Total 55,752 skills, AI & Machine Learning has 9269 skills
Showing 12 of 9269 skills
[EXPLICIT INVOCATION ONLY] Creates dependency-aware implementation plans optimized for parallel multi-agent execution.
The industry standard library for machine learning in Python. Provides simple and efficient tools for predictive data analysis, covering classification, regression, clustering, dimensionality reduction, model selection, and preprocessing.
Multi-step reasoning patterns and frameworks for systematic problem solving. Activate for Chain-of-Thought, Tree-of-Thought, hypothesis-driven debugging, and structured analytical approaches that leverage extended thinking.
Build a conversational AI assistant with memory and state. Use when you need a customer support chatbot, helpdesk bot, onboarding assistant, sales qualification bot, FAQ assistant, or any multi-turn conversational AI. Powered by DSPy for response quality and LangGraph for conversation state management.
Switch AI providers or models without breaking things. Use when you want to switch from OpenAI to Anthropic, try a cheaper model, stop depending on one vendor, compare models side-by-side, a model update broke your outputs, you need vendor diversification, or you want to migrate to a local model. Covers DSPy model portability — provider config, re-optimization, model comparison, and multi-model pipelines.
Generate optimized prompts for AI image and video generation. Triggers on "generate a prompt for", "write me a prompt", "create an image prompt", "create a video prompt", "optimize this prompt".
Triages GitHub issues by routing to oncall teams, applying labels, and closing questions. Use when processing new PyTorch issues or when asked to triage an issue.
Multi-agent feature implementation. Spawns independent solver agents that each implement the feature from scratch, then synthesizes the best elements from each. Use when building complex features where you want diverse approaches and comprehensive edge case coverage.
Analyze a codebase to extract its conventions, patterns, and style. Spawns specialized analyzer agents that each focus on one aspect (structure, naming, patterns, testing, frontend). Generates a comprehensive style guide that other skills can reference. Use when starting work on an unfamiliar codebase, or to create explicit documentation of implicit conventions.
Use when working with error debugging multi agent review
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Adaptive epoch selection for Walk-Forward Optimization. TRIGGERS - WFO epoch, epoch selection, WFE optimization, overfitting epochs.