Loading...
Loading...
Found 797 Skills
Monitor Render services in real-time. Check health, performance metrics, logs, and resource usage. Use when users want to check service status, view metrics, monitor performance, or verify deployments are healthy.
Helps estimate and calculate Azure resource costs. Use this skill when users ask about Azure pricing, cost estimation, resource sizing costs, comparing pricing tiers, budgeting for Azure deployments, or understanding Azure billing. Triggers include questions like "how much will this cost in Azure", "estimate Azure costs", "compare Azure pricing", "budget for Azure resources".
Analyze AI/ML technical content (papers, articles, blog posts) and extract actionable insights filtered through enterprise AI engineering lens. Use when user provides URL/document for AI/ML content analysis, asks to "review this paper", or mentions technical content in domains like RAG, embeddings, fine-tuning, prompt engineering, LLM deployment.
ABC Jenkins Project Deployment Skill. Supports intelligent parameter inference and interactive triggering of Jenkins builds, automatically retrieves Git branch and tag information. This skill is triggered when users request "Deploy Jenkins", "Trigger Build", "Deploy Project", "Jenkins Deployment" or similar operations. Requires environment variables JENKINS_USER and JENKINS_TOKEN.
Frappe Bench CLI command reference for site management, app management, development, and production operations. Use when running bench commands, managing sites, migrations, builds, or deployments.
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.
Workflows for generating terraform solution that are the composition of one or several Terraform IBM Modules (TIM). Use when working with IBM Cloud infrastructure as code, Terraform modules, infrastructure automation, or cloud resource provisioning. Provides workflows for module discovery, composition patterns, code generation, and validation. Essential for tasks involving IBM Cloud VPC, compute, networking, security, databases, observability, or any IBM Cloud service deployment. Triggers on keywords like "terraform", "IBM Cloud", "infrastructure", "IaC", "modules", "deploy", "provision", or specific IBM Cloud services (VPC, VSI, OpenShift, etc.).
Modern Python API development with FastAPI covering async patterns, Pydantic validation, dependency injection, and production deployment
Complete guide for Hasura GraphQL Engine including instant GraphQL APIs, permissions, authentication, event triggers, actions, and production deployment
Complete guide for Apache Airflow orchestration including DAGs, operators, sensors, XComs, task dependencies, dynamic workflows, and production deployment
Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
Machine learning development patterns, model training, evaluation, and deployment. Use when building ML pipelines, training models, feature engineering, model evaluation, or deploying ML systems to production.