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Found 289 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).
Neovim (LazyVim) configuration via Nix: LSP, plugins, im-select, extraPackages. Mason is disabled; all LSP/formatters/linters are managed by Nix extraPackages. Triggers: "nvim 플러그인", "lazy.nvim", "한글 입력", "im-select", "extraPackages", "Mason 비활성화", "tree-sitter 빌드 오류", "LSP 서버 안 됨", "markdownlint", "Neovim 설정", Mason migration, tree-sitter build errors, lazy-lock.json conflict.
Design distributed systems using Leslie Lamport's rigorous approach. Emphasizes formal reasoning, logical time, consensus protocols, and state machine replication. Use when building systems where correctness under concurrency and partial failure is critical.
Use this skill when crafting LLM prompts, implementing chain-of-thought reasoning, designing few-shot examples, building RAG pipelines, or optimizing prompt performance. Triggers on prompt design, system prompts, few-shot learning, chain-of-thought, prompt chaining, RAG, retrieval-augmented generation, prompt templates, structured output, and any task requiring effective LLM interaction patterns.
Use this skill when designing event-driven systems, implementing event sourcing, applying CQRS patterns, selecting message brokers, or reasoning about eventual consistency. Triggers on tasks involving Kafka, RabbitMQ, event stores, command-query separation, domain events, sagas, compensating transactions, idempotency, message ordering, and any architecture where components communicate through asynchronous events rather than direct synchronous calls.
Install AI UI components from the Elements registry. Use when user needs chat interfaces, agentic UIs (tool calls, reasoning, plans), multi-agent dashboards, or AI devtools. Triggers on "AI component", "chat UI", "agent UI", "tool call component", "streaming text", "agentic", "multi-agent", "AI SDK", "chat input", "message bubble", "thinking indicator".
#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.
E-commerce email marketing system builder. Creates complete email automation flows with full copywriting, subject lines, ESP setup instructions, segmentation rules, and annual campaign calendars. Generates copy-paste-ready email sequences for Klaviyo, Omnisend, Mailchimp, or any ESP. Covers welcome series, cart abandonment, browse abandonment, post-purchase, review requests, cross-sell, win-back, VIP/loyalty, replenishment, and sunset flows. Includes A/B test subject line variants, send timing, trigger conditions, branching logic, and seasonal campaign calendar. No API key required. Use when: (1) setting up email marketing for an e-commerce store, (2) writing email sequences and flows, (3) planning seasonal email campaigns.
Logseq Datascript schema, built-in properties/classes, and :db/ident discovery for composing or reviewing Datascript queries about blocks/pages/tags/properties/classes. Use whenever editing or reviewing Datascript pull selectors or queries, or any code that adds/removes attributes in pull patterns, or touches property namespaces/identifiers, or requires reasoning about property value shapes/ref/cardinality in Logseq.
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, designing systems, or making architectural decisions. Enters plan mode, reads all available docs, explores the codebase deeply, then interviews the user relentlessly with ultrathink-level reasoning on every decision until a shared understanding is reached. Produces a validated design spec before any implementation begins. Triggers on feature requests, design discussions, refactors, new projects, component creation, system changes, and any task requiring design decisions.
React useEffect anti-pattern detection and correction guide. Use this skill whenever writing, reviewing, or modifying any React component that contains useEffect, or when about to add a useEffect hook. Also trigger when you see patterns like "setState inside useEffect", "effect chains", "derived state in effect", or "notify parent in effect". Covers 12 specific scenarios where Effects are unnecessary or misused, with correct alternatives. Even if the useEffect looks reasonable at first glance, consult this skill to verify it's truly needed.
Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.