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Found 18 Skills
Use Neo4j GenAI Plugin ai.text.* functions and procedures for in-Cypher embedding generation, text completion, structured output, chat, tokenization, and batch ingestion. Covers ai.text.embed(), ai.text.embedBatch(), ai.text.completion(), ai.text.structuredCompletion(), ai.text.aggregateCompletion(), ai.text.chat(), ai.text.tokenCount(), ai.text.chunkByTokenLimit(), and provider configuration for OpenAI, Azure OpenAI, VertexAI, and Amazon Bedrock. Requires CYPHER 25. Replaces deprecated genai.vector.encode(). Use when writing pure-Cypher GraphRAG, embedding nodes in-graph, generating structured maps from prompts, or calling LLMs inside Cypher queries. Does NOT handle neo4j-graphrag Python library pipelines — use neo4j-graphrag-skill. Does NOT handle vector index creation/search — use neo4j-vector-index-skill.
Train your own GPT-2 level LLM for under $100 using nanochat, Karpathy's minimal hackable harness covering tokenization, pretraining, finetuning, evaluation, inference, and chat UI.
Implement PCI DSS compliance requirements for secure handling of payment card data and payment systems. Use when securing payment processing, achieving PCI compliance, or implementing payment card security measures.
Use when "HuggingFace Transformers", "pre-trained models", "pipeline API", or asking about "text generation", "text classification", "question answering", "NER", "fine-tuning transformers", "AutoModel", "Trainer API"
Inspect and debug KGF (Knowledge Graph Framework) specs — tokenize, parse, and extract edges from source files. Use when the user wants to debug language parsing, inspect how indexion processes a file, or verify KGF spec behavior.
Convert a public brand URL into a practical DESIGN.md file and optional single-file HTML demo. Use when the user asks to extract, distill, compile, generate, or validate a DESIGN.md/design system from a website, brand page, press kit, or public visual identity.