Skill UI

LangChain accelerates building LLM-powered agents, RAG pipelines, and chatbots by orchestrating models, chains, tools, memory, and vector stores across major providers for rapid prototyping or production deployment.

This guide provides comprehensive techniques to optimize LangChain applications for production environments. Learn how to measure baseline latency, implement efficient caching strategies (in-memory, Redis, SQLite), utilize batch processing with concurrency control, and maximize perceived speed through streaming. Furthermore, it covers prompt optimization and strategic model selection to ensure high throughput and low costs.

This comprehensive guide details how to safely upgrade LangChain versions (e.g., from 0.1.x to 0.3.x+). It covers critical breaking changes across both TypeScript and Python implementations, including updating import paths, converting legacy LLMChain to the modern LCEL pipe syntax, updating agent creation, and migrating memory management. Essential for maintaining and modernizing existing LLM applications.

Guide to automating Linkhut operations through Composio’s toolkit via Rube MCP, covering discovery of current tool schemas, connection validation, multi-tool execution patterns, memory/session handling, and pagination-aware workflows.

Automate Linkup operations through Composio's Linkup toolkit by orchestrating Rube MCP calls (search tools, manage connections, execute multi-tool workflows) while strictly following schema discovery, connection validation, memory handling, and pagination guidance.

A systematic, multi-phase workflow designed for diagnosing and resolving complex Linux system issues. It guides users through initial assessment, resource analysis (CPU, memory, disk), process investigation, log analysis, network diagnostics, and service failure resolution. Ideal for system administrators and DevOps engineers handling production incidents.

A comprehensive deep dive guide for migrating translation memory (TM) and localization content from competing Translation Management Systems (TMS) like Crowdin, Phrase, or POEditor into Lokalise. This process involves exporting data from the source platform, transforming key variables and file structures to match Lokalise conventions, and finally performing a bulk API upload to establish a new, centralized localization repository. Perfect for re-platforming or migrating existing translation pipelines.

Automates Loomio workflows through Composio's Loomio toolkit via Rube MCP, guiding you to discover current tool schemas, manage Loomio connections, and execute workflows while respecting required memory, session, and schema conventions.

Guide to automating Mailcheck tasks through Composio’s Rube MCP, covering tool discovery via RUBE_SEARCH_TOOLS, connection checks, schema-compliant execution, and workflow best practices for reliable Mailcheck automation.

This comprehensive skill manages the entire lifecycle of database testing, ensuring data integrity and system reliability. It covers setting up isolated test environments (using Docker or in-memory databases), executing migrations, and implementing robust test isolation strategies (such as transaction rollback). Use cases include verifying CRUD operations, validating referential constraints, performance benchmarking (EXPLAIN ANALYZE), and ensuring backward compatibility across multiple databases (PostgreSQL, MySQL, MongoDB) and ORMs.

Orchestrate Mem0 tasks through the Rube MCP-powered Composio toolkit, ensuring schema discovery, connection validation, and memory/session management before executing any workflow.

Memory provides persistent context across multiple coding sessions. It stores crucial project decisions, user preferences (like preferred package managers or specific libraries), and architectural conventions in a local memory file. This ensures that the AI maintains consistency, recalls past choices automatically, and applies project-specific rules without needing constant reminders, significantly improving workflow continuity and reliability.