Skill UI

Guide for automating Webscraping AI workflows through Composio’s Webscraping AI toolkit using Rube MCP, covering connection checks, tool discovery, execution patterns, and schema compliance best practices.

A comprehensive directory designed for discovering, researching, and comparing autonomous AI agents, frameworks, and tools across diverse ecosystems. This skill helps users map the current AI agent landscape, identify existing solutions, gather best practices, and pinpoint market gaps before initiating custom development or workflow design.

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 outlines best practices for building reliable and robust AI agent harnesses. It covers optimizing action spaces, defining structured tools, managing observation formats, and implementing essential error recovery contracts. Use these principles to dramatically improve agent completion rates, manage context budgets effectively, and transition AI prototypes into stable, production-grade autonomous systems.

This skill formalizes successful, recurring patterns discovered in auto-memory (MEMORY.md) and graduates them into permanent, enforced rules within the project's core instruction set (CLAUDE.md or scoped rules). It ensures that learned best practices become mandatory project conventions, significantly improving adherence and consistency across all future AI interactions and development cycles. Use this when a temporary note proves to be a vital, repeatable guideline.

This agent enhances AI's auto-memory by analyzing raw learned patterns (from MEMORY.md). It allows users to promote proven knowledge into structured project rules (CLAUDE.md) or extract them into reusable skills. Use it to audit memory health, enforce best practices, and graduate temporary notes into permanent, actionable standards.

Documented best practices for building applications with Anthropic Claude via Python and TypeScript SDKs, covering messaging, streaming, tools, vision, reasoning, caching, batching, and Agent workflows to optimize prompts, tokens, and cost.

This tool allows users to systematically evaluate and rank the outputs of multiple agents within an AgentHub session. It supports metric-based evaluation (running custom commands for measurable metrics like speed or resource usage), or an advanced LLM Judge Mode. The LLM Judge compares results based on criteria like correctness, simplicity, and overall quality, helping users determine the best-performing agent for the task.

This skill provides guidance on implementing common architectural patterns and best practices within the PyTorch framework. It is designed for developers building sophisticated deep learning models, helping to improve structure, efficiency, and code maintainability when working with neural networks.

This skill systematically probes an AI model's core behavioral patterns across six critical dimensions, including reasoning, refusal, formatting, and grounding. It generates a comprehensive, styled HTML report with radar charts and actionable insights, allowing users to understand a model's true capabilities, compare different models, or perform compliance and red-team assessments without needing an external API key.

A comprehensive guide and function for discovering, searching, and securely installing modular agent skills from an open ecosystem. It helps users identify specialized capabilities needed for domains like web development, testing, or DevOps, utilizing the `npx skills` CLI. The skill emphasizes best practices, including checking skill reputation and requiring explicit user confirmation before running code.

Describes how to use the MemOS local memory toolkit to recall past conversations, search shared histories, and choose the right memory tool when automatic recall is insufficient.