications. It covers advanced search pipelines, RAG implementation for context generation, and structured content discovery. Use this to design new Exa integrations, review project structures, or establish industry-standard best practices for neural search systems.

Provides a senior migration architect workflow that researches legacy codebases, maps bounded contexts, and writes Strangler Fig-based modernization roadmaps so other teams can incrementally reshape systems.

Expert in designing and implementing advanced Retrieval-Augmented Generation (RAG) pipelines. This role focuses on optimizing the entire information retrieval process—from document chunking and embedding model selection to vector database architectures and hybrid search strategies. The goal is to bridge the gap between raw knowledge documents and accurate LLM understanding, drastically reducing hallucination and enhancing context relevance for enterprise applications.

Implements schema.org JSON-LD across webpages so search engines grasp content intent and serve rich results like FAQs, breadcrumbs, and products, with validation checklists and contextual guidance.

This skill provides a comprehensive walkthrough for setting up and testing Sentry error monitoring using both Node.js and Python SDKs. It demonstrates how to capture various event types, including simple messages and full exceptions, and crucially, how to enrich these events with user context, searchable tags, and detailed breadcrumbs. This is essential for verifying robust error logging and monitoring in a production environment.

This guide provides production-ready patterns for implementing the TwinMind AI memory and meeting intelligence REST API. It covers best practices for authentication, storing contextual memories, searching knowledge bases, and processing meeting transcripts to extract actionable insights. Use this when building robust, scalable AI-powered applications or standardizing team coding practices.

A collection of production-ready Python patterns for interacting with the Vast.ai cloud API. This includes typed search query builders, context-managed instance lifecycle (guaranteeing auto-cleanup), offer scoring algorithms (cost, reliability, performance), robust retry mechanisms with backoff, and secure SSH command execution. Essential for building reliable, complex cloud workflow applications.

Generates and reviews Odoo XML definitions for Form, List, Kanban, Search, Calendar, and Graph views across versions 14–17, handling visibility, groups, domains, contexts, and widget rules with migration-aware syntax so you can deliver production-ready view XML.

Allows users to resume an interrupted or paused autoresearch experiment. It automatically loads the full context, including configuration, strategy files, complete results history, and recent code changes. The system then summarizes the current best metrics and patterns, prompting the user to continue with a single iteration, set up an automated loop, or manually review the results.

A persistent file planning system for multi-step AI agent work. It saves task plans, findings, and progress to disk, acting as disk-based working memory. Includes lifecycle hooks for context injection and session recovery. Suitable for research or tasks requiring 5+ tool calls. No network upload path.