Skill UI

Automate blockchain Alchemy tasks through Composio's Rube MCP by always discovering current tool schemas, managing the Alchemy toolkit connection, and executing multi-tool workflows with schema-compliant arguments.

Use the Rube MCP endpoints to orchestrate Exist workflows: discover current tool schemas, validate connections, and execute multi-step tool chains while tracking sessions and memory state for reliable automation.

This skill provides guidance and patterns for generating structured JSON files that define complex workflow pipelines. It is essential for chaining multiple distinct AI models together, enabling multi-step, automated data processing. Use this when a single task requires a sequence of interconnected AI operations or services.

Automates Fidel API workflows through Composio’s toolkit via Rube MCP, emphasizing schema discovery, managed connections, and multi-tool execution with reusable sessions for reliable operational chains.

Master the art of building robust, production-grade LLM chains using LangChain Expression Language (LCEL). This guide covers advanced composition patterns, including sequential, parallel, and conditional branching chains. It also details prompt templating, structured output parsing (JSON/Zod), and context injection, enabling the creation of complex, multi-step AI pipelines.

This skill provides a comprehensive guide for deploying LangChain chains and agents into production-grade APIs. It supports multiple development stacks, including Python (LangServe/FastAPI) and Node.js (Express). Topics covered include containerization using Docker, setting up robust health checks, and deploying to major cloud platforms like Google Cloud Run and AWS Lambda. Learn how to build scalable, observable, and enterprise-grade API endpoints for advanced LLM applications.

This module implements comprehensive Role-Based Access Control (RBAC) for multi-tenant LangChain applications. It provides granular permission models for controlling model access, tool execution, and chain invocation. Key features include multi-tenant data isolation in vector stores, enforcing usage quotas (token limits), and integrating middleware for robust security enforcement. Ideal for building secure, scalable, and compliant enterprise LLM systems.

This guide details best practices for configuring LangChain applications across development, staging, and production environments. It ensures strict environment isolation by managing separate API keys, model settings, and LangSmith project names. The setup utilizes Zod for robust validation and integrates secure secret management via GitHub Actions, AWS Secrets Manager, or GCP, guaranteeing reliable and secure deployments.

This blueprint provides a scalable, production-grade reference architecture for advanced LLM applications using LangChain. It guides the implementation of layered design, provider abstraction (allowing seamless switching between LLMs like OpenAI and Anthropic), dynamic chain registry, robust RAG pipelines, and complex multi-agent orchestration. Ideal for building enterprise-level, maintainable, and highly flexible AI systems.

A comprehensive utility designed to monitor, analyze, and predict blockchain gas costs across multiple major chains (e.g., Ethereum, Polygon, Arbitrum). It fetches real-time pricing, estimates transaction costs in both ETH and USD, and identifies the optimal time windows for executing DeFi or NFT transactions, ensuring maximum cost efficiency.

Automates Passcreator procedures through Composio's toolkit with Rube MCP by discovering current schemas, verifying active connections, and executing schema-compliant tool chains, including search, connection checks, and multi-tool runs.

This skill acts as a specialized security expert for analyzing project dependencies. It scans dependencies across multiple ecosystems (e.g., npm, pip, Maven) to identify known vulnerabilities, assess associated risks, and generate Software Bill of Materials (SBOMs). It provides comprehensive insights into supply chain security and offers automated strategies for remediation, ensuring compliance and stability during development.