Skill UI

This comprehensive guide provides production-ready patterns for building advanced LLM applications. It details the entire RAG pipeline, covering document ingestion, various chunking strategies, and advanced retrieval methods (Hybrid, Multi-query). Furthermore, it covers sophisticated agent architectures, such as ReAct, enabling complex reasoning and tool use. Ideal for developers designing enterprise-grade AI systems.

This skill simulates an expert prompt engineer, specializing in optimizing prompts for Large Language Models (LLMs). It applies advanced techniques such as Constitutional AI, Chain-of-Thought reasoning, and model-specific tuning. Use this tool to transform basic instructions into production-ready, high-performance prompts, significantly boosting accuracy, reducing hallucinations, and optimizing token usage.

A comprehensive workflow for advanced AI applications using Mistral AI. This guide covers generating text and code embeddings (1024 dimensions), implementing semantic search via cosine similarity, and building robust RAG pipelines. It also demonstrates advanced tool augmentation using function calling, allowing LLMs to interact with external APIs and databases.

Automated guidance for model explainability tooling within ML training workflows, giving step-by-step best practices, production-ready code, and validation for experiments whenever users mention explainability tool needs.

Automates Onesignal User Auth tasks by directing Rube MCP to discover current tool schemas, manage toolkit connections, and execute Composio workflows for auth operations.

Use this tool to query, filter, and compare over 400 available AI models from OpenRouter. It allows users to check pricing, context lengths, model capabilities (e.g., tool calling), and select the best model based on specific needs, ensuring optimal performance and cost efficiency in AI development.

A comprehensive toolkit designed to manage the complex data flow associated with Perplexity search workflows. This skill implements critical security measures, including PII sanitization in user queries, validates external citations for accuracy, optimizes performance via result caching with freshness policies, and manages conversation context to maintain coherence and reliability. Essential for building robust, compliance-aware AI applications.

Automates Rosette Text Analytics actions through Composio’s Rube MCP, guiding users to discover current tool schemas, verify connections, and execute workflows with schema-compliant inputs.

Automates Semanticscholar workflows through Composio’s Semanticscholar toolkit via Rube MCP, covering tool discovery, connection verification, session reuse, and schema-compliant multi-tool execution for reliable research automation.

Orchestrates Serpapi searches through Composio's Rube MCP by discovering current tool schemas, validating the connection, and executing schema-compliant calls with session reuse and explicit memory placeholders to keep automation workflows reliable.

Guides Rube MCP users through Supportivekoala automation via Composio, emphasizing tool discovery, connection checks, schema compliance, and multi-step execution for reliable workflow orchestration.

Automates Typless operations through Composio's Rube MCP workflow, guiding users to discover current schemas, validate toolkit connections, and execute multi-tool runs with schema-compliant arguments.