Skill UI

This skill optimizes multi-agent systems through coordinated profiling, workload distribution, and cost-aware orchestration. It helps improve agent performance, throughput, and reliability by identifying bottlenecks, managing context windows, and reducing latency. Suitable for complex workflows requiring intelligent coordination and efficiency tracking across multiple AI agents.

Coordinates discovery, matching, and workflow orchestration across agent ecosystems, automatically scanning SKILL.md, ranking relevant skills, and executing multi-step plans for complex requests.

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.

A comprehensive, multi-phase workflow designed for building sophisticated AI systems. This guide covers everything from designing autonomous agents and implementing single-agent logic, to orchestrating complex multi-agent systems and integrating advanced tools and memory mechanisms. Ideal for developers building production-grade AI applications using frameworks like CrewAI and LangGraph.

Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Ensures graceful degradation and clear failure modes. Capable of agent architecture design, tool calling, memory management, and debugging complex agent systems.

This AI-driven system integrates multi-dimensional health data including lifestyle, medical history, and mental health to identify anomalies and predict risks. It provides personalized health recommendations based on evidence-based guidelines and generates comprehensive interactive reports. Supports intelligent Q&A for health metrics and trends, ensuring data privacy with local processing. Ideal for users seeking data-driven health insights without replacing professional medical advice.

This skill enables building production-ready LLM applications, advanced RAG systems, and intelligent agents. It covers vector search, multimodal AI, agent orchestration, and enterprise integrations. Learn to design architectures, optimize embeddings, ensure safety, and deploy models at scale using frameworks like LangChain and vector databases.

This toolkit provides six production-ready AI engineering workflows including prompt evaluation, context budget planning, RAG pipeline design, agent security audits, evaluation harness building, and product sense coaching. It transforms AI coding assistants into senior engineering partners with structured methodologies, quantitative scoring, and checklists for consistent results in LLM system optimization and security.

Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models, reducing token usage while increasing compliance. Ideal for optimizing LLM system prompts and migrating rules between AI tools.

Orchestrate AI/ML workflows including data ingestion, model training, batch inference, and RAG indexing using tools like Prefect, Airflow, or Dagster. Essential for managing complex AI systems and automating ML pipelines.

Secure LLM and AI systems against prompt injection, data exfiltration, model theft, and supply chain attacks in production environments. This skill covers input sanitization, output filtering, PII scrubbing, and API endpoint protection to ensure compliance with SOC2 or ISO 27001 standards.

Design patterns for building autonomous coding agents, including tool calling APIs, permission systems, browser automation, and human-in-the-loop workflows. Inspired by Cline and OpenAI Codex, this skill provides guidance for creating efficient and safe AI agents.