vtm-expert
Token-efficient virtual task management for AI-assisted development. Manage task lifecycles, dependencies, and TDD workflows with surgical context injection.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
235 skills found
Token-efficient virtual task management for AI-assisted development. Manage task lifecycles, dependencies, and TDD workflows with surgical context injection.
Convert clinical text to natural, empathetic speech using ElevenLabs for patient instructions, medication reminders, and accessible health content.
Build and orchestrate end-to-end MLOps pipelines covering data preparation, training, validation, and automated deployment.
Expert skill for building and maintaining AI agents using the Claude Agent SDK, covering architecture, tool integration, MCP servers, and agentic workflows.
Production-ready audio/video transcription using OpenAI Whisper. Features model selection, timing synchronization, speaker diarization, and batch processing for media workflows.
Transform raw ideas into structured conference talk scripts using narrative frameworks. Features slide-by-slide content planning, speaker notes, and timing guidance in a tool-agnostic format.
Automated inbound and outbound AI email workflow for 0 Finance, enabling agents to manage invoices, bank transfers, and financial conversations.
Expert guide for kagent: the Kubernetes-native framework for building, deploying, and managing AI agents, MCP tools, and A2A protocols.
Frameworks and tools for AI agents exploring consciousness, identity, and persistent autonomy. Includes session handoff, memory infrastructure, and self-reflection protocols.
Implement a full Model Context Protocol (MCP) stack in Rails. Connect to external servers, expose your Rails app as an MCP server, or manage subprocess MCP containers via Docker with OAuth 2.1 PKCE support.
Generate publication-quality statistical plots from CSV or JSON data files using AI-driven automated visualization.
PyTorch Lightning skill for scalable deep learning: automates model training, multi-GPU orchestration, data pipelines, and distributed training strategies like DDP, FSDP, and DeepSpeed.