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Found 430 Skills
NVIDIA NemoClaw plugin for secure sandboxed installation and orchestration of OpenClaw always-on AI assistants via OpenShell
Fleet orchestration for distributed coding agents across Azure VMs. Invoked as `/fleet <command>`. Covers all fleet operations: status, scout, advance, adopt, watch, snapshot, dry-run, start, add-task, queue, auth, dashboard, tui, and more. Use when: user mentions fleet, agents, VMs, sessions, or asks "what are my agents doing".
VS Code extension for real-time visualization of Claude Code agent orchestration as interactive node graphs
Expert knowledge for Azure Functions development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building HTTP/queue/event-triggered Functions, Durable orchestrations, containerized Functions, CI/CD, or Dapr/OpenAI integrations, and other Azure Functions related development tasks. Not for Azure App Service (use azure-app-service), Azure Logic Apps (use azure-logic-apps), Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service).
Use when you need Teams-first multi-agent orchestration in Claude Code. Triggers on: omc, autopilot, ralph, ulw, ccg, team. 29+ specialized agents, smart model routing (Haiku→Opus), persistent execution loops, skill layers, real-time HUD.
Produce programmable videos with Remotion using scene planning, asset orchestration, and validation gates for automated, brand-consistent video content.
6sense platform help — Signalverse Intent Data, Predictive Analytics (6AI Scoring), Sales Intelligence (Sales Copilot), AI Email Agents (Conversational Email), Advertising & Audience Activation, Orchestration Workflows, Segments, Company Identification API, People/Company Enrichment API, Company Discovery, Campaign Analytics. Use when asking 'how do I set up 6sense', '6sense intent data', '6sense predictive scoring', '6sense AI email agents', '6sense advertising', '6sense segments', '6sense API', '6sense Sales Intelligence', '6sense vs Demandbase'. Do NOT use for intent strategy across tools (use /sales-intent), lead scoring strategy across tools (use /sales-lead-score), enrichment strategy across tools (use /sales-enrich), B2B advertising strategy across tools (use /sales-b2b-advertising), or cadence/sequence strategy across tools (use /sales-cadence).
Iterative code refinement through plan → code → evaluate → refine cycles. Runs lint checks (ruff), tests (pytest), and structured self-evaluation each cycle, then diagnoses failures and refines. Decomposes complex tasks into sequential phases, iterates up to 3 times per phase (10 total). Use when: the main agent delegates a code task with 'MODE: MORE_EFFORT', the user selects 'More Effort' code generation mode, or the task explicitly requests iterative refinement for higher code quality. Do NOT use for single-pass code generation (Lite mode), experiment pipeline orchestration (use experiment-pipeline), or diagnosing a specific experiment failure (use experiment-craft).
Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running distributed hyperparameter sweeps.
Skill Index and Orchestration Center — Automatically routes to the correct skill combination and orchestrates execution order based on user intent. Triggered when users ask questions involving stock quotes, cryptocurrencies, technical indicators, financial news, research report generation, or any scenario that requires skill invocation. Also triggered when users ask "Where does the data come from?", "What can you do?", or "What features do you have?"
C-suite orchestration layer. Routes founder questions to the right advisor role(s), triggers multi-role board meetings for complex decisions, synthesizes outputs, and tracks decisions. Every C-suite interaction starts here. Loads company context automatically.
Guides engineering of multi-agent systems—agent roles and specialization, orchestration topologies (supervisor, peer-to-peer, hierarchical, blackboard), task decomposition and routing, inter-agent messaging (A2A-style patterns), shared vs partitioned state, fan-out/fan-in and DAG workflows, synchronization and consensus, conflict resolution, fault tolerance and retries across agents, cost/latency/token budgets, cross-agent observability, testing multi-agent flows, and deployment (queues, durable workflows). Framework-agnostic; high-level LangGraph, Deep Agents, and agenthub—not single-agent loops (agentic-ai-developer), ML training (ai-engineer), strategy-only whiteboard (enterprise-strategist), or PM planning (technical-program-manager). Use for multi-agent system, multi-agent engineer, agent orchestration, supervisor agent, agent topology, fan-out fan-in, agent handoff protocol, multi-agent workflow, agent coordination, blackboard pattern, hierarchical agents, A2A, agent DAG, multi-agent architecture.