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Found 1,966 Skills
Orchestrate end-to-end backend feature development from requirements to deployment. Use when coordinating multi-phase feature delivery across teams and services.
gh, vercel, supabase, render CLI and deployment platform setup
Deploy prompt-based Azure AI agents from YAML definitions to Azure AI Foundry projects. Use when users want to (1) create and deploy Azure AI agents, (2) set up Azure AI infrastructure, (3) deploy AI models to Azure, or (4) test deployed agents interactively. Handles authentication, RBAC, quotas, and deployment complexities automatically.
Intelligent agent for validating ERPNext/Frappe code against best practices and common pitfalls. Use when reviewing generated code, checking for errors before deployment, or validating code quality. Triggers: review this code, check my script, validate before deployment, is this correct, find bugs, check for errors, will this work.
Use when user needs LLM system architecture, model deployment, optimization strategies, and production serving infrastructure. Designs scalable large language model applications with focus on performance, cost efficiency, and safety.
This skill should be used when users need to manage GitOps deployments via ArgoCD CLI. It covers application sync, rollback, status checking, refresh, and deployment history. Integrates with Kargo for progressive delivery. Triggers on requests mentioning ArgoCD, GitOps, application sync, deployment status, or rollback operations.
Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deployment, agent evaluation, human-in-the-loop flows. Actions: build, create, deploy, evaluate, orchestrate AI agents. Keywords: Google ADK, Agent Development Kit, AI agent, multi-agent system, LlmAgent, SequentialAgent, ParallelAgent, LoopAgent, tool integration, Google Search, Code Execution, Vertex AI, Cloud Run, agent evaluation, human-in-the-loop, agent orchestration, workflow agent, hierarchical coordination. Use when: building AI agents, creating multi-agent systems, implementing workflow pipelines, integrating LLM agents with tools, deploying to Vertex AI, evaluating agent performance, implementing approval flows.
Complete guide for Apache Airflow orchestration including DAGs, operators, sensors, XComs, task dependencies, dynamic workflows, and production deployment
Configure Exa across development, staging, and production environments. Use when setting up multi-environment deployments, configuring per-environment secrets, or implementing environment-specific Exa configurations. Trigger with phrases like "exa environments", "exa staging", "exa dev prod", "exa environment setup", "exa config by env".
Automate Render tasks via Rube MCP (Composio): services, deployments, projects. Always search tools first for current schemas.
Build production-ready systems with stability patterns: circuit breakers, bulkheads, timeouts, and retry logic. Use when the user mentions "production outage", "circuit breaker", "timeout strategy", "deployment pipeline", or "chaos engineering". Covers capacity planning, health checks, and anti-fragility patterns. For data systems, see ddia-systems. For system architecture, see system-design.
.NET SDK and runtime installation across Windows, macOS, and Linux. Handles version detection, platform-specific installers (WinGet, Homebrew, apt, dnf), SDK vs runtime selection, offline installation, Docker setup, and troubleshooting. Auto-activates for .NET installation, setup, version management, and multi-platform deployment.