Guide for creating effective Claude Code agents. This skill should be used when users want to create a new agent (or update an existing agent) that configures Claude with specialized system prompts, tool restrictions, model selection, and MCP/skill integrations.
Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.
Recognize a photo and narrate a kid-friendly explanation using image understanding + TTS.
Create and maintain AgentV YAML evaluation files for testing AI agent performance. Use this skill when creating new eval files, adding eval cases, or configuring custom evaluators (code validators or LLM judges) for agent testing workflows.
Reduces LLM costs and improves response times through caching, model selection, batching, and prompt optimization. Provides cost breakdowns, latency hotspots, and configuration recommendations. Use for "cost reduction", "performance optimization", "latency improvement", or "efficiency".
Add and manage Model Context Protocol (MCP) servers for AI agents, including transports, scopes, and config files. Use when extending agent capabilities with new tools or data sources.
Frontend React hooks for AI-powered chat interfaces, completions, and streaming UIs with Vercel AI SDK v5. Includes useChat, useCompletion, and useObject hooks for building interactive AI applications. Use when: building React chat interfaces, implementing AI completions in UI, streaming AI responses to frontend, handling chat message state, building Next.js AI apps, managing file attachments with AI, or encountering errors like "useChat failed to parse stream", "useChat no response", unclosed streams, or streaming issues. Keywords: ai sdk ui, useChat hook, useCompletion hook, useObject hook, react ai chat, ai chat interface, streaming ai ui, nextjs ai chat, vercel ai ui, react streaming, ai sdk react, chat message state, ai file attachments, message persistence, useChat error, streaming failed ui, parse stream error, useChat no response, react ai hooks, nextjs app router ai, nextjs pages router ai
Usa esta skill para diseñar y modificar el pipeline de RAG, incluyendo LangGraph, retrieval híbrido, GraphRAG y prompts de LLM.
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
Design and build knowledge graphs. Use when modeling complex relationships, building semantic search, or creating knowledge bases. Covers schema design, entity relationships, and graph database selection.
Add and manage evaluation results in Hugging Face model repositories using the new .eval_results/ format. Supports extracting scores from model cards, importing from Artificial Analysis API, and batch processing trending models.
Use when search queries need better recall through query expansion - generates multiple query variants, retrieves with each, and fuses results using RRF for improved retrieval quality especially with ambiguous or under-specified queries
Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
Builds Model Context Protocol (MCP) servers for Claude with tools, resources, and prompts. Use when users request "create MCP server", "build Claude tool", "MCP integration", or "custom Claude tools".
Diagnoses LLM output failures including hallucinations, constraint violations, format errors, and reasoning issues. Provides root cause classification, prompt fixes, tool improvements, and new test cases. Use for "debugging AI", "fixing prompts", "quality issues", or "output errors".
Expert guidance for Stan probabilistic programming language development, including modern syntax, cmdstanr/cmdstanpy integration, and testing patterns
Bayesian statistical modeling with PyMC v5+. Use when building probabilistic models, specifying priors, running MCMC inference, diagnosing convergence, or comparing models. Covers PyMC, ArviZ, pymc-bart, pymc-extras, nutpie, and JAX/NumPyro backends. Triggers on tasks involving: Bayesian inference, posterior sampling, hierarchical/multilevel models, GLMs, time series, Gaussian processes, BART, mixture models, prior/posterior predictive checks, MCMC diagnostics, LOO-CV, WAIC, model comparison, or causal inference with do/observe.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Design and implement a complete ML pipeline for: $ARGUMENTS
Generate synthetic PDF documents for RAG and unstructured data use cases. Use when creating test PDFs, demo documents, or evaluation datasets for retrieval systems.
Calculate statistical significance for A/B tests. Sample size estimation, power analysis, and conversion rate comparisons with confidence intervals.
Expert in technical adjustment grid construction for comparable sales analysis including adjustment hierarchy, quantification methods (paired sales, regression, cost, income), and validation techniques. Use when constructing detailed comparable sales grids, quantifying specific adjustments, applying statistical validation, or reconciling adjusted sale prices. Key terms include adjustment grid, paired sales analysis, hedonic regression, gross adjustment limits, net adjustment, sensitivity analysis
Analyzes UXR report PDFs and generates structured analysis documents with key findings, recommendations, and strategic connections. Use when given a UXR report to analyze.
Calculate ROI for marketing campaigns, investments, and business decisions. Includes break-even analysis, payback period, and comparative ROI.
