Total 30,743 skills, AI & Machine Learning has 4963 skills
Showing 12 of 4963 skills
LLM integration patterns for function calling, streaming responses, local inference with Ollama, and fine-tuning customization. Use when implementing tool use, SSE streaming, local model deployment, LoRA/QLoRA fine-tuning, or multi-provider LLM APIs.
Runs an autonomous development loop with research and implementation modes. Use when orchestrating iterative research and implementation cycles with dots-based task tracking and git workflow automation.
DigitalOcean Gradient AI agentic cloud and AI platform for building, training, and deploying AI agents on GPU infrastructure with foundation models, knowledge bases, and agent routes. Use when planning or operating AI agents on DigitalOcean.
Assess platform upgrade readiness for Claude model and CC version changes. Use when evaluating upgrades.
Use when generating 50+ structured items with parallel Claude Code subagents and merging outputs into one file.
Use when building an LLM-powered app that needs cost control via model routing, budget tracking, retry, and prompt caching.
Self-contained parallel generator — invoke directly, do not decompose. Generates 3-10 app variations in parallel for comparing ideas. Use when user says "explore options", "give me variations", "riff on this", "brainstorm approaches", or wants to see multiple interpretations of a concept.
Create learning materials, explain concepts, generate quizzes and study aids. Use when asked to explain topics, create tutorials, generate practice questions, make flashcards, design curricula, or help study. Triggers include "explain this", "help me learn", "create a quiz", "tutorial for", "study guide", "how does X work", "teach me", "practice questions".
Framework adoption decision matrix: custom vs large frameworks in the Claude Code era. Use when evaluating whether to adopt a large framework or build custom with AI.
Analyze arguments, detect biases, evaluate claims, and improve reasoning. Use when asked to fact-check, identify logical fallacies, evaluate arguments, analyze predictions, find root causes, or think adversarially about plans. Triggers include "evaluate this argument", "logical fallacies", "fact check", "analyze the claims", "identify biases", "devil's advocate", "red team this", "root cause".
Expert guide for the NotebookLM CLI (`nlm`) - a command-line interface for Google NotebookLM. Use this skill when users want to interact with NotebookLM programmatically, including: creating/managing notebooks, adding sources (URLs, YouTube, text, Google Drive), generating content (podcasts, reports, quizzes, flashcards, mind maps, slides, infographics, videos, data tables), conducting research, chatting with sources, or automating NotebookLM workflows. Triggers on mentions of "nlm", "notebooklm", "notebook lm", "podcast generation", "audio overview", or any NotebookLM-related automation task.
Automatically identifies prompt type, saves to corresponding category (technical/content/teaching/product/general), and updates index. Use when user says save prompt, record, or organize prompt. Supports 5 major classifications with automatic file naming and indexing.