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Found 762 Skills
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX Runtime, and OllamaSharp. Covers the full spectrum from classic ML through modern LLM orchestration to local inference. Use when adding classification, regression, clustering, anomaly detection, recommendation, LLM integration (text generation, summarization, reasoning), RAG pipelines with vector search, agentic workflows with tool calling, Copilot extensions, or custom model inference via ONNX Runtime to a .NET project. DO NOT USE FOR projects targeting .NET Framework (requires .NET 8+), the task is pure data engineering or ETL with no ML/AI component, or the project needs a custom deep learning training loop (use Python with PyTorch/TensorFlow, then export to ONNX for .NET inference).
Comprehensive Azure administration capabilities covering identity management, resource orchestration, CLI tooling, and DevOps automation. Auto-activates for Azure, az cli, azd, Entra ID, RBAC, and infrastructure tasks.
Use this skill when setting up or managing monorepos, configuring workspace dependencies, optimizing build caching, or choosing between monorepo tools. Triggers on Turborepo, Nx, Bazel, pnpm workspaces, npm workspaces, yarn workspaces, build pipelines, task orchestration, affected commands, and any task requiring multi-package repository management.
Monorepo tooling, task orchestration, and workspace architecture for JavaScript/TypeScript repositories. Use when setting up Turborepo, Nx, pnpm workspaces, or npm workspaces; designing package boundaries; configuring remote caching; optimizing CI for affected packages; managing versioning with Changesets; or untangling circular dependencies. Activate on "monorepo", "turborepo", "nx", "pnpm workspace", "task pipeline", "remote cache", "changesets", "CODEOWNERS", "circular dependency", "affected packages", "workspace". NOT for git submodules or multi-repo federation strategies, non-JavaScript monorepos (Bazel, Pants, Buck), or single-package repository setup.
#1 on DeepResearch Bench (Feb 2026). Any-to-Any AI for agents. Combines deep reasoning with all modalities through sophisticated multi-agent orchestration. Research, videos, images, audio, dashboards, presentations, spreadsheets, and more.
Simple scroll-triggered reveal animations using AOS (Animate On Scroll). Use this skill when building marketing pages, landing pages, or content-heavy sites requiring basic fade/slide effects without complex animation orchestration. Triggers on tasks involving scroll animations, scroll-triggered reveals, AOS, simple animations, or basic scroll effects. Alternative to GSAP ScrollTrigger and Locomotive Scroll for simpler use cases. Compare with motion-framer for React-specific animations.
Use this skill when designing AI agent architectures, implementing tool use, building multi-agent systems, or creating agent memory. Triggers on AI agents, tool calling, agent loops, ReAct pattern, multi-agent orchestration, agent memory, planning strategies, agent evaluation, and any task requiring autonomous AI agent design.
Use this skill when building data pipelines, ETL/ELT workflows, or data transformation layers. Triggers on Airflow DAG design, dbt model creation, Spark job optimization, streaming vs batch architecture decisions, data ingestion, data quality checks, pipeline orchestration, incremental loads, CDC (change data capture), schema evolution, and data warehouse modeling. Acts as a senior data engineer advisor for building reliable, scalable data infrastructure.
Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
Create isolated Neon database branches for testing. Schema-only branches with auto-cleanup via TTL, test server orchestration, and environment variable management.
Manages context window optimization, session state persistence, and token budget allocation for multi-agent workflows. Use when dealing with token budget management, context window limits, session handoff, state persistence across agents, or /clear strategies. Do NOT use for agent orchestration patterns (use moai-foundation-core instead).
Master of LLM Economic Orchestration, specialized in Google GenAI (Gemini 3), Context Caching, and High-Fidelity Token Engineering.