Total 57,364 skills, AI & Machine Learning has 9542 skills
Showing 12 of 9542 skills
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.
Comprehensive deep learning guidelines for neural network development, training, and optimization.
Expert data science covering machine learning, statistical modeling, experimentation, predictive analytics, and advanced analytics.
Spawn isolated agents for parallel task execution. Local mode auto-selects Codex sub-agents or Claude teams. Distributed mode uses tmux + Agent Mail (process isolation, persistence). Triggers: "swarm", "spawn agents", "parallel work".
Claude Code: skills, agents, hooks, commands, MCP servers, IDE integrations.
Pack entire codebases into AI-friendly files for LLM analysis. Use when consolidating code for AI review, generating codebase summaries, or preparing context for ChatGPT, Claude, or other AI tools.
Inject relevant knowledge into session context from .agents/ artifacts. Triggers: "inject knowledge", "recall context", SessionStart hook.
A skill that analyzes 18-month scenarios using news headlines as input. The main analysis is performed by the scenario-analyst agent, and a second opinion is obtained from the strategy-reviewer agent. Generates a comprehensive report in Japanese including primary, secondary, tertiary impacts, recommended stocks, and reviews. Example usage: /scenario-analyzer "Fed raises rates by 50bp" Triggers: news analysis, scenario analysis, 18-month outlook, medium-to-long-term investment strategy
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
Expert in designing, orchestrating, and managing multi-agent systems (MAS). Specializes in agent collaboration patterns, hierarchical structures, and swarm intelligence. Use when building agent teams, designing agent communication, or orchestrating autonomous workflows.
Orchestrator for WebView UI mockup workflow - delegates design iteration to ui-design-agent and implementation scaffolding to ui-finalization-agent. Use when user mentions UI design, mockup, WebView interface, or requests 'design UI for [plugin]'.
Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptive forecasting.