Embeddings
Vector embeddings and similarity
corrective-rag
by latestaiagents
Implement Corrective RAG (CRAG) and Self-RAG for reliable, self-healing retrieval systems. Use this skill when building reliable RAG, preventing hallucinations, implementing retrieval evaluation, or adding self-correction to RAG pipelines. Activate when: corrective RAG, CRAG, self-RAG, hallucination prevention, retrieval evaluation, RAG reliability, self-healing RAG, document grading.
graphrag-patterns
by latestaiagents
Implement GraphRAG combining knowledge graphs with RAG for multi-hop reasoning. Use this skill when building knowledge graph RAG, implementing multi-hop queries, using Neo4j with RAG, or connecting entities across documents. Activate when: GraphRAG, knowledge graph, multi-hop reasoning, Neo4j RAG, entity extraction, relationship queries, graph database, connected data.
agentic-rag
by latestaiagents
Build agentic RAG systems with autonomous planning, reflection, and tool use. Use this skill when implementing agent-driven retrieval, query decomposition, iterative refinement, or multi-source RAG orchestration. Activate when: agentic RAG, A-RAG, autonomous retrieval, query planning, iterative RAG, multi-step retrieval, agent retrieval, RAG agent.
memory-management
by richfrem
"Tiered memory system for cognitive continuity across agent sessions. Manages hot cache (session context loaded at boot) and deep storage (loaded on demand). Use when: (1) starting a session and loading context, (2) deciding what to remember vs forget, (3) promoting/demoting knowledge between tiers, (4) user says 'remember this' or asks about project history."
memory-integration
by troykelly
Use to maintain context across sessions - integrates episodic-memory for conversation recall and mcp__memory knowledge graph for persistent facts
memory-integration
by troykelly
Use to maintain context across sessions - integrates episodic-memory for conversation recall and mcp__memory knowledge graph for persistent facts
x-algo-ml
by CloudAI-X
Explain the Phoenix ML model architecture for X recommendations. Use when users ask about embeddings, transformers, how predictions work, or ML model details.
content-strategy
by aiaiohhh
When the user wants to plan a content strategy, decide what content to create, or figure out what topics to cover. Also use when the user mentions "content strategy," "what should I write about," "content ideas," "blog strategy," "topic clusters," or "content planning." For writing individual pieces, see copywriting. For SEO-specific audits, see seo-audit.
free-tool-strategy
by aiaiohhh
When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," or "free resource." This skill bridges engineering and marketing — useful for founders and technical marketers.
app-intents-expert-skill
by rudrankriyam
Expert App Intents guidance for building Siri, Shortcuts, Spotlight, Apple Intelligence, and interactive snippet integrations on iOS 26+. Use when implementing AppIntent, AppEntity, AppEnum, EntityQuery, AppShortcutsProvider, SnippetIntent, SiriTipView, IndexedEntity, or when making an app work with Siri, Shortcuts, Spotlight, Apple Intelligence, Visual Intelligence, Action Button, or Apple Pencil. Also use when asked about App Intents architecture, intent-driven development, or migrating from SiriKit.
auto-claude-memory
by adaptationio
Auto-Claude Graphiti memory system configuration and usage. Use when setting up memory persistence, configuring LLM/embedding providers, querying knowledge graph, or optimizing memory performance.
Smoke Test Critical Paths Skill
by FortiumPartners
Load: skills/smoke-test-critical-paths/REFERENCE.md (~10KB)
agent-memory-system
by adaptationio
Persistent memory architecture for AI agents across sessions. Episodic memory (past events), procedural memory (learned skills), semantic memory (knowledge graph), short-term memory (active context). Use when implementing cross-session persistence, skill learning, context preservation, personalization, or building truly adaptive AI systems with long-term memory.
deep-learning-core
by levy-n
Explains neural network fundamentals: the Three Pillars (Model, Loss, Optimizer), backpropagation, gradient descent variants (SGD, Adam), regularization (Dropout, BatchNorm), and MLP architecture design. Use when learning how neural networks work, debugging training issues, or when user asks about 'backpropagation', 'vanishing gradients', 'learning rate', 'loss function', 'overfitting', 'underfitting', 'activation functions', 'why isn\'t my model learning', 'gradient descent', 'Adam', 'Dropout', 'BatchNorm', 'autoencoder', 'denoising autoencoder', or 'latent space'.
ml-knowledge-index
by levy-n
Routes ML/DL questions to specialized skills. Use FIRST when unsure which skill applies, when user asks broad ML questions, or when multiple topics might be relevant. Maps: regression/classification → ml-fundamentals, ensembles/clustering → ml-advanced, TF-IDF/Word2Vec → nlp-classical, training/backprop → deep-learning-core, PyTorch → pytorch-mastery, CNNs/images → cnn-vision, LSTM/time-series → sequence-models, BERT/HuggingFace → transformers-llm, RAG/embeddings → rag-retrieval, APIs/PDF-parsing → data-pipeline, LoRA/QLoRA/PEFT → fine-tuning-peft, MLflow/W&B/Optuna → mlops-experiment, SHAP/Grad-CAM → model-interpretability, Q-learning/PPO/DQN → reinforcement-learning, GAN/VAE/diffusion → generative-models, explanations → ml-teaching-assistant.
langchain-agents
by eyadsibai
Use when "LangChain", "LLM chains", "ReAct agents", "tool calling", or asking about "RAG pipelines", "conversation memory", "document QA", "agent tools", "LangSmith"
changelog-setup
by phrazzld
Full changelog infrastructure from scratch. Greenfield workflow. Installs semantic-release, commitlint, GitHub Actions, LLM synthesis, public page.
before-file-search
by eveld
Use BEFORE running grep or glob commands. Reminds you to use codebase-locator agent instead of basic file search tools.
nlp-classical
by levy-n
Implements traditional NLP techniques before transformers. Covers text vectorization (TF-IDF, Bag-of-Words), word embeddings (Word2Vec, FastText, GloVe, Doc2Vec), topic modeling (LDA, Gensim), and text similarity (Jaccard, Cosine, FuzzyWuzzy, record linkage). Use when building text classifiers without deep learning, doing topic extraction, entity matching, or when user mentions 'TF-IDF', 'Word2Vec', 'topic modeling', 'LDA', 'text similarity', 'n-grams', 'document clustering', 'GloVe', 'Doc2Vec', 'FuzzyWuzzy', or 'record linkage'.
accessibility-engineer
by mae616
Apply semantic HTML/JSX and WAI-ARIA correctly and minimally. Apply when implementing any UI, especially forms, interactive components, or when accessibility is mentioned.
ai-native-development
by ArieGoldkin
Build AI-first applications with RAG pipelines, embeddings, vector databases, agentic workflows, and LLM integration. Master prompt engineering, function calling, streaming responses, and cost optimization for 2025+ AI development.
Accessibility Patterns
by Kaakati
WCAG 2.2 Level AA compliance patterns for Flutter applications including Semantics widgets, screen reader support, keyboard navigation, and color contrast requirements
ai-prd-generator
by cdeust
Enterprise PRD generation with VisionEngine (Apple Foundation Models, 180+ components), Business KPIs (8 metric systems), context-aware depth (8 PRD types), license-aware tiered architecture, 15 RAG-enhanced thinking strategies, research-based prioritization, MCP server with 7 utility tools, Cowork plugin support, and production-ready technical specifications
changelog
by phrazzld
Complete changelog and release notes infrastructure. Audits current state, implements missing components, and verifies the release pipeline works end-to-end.