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All Skills

Total 50,483 skills, AI & Machine Learning has 8475 skills

Categories

Showing 12 of 8475 skills

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AI & Machine Learninghuggingface/kernels

cuda-kernels

Provides guidance for writing and benchmarking optimized CUDA kernels for NVIDIA GPUs (H100, A100, T4) targeting HuggingFace diffusers and transformers libraries. Supports models like LTX-Video, Stable Diffusion, LLaMA, Mistral, and Qwen. Includes integration with HuggingFace Kernels Hub (get_kernel) for loading pre-compiled kernels. Includes benchmarking scripts to compare kernel performance against baseline implementations.

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15
5 scripts/Checked
AI & Machine Learningruvnet/claude-flow

sparc-methodology

SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

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15
AI & Machine Learningtambo-ai/tambo

tools-and-context

Provides Tambo with data and capabilities via custom tools, MCP servers, context helpers, and resources. Use when registering tools Tambo can call, connecting MCP servers, adding context to messages, implementing @mentions, or providing additional data sources with defineTool, mcpServers, contextHelpers, or useTamboContextAttachment.

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15
AI & Machine Learninggiuseppe-trisciuoglio/dev...

chunking-strategy

Implement optimal chunking strategies in RAG systems and document processing pipelines. Use when building retrieval-augmented generation systems, vector databases, or processing large documents that require breaking into semantically meaningful segments for embeddings and search.

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15
AI & Machine Learninggiuseppe-trisciuoglio/dev...

langchain4j-rag-implementation-patterns

Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use when creating question-answering systems over document collections or AI assistants with external knowledge bases.

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15
AI & Machine Learningjezweb/claude-skills

context-mate

Entry point to the Context Mate toolkit - skills, agents, and slash commands that work with Claude Code's natural flow. Project lifecycle (/explore-idea → /plan-project → /wrap-session), session handoff across context windows, developer agents for specialized tasks, and quality auditing. Use when: starting new projects, understanding the toolkit, needing workflow guidance. "It's all about the context, maaate!"

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15
AI & Machine Learningsmithery-ai/cli

smithery

Discover, connect and use over 100K+ MCP tools and skills from the Smithery marketplace.

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15
AI & Machine Learningglittercowboy/taches-cc-r...

create-subagents

Expert guidance for creating, building, and using Claude Code subagents and the Task tool. Use when working with subagents, setting up agent configurations, understanding how agents work, or using the Task tool to launch specialized agents.

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15
AI & Machine Learningjwynia/agent-skills

gentle-teaching

Guide AI-assisted learning that empowers learners while maintaining appropriate boundaries. Use when teaching, explaining concepts, or helping someone who is struggling to understand.

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15
AI & Machine Learningletta-ai/skills

train-fasttext

Guidance for training FastText text classification models with constraints on model size and accuracy. This skill should be used when training FastText models, optimizing hyperparameters, or balancing trade-offs between model size and classification accuracy.

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15
AI & Machine Learningomer-metin/skills-for-ant...

prompt-engineer

Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when "prompt engineering, system prompt, few-shot, chain of thought, prompt design, LLM prompt, instruction tuning, prompt template, output format, prompts, llm, gpt, claude, system-prompt, few-shot, chain-of-thought, evaluation" mentioned.

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15
AI & Machine Learningpatricio0312rev/skills

rag-pipeline-builder

Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".

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15
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