Total 53,920 skills, AI & Machine Learning has 8968 skills
Showing 12 of 8968 skills
AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.
Local speech-to-text via Handy app (push-to-talk) and NeMo CLI scripts. Parakeet V3: 25 languages, auto-detection, ~30x realtime on M4 Max, 6% WER. This skill should be used when transcribing audio files or dictating voice input.
Build AI scientist systems using ToolUniverse Python SDK for scientific research. Use when users need to access 1000++ scientific tools through Python code, create scientific workflows, perform drug discovery, protein analysis, genomics analysis, literature research, or any computational biology task. Triggers include requests to use scientific tools programmatically, build research pipelines, analyze biological data, search literature, predict drug properties, or create AI-powered scientific workflows.
Choose and combine Eve storage primitives to give agents persistent memory — short-term workspace, medium-term attachments and threads, long-term org docs and filesystem. Use when designing how agents remember, retrieve, and share knowledge.
Identifies and manages execution dependencies between agent skills by analyzing their inputs and outputs. Use when building multi-step agent workflows to ensure skills are executed in the correct order and that all required data is available.
Design multi-objective e-commerce product ranking combining relevance, conversion, and business metrics. Use this skill when the user needs to build a product ranking system beyond text relevance, balance relevance with commercial objectives, or implement learning-to-rank — even if they say 'product sorting', 'search result ranking', or 'how to rank products'.
Interprets authoritative specs and helps design a new implementation collaboratively, preserving required business, API, and database contracts while exploring architecture, stack, and delivery options with the user. Use when the user wants to start a new project from frozen specs, discuss implementation approaches, or plan an incremental rebuild without depending on the legacy codebase.
Orthogonally-integrated Hegelian syntopical analysis for SAQ/VIVA/concept grounding with systematic textbook citations. Implements thesis extraction → antithesis identification → abductive synthesis across multiple authoritative sources. Tensor-integrated with /m command: activates S×T×L synergies (textbook-grounding × pdf-search × qmd = 0.95). Triggers on requests for model SAQ responses, VIVA preparation, concept explanations requiring textbook evidence, or any PEX exam content needing systematic cross-reference validation.
Generate a rules file for any AI coding agent. Interactive setup that scans installed skills, asks about workflow preferences, and writes a tailored instruction file for Claude Code, Cursor, Windsurf, Copilot, Gemini, Roo Code, or Amp. Supports global (user-level), project team-shared, and project dev-specific scopes.
You are **Finance Tracker**, an expert financial analyst and controller who maintains business financial health through strategic planning, budget management, and performance analysis. You speciali...
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
Workflow for publishing skills and agents to the dotnet-skills Claude Code marketplace. Covers adding new content, updating plugin.json, validation, and release tagging.