Total 30,612 skills, AI & Machine Learning has 4949 skills
Showing 12 of 4949 skills
Guidance for creating standalone CLI tools that perform neural network inference by extracting PyTorch model weights and reimplementing inference in C/C++. This skill applies when tasks involve converting PyTorch models to standalone executables, extracting model weights to portable formats (JSON), implementing neural network forward passes in C/C++, or creating CLI tools that load images and run inference without Python dependencies.
Guidance for building Caffe from source and training CIFAR-10 models. This skill applies when tasks involve compiling Caffe deep learning framework, configuring Makefile.config, preparing CIFAR-10 dataset, or training CNN models with Caffe solvers. Use for legacy ML framework installation, LMDB dataset preparation, and CPU-only deep learning training tasks.
Automate Flowiseai tasks via Rube MCP (Composio). Always search tools first for current schemas.
Gemini CLI - Google's AI-powered command-line interface for building, debugging, and deploying with AI. Use when working with Gemini CLI configuration, commands, tools, extensions, hooks, skills, or MCP servers. Keywords: gemini-cli, google-ai, terminal, code-generation, workflow-automation, cli-commands, gemini-md, authentication, configuration, sandboxing, headless-mode, custom-commands, agent-skills, extensions, hooks, mcp-servers, file-system-tools, shell-commands, web-search, ide-integration.
Coordinate AI agent teams via a Kanban task board with local JSON storage. Enables multi-agent workflows with a Team Lead assigning work and Worker Agents executing tasks via heartbeat polling. Perfect for building AI agent command centers.
Automate AI ML API tasks via Rube MCP (Composio). Always search tools first for current schemas.
Deep explanation of complex code, files, or concepts. Routes to expert agents, uses structural search, generates mermaid diagrams. Triggers on: explain, deep dive, how does X work, architecture, data flow.
Generate PhD-level expert agent prompts for Claude Code. Creates comprehensive 500-1000 line agents with detailed patterns, code examples, and best practices. Triggers on: spawn agent, create agent, generate expert, new agent, agent genesis.
Improve and rewrite user prompts to reduce ambiguity and improve LLM output quality. Use when a user asks to optimize, refine, clarify, or rewrite a prompt for better results, or when the request is about prompt optimization or prompt rewriting.
Confusion Matrix Generator - Auto-activating skill for ML Training. Triggers on: confusion matrix generator, confusion matrix generator Part of the ML Training skill category.
Knowledge graph memory orchestration - entity extraction, query parsing, deduplication, and cross-reference boosting. Use when designing memory orchestration.
LangGraph workflow patterns for state management, routing, parallel execution, supervisor-worker, tool calling, checkpointing, human-in-loop, streaming, subgraphs, and functional API. Use when building LangGraph pipelines, multi-agent systems, or AI workflows.