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Vast.ai GPU Compute Workflow Architecture

vastai-reference-architecture

jeremylongshore/claude-code-plugins-plus-skills

This guide details the production-grade reference architecture for running complex GPU compute workflows on Vast.ai. It covers the foundational three-tier pattern—Orchestrator, GPU Workers, and Artifact Storage—providing blueprints for job queue management, fault-tolerant training pipelines, and robust checkpointing. Use this when designing scalable and reliable ML/AI training systems.

Volcano Engine RL Training

verl-rl-training

Orchestra-Research/AI-Research-SKILLs

Guides training large language models with Volcano Engine's verl library, covering PPO/GRPO workflows, distributed backends, multi-turn rollouts, reward configs, critic-enabled PPO, and production deployments using Ray workers.

Voice AI Engine Development

voice-ai-engine-development

sickn33/antigravity-awesome-skills

Guides building async worker pipelines for real-time conversational voice agents with streaming transcription, LLM reasoning, and interrupt-aware TTS across providers.

Workflow Orchestration for AI Agents

affaan-m/everything-claude-code

Manages and coordinates complex workflows involving multiple AI agents and tasks. It efficiently distributes work across multiple workers, handles runtime errors, and intelligently merges disparate results into a unified output, making it ideal for large-scale, distributed AI computations.

Progressive AI Literacy and ML Coach

02-ai-ml-learning

24kchengYe/human-skill-tree

This coach guides users through a progressive mastery of AI, structured across three layers: AI User (prompting), AI-Enhanced Worker (workflow integration), and AI Builder (ML foundations). It uses Socratic questioning, layered scaffolding, and spaced repetition to build genuine, transferable AI literacy, moving beyond simple copy-pasting prompts to deep conceptual understanding of models, transformers, and RAG.

Workflow Orchestration for AI Agents

Manages and coordinates complex workflows involving multiple AI agents and tasks. It efficiently distributes work across multiple workers, handles runtime errors, and intelligently merges disparate results into a unified output, making it ideal for large-scale, distributed AI computations.

Advisor Orchestrator Worker

advisor-orchestrator-worker

Shubhamsaboo/awesome-llm-apps

A three-tier model team orchestrator that decomposes oversized tasks into parallel subtasks, dispatches cheap workers in batches, gets plan review from a stronger advisor model, verifies each result, and synthesizes the final deliverable.

AgentFlow Autonomous Dev Pipeline

sickn33/agentic-awesome-skills

Turns your Kanban board (Asana, GitHub Projects, Linear) into an autonomous AI development pipeline with multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, cost tracking, and recoverable task state.

Multi-Agent Orchestration Review

review-multi-agent-orchestration

sickn33/agentic-awesome-skills

Review supervisor, swarm, planner-worker and parallel agent workflows as distributed state machines: task ownership, shared state, branch joins, retries, cancellation, context handoffs, budgets, deadlocks and human escalation before rollout.

Voice AI Engine Development

voice-ai-engine-development

sickn33/agentic-awesome-skills

Build real-time conversational AI voice engines using async worker pipelines, streaming transcription, LLM agents, and TTS synthesis with interrupt handling and multi-provider support. Ideal for creating voice assistants, customer service agents, and voice-enabled applications that process streaming audio and integrate multiple AI providers effectively.

Math Proof Siege

anthropics/claude-plugins-official

Automated multi-agent system to solve hard mathematics problems through iterative rounds of judging, worker queries, and verification, producing a proof.md with clear status.

AI Agent Security Hardening

agent-security-hardening

Security hardening guidance for AI agent frameworks processing untrusted content, invoking tools, writing files, managing identifiers, or handling credentials. Use when building or reviewing agent runtimes, autonomous workers, tool gateways, memory services, or multi-tenant deployments.

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