Skill UI

A specialized skill for architecting, building, and productionizing complex Agent Development Kit (ADK) agents and multi-agent systems. This process emphasizes best practices, including clean module structure, robust tool integration, comprehensive regression testing, and deployment automation for reliable, shippable AI solutions. Use this when requiring the creation of structured, enterprise-grade agent code.

Provision production-grade Vertex AI ADK Agent Engine infrastructure with Terraform, covering Agent Engine runtime, code execution sandbox, Memory Bank, VPC Service Controls, and secure IAM setup for multi-agent deployments.

Design multi-agent system architectures using patterns like supervisor, swarm, and pipeline. Generate provider-ready tool schemas for Anthropic and OpenAI. Evaluate execution logs to identify bottlenecks, latency, and costs. Use for complex agent workflows requiring structured design and optimization, not simple automation scripts.

This skill provides a comprehensive guide to designing and developing autonomous AI agents for code plugins. It covers the required file structure (YAML frontmatter), best practices for defining agent roles, designing robust system prompts, and setting up clear triggering conditions. Use this when you need to conceptualize, structure, or refine an agent's capabilities to handle complex, multi-step tasks autonomously.

A systematic workflow designed to significantly improve the reliability and performance of existing AI agents. It covers detailed performance analysis, including gathering metrics (e.g., task success rate, latency), classifying failure modes, and advanced prompt engineering techniques (like Chain-of-Thought and Constitutional AI). The process culminates in structured A/B testing and controlled deployment, ensuring measurable, robust improvements.

This skill defines the coordination protocol for multi-agent execution during development sprints. It governs how project architects must spawn specialized agents (e.g., backend, frontend, QA), manage dependencies via shared contracts, and collect comprehensive, structured reports. It ensures systematic, parallel, and controlled project iteration development.

Guide to automate Agenty tasks through Composio’s Agenty toolkit by orchestrating Rube MCP workflows, ensuring schema discovery, connection checks, and structured tool execution.

Helps analyze current CPU, memory, storage, and network utilization to forecast future infrastructure needs, identify bottlenecks, and recommend scaling tactics with cost context for proactive capacity management.

Helps analyze current CPU, memory, storage, and network utilization to forecast future infrastructure needs, identify bottlenecks, and recommend scaling tactics with cost context for proactive capacity management.

Analyzes application logs to spot slow requests, recurring errors, and resource warnings, helping troubleshoot performance issues and inform structured logging or monitoring improvements.

Analyzes application logs to spot slow requests, recurring errors, and resource warnings, helping troubleshoot performance issues and inform structured logging or monitoring improvements.

Guides a structured walkthrough for onboarding into unfamiliar codebases by covering quick overviews, stack detection, directory mapping, pattern spotting, workflow checks, and summary reporting so teams can answer "how does this work" with confidence.