AI and machine learning skills for AI agents.

The library's AI and machine learning skills include AI Agent Builder, AI Agent Patterns and AI Automation Builder. They cover LLM engineering, applied AI, AI and ML engineering, and ML fundamentals. 35 passed Skill Guard clean. The other 6 switch on only after you have read them and said yes. 4 ready-made teams use skills from this list, such as Dev Shop and SaaS MVP Sprint. Skills are written instructions, not app connections: a bot reads the one a job calls for and works the way it lays out. Add any of them to a bot in Settings → Skills, or tell your Chief of Staff the job and let it choose.

• AI Agent BuilderAI agent architecture covering agent patterns (ReAct, Plan-and-Execute, LATS), tool design, memory systems (short-term, long-term and episodic).
• AI Agent PatternsGuides expert-level ai agent patterns implementation: ai-ml and architecture decision frameworks and production-ready patterns.
• AI Automation BuilderComprehensive guide to building AI-powered automation workflows using n8n, Zapier, Make, and custom agent frameworks covering integration patterns.
• AI Coding Assistant Power UserMaster guide to maximizing productivity with AI coding assistants including GitHub Copilot, Cursor and Claude Code.
• AI Image Generation MasterExpert-level guide to AI image generation across Midjourney, DALL-E, and Stable Diffusion covering prompt engineering for visual output and style control.
• AI Prompt CrafterAdvanced prompting techniques for any AI model covering system prompts, chain-of-thought reasoning, few-shot examples and structured output formats.
• AI Readiness EvaluationOrganizational AI readiness assessment evaluating data quality, team capabilities, infrastructure and governance.
• AI Safety EngineerAI safety and alignment engineering covering guardrail implementation, red teaming methodologies, content filtering pipelines and output validation.
• Computer VisionComputer vision implementation covering image classification, object detection (YOLO), image segmentation, OCR (Tesseract) and face detection.
• Computer Vision DeveloperHands-on computer vision development covering image classification with transfer learning, object detection with YOLO and Faster R-CNN.
• Email ProductivityEmail management mastery covering Inbox Zero methodology, filter and label systems, template libraries and batch processing workflows.
• Embedding EngineerVector embedding specialist covering embedding model comparison, dimensionality reduction, similarity metrics (cosine, euclidean and dot product).
• Feature EngineerFeature engineering covering numerical features (scaling, binning, log transforms), categorical encoding (one-hot, target and ordinal).
• Fine-Tuning GuideModel fine-tuning covering dataset preparation, LoRA and QLoRA, instruction tuning, RLHF and DPO, benchmarking and overfitting prevention.
• Knowledge Graph BuilderKnowledge graph engineering covering ontology design, graph database selection (Neo4j, Amazon Neptune and ArangoDB).
• LLM Fine-TunerLarge language model fine-tuning expertise covering LoRA and QLoRA parameter-efficient methods and full fine-tuning strategies.
• LLM IntegratorLLM API integration covering OpenAI, Anthropic, and Google API patterns, streaming responses, function calling and tool use and token counting.
• ML Ops EngineerMachine learning operations covering MLflow experiment tracking and model registry, model versioning and reproducibility.
• ML PipelineML pipeline design covering feature engineering, model training workflows, hyperparameter tuning, cross-validation, experiment tracking (MLflow and W&B).
• MLOps EngineerMLOps and deployment covering model serving (TorchServe, TF Serving, Triton), containerized inference and A/B testing deployment.
• Model Evaluation SpecialistAdvanced model evaluation covering LLM benchmarks, evaluation frameworks (lm-evaluate-harness, HELM, RAGAS) and leaderboard interpretation.
• Model EvaluatorML model assessment covering classification metrics (precision, recall, F1, AUC-ROC), regression metrics (MAE, RMSE, R2) and confusion matrix analysis.
• Multimodal AI BuilderMultimodal AI pipeline design covering vision-language models, text-audio integration, image generation and model selection across modalities.
• NLP EngineerNLP processing covering tokenization, named entity recognition, sentiment analysis, text classification, summarization and topic modeling.
• Notion MasterAdvanced Notion workspace design covering database architecture, relations and rollups, templates, dashboard creation, team workspaces and formulas.
• Obsidian Power UserAdvanced Obsidian knowledge management covering Zettelkasten methodology, linking strategy, graph navigation, essential community plugins and templates.
• Prompt EngineerPrompt engineering mastery covering chain-of-thought reasoning, few-shot learning, system prompt design and structured output with JSON mode.
• RAG ArchitectRAG system design covering document chunking strategies, embedding model selection, vector database selection (Pinecone, Weaviate, Chroma and pgvector).
• Spreadsheet WizardAdvanced Excel and Google Sheets mastery covering lookup functions, pivot tables, conditional formatting, macros and Apps Script and data validation.
• Synthetic Data GeneratorSynthetic data generation covering LLM-based data creation, statistical data synthesis, privacy-preserving techniques (differential privacy and k-anonymity).
• Vector DB EngineerVector database engineering covering Pinecone, Weaviate, Qdrant, pgvector, Milvus, and Chroma selection and configuration.
• AI Deployment PatternsGuides expert-level ai deployment patterns implementation: ai-ml and devops decision frameworks and production-ready patterns.
• AI Evaluation PatternsGuides expert-level ai evaluation patterns implementation: ai-ml and testing decision frameworks and production-ready patterns.
• Automation ArchitectWorkflow automation design using Zapier, Make, and n8n covering trigger-action architecture, multi-step automation workflows and error handling strategies.
• Calendar OptimizerStrategic calendar management covering time blocking, meeting reduction strategies, energy-based scheduling, buffer time design and focus blocks.
• Fine Tuning StrategyGuides expert-level fine-tuning strategy implementation: ai-ml and optimization decision frameworks and production-ready patterns.
• LLM Integration PatternsGuides expert-level llm integration patterns implementation: ai-ml and backend decision frameworks and production-ready patterns.
• Personal Knowledge ManagerPKM systems comparison covering PARA, Zettelkasten, GTD, and Building a Second Brain methodologies with capture workflows and processing routines.
• Prompt EngineeringGuides expert-level prompt engineering implementation: ai-ml and best-practices decision frameworks and production-ready patterns.
• RAG Pipeline DesignGuides expert-level rag pipeline design implementation: ai-ml and database decision frameworks and production-ready patterns.
• Vector Database PatternsGuides expert-level vector database patterns implementation: ai-ml and database decision frameworks and production-ready patterns.