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Found 306 Skills
Explains operational tasks after the quickstart: listing sandboxes, status and health checks, logs, diagnostics, port forwards, multiple sandboxes, credential reset, rebuilds, network presets, upgrades, and uninstall. Trigger keywords - manage nemoclaw sandboxes, nemoclaw status, nemoclaw list, nemoclaw dashboard port, nemoclaw rebuild, nemoclaw upgrade sandboxes, nemoclaw uninstall, sandbox mutability, sandbox runtime configuration, sandbox rebuild, nemoclaw backup, nemoclaw restore, workspace backup, openshell sandbox download upload, nemoclaw messaging channels, nemoclaw telegram, nemoclaw discord, nemoclaw slack, nemoclaw whatsapp, openshell channel messaging, nemoclaw workspace files, soul.md, user.md, identity.md, agents.md, sandbox persistence.
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when: langgraph, langchain agent, stateful agent, agent graph, react agent.
Persistent, budgeted, DAG-ordered runner for parallel `claude -p` or `codex exec` workers in tmux. Use ONLY when you need persistence across sessions, per-worker budget caps, dependency ordering, or mixed models/providers per worker. For ad-hoc parallel sub-agents inside a live conversation, use Claude Code's built-in Agent tool instead.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any Transformers classifier), and SAM/SAM2 segmentation using Hugging Face Transformers on Hugging Face Jobs cloud GPUs. Covers COCO-format dataset preparation, Albumentations augmentation, mAP/mAR evaluation, accuracy metrics, SAM segmentation with bbox/point prompts, DiceCE loss, hardware selection, cost estimation, Trackio monitoring, and Hub persistence. Use when users mention training object detection, image classification, SAM, SAM2, segmentation, image matting, DETR, D-FINE, RT-DETR, ViT, timm, MobileNet, ResNet, bounding box models, or fine-tuning vision models on Hugging Face Jobs.
Guide for creating MCP servers that enhance LLM reasoning through structured processes, persistence, and workflow guidance. Use when building MCP servers for structured thinking, journaling, memory systems, or other cognitive enhancement patterns.
Implement and configure the Syncfusion Angular Gantt Chart component (ejs-gantt, GanttModule). Use this when building Angular applications with Gantt chart functionality, task scheduling, dependencies, or resource management. Covers component setup, task dependencies, taskbar editing, critical path analysis, resource allocation, timeline configuration, filtering, sorting, export, undo/redo, state persistence, and localization.
Fully autonomous epic execution. Runs until ALL children are CLOSED. Local mode uses /swarm with runtime-native spawning (Codex sub-agents or Claude teams). Distributed mode uses /swarm --mode=distributed (tmux + Agent Mail) for persistence and coordination. NO human prompts, NO stopping.
This skill provides comprehensive knowledge for building applications with Cloudflare Sandboxes SDK, which enables secure, isolated code execution in full Linux containers at the edge. It should be used when executing untrusted code, running Python/Node.js scripts, performing git operations, building AI code execution systems, creating interactive development environments, or implementing CI/CD workflows that require full OS capabilities. Use when: Setting up Cloudflare Sandboxes, executing Python/Node.js code safely, managing stateful development environments, implementing AI code interpreters, running shell commands in isolation, handling git repositories programmatically, building chat-based coding agents, creating temporary build environments, processing files with system tools (ffmpeg, imagemagick, etc.), or when encountering issues with container lifecycle, session management, or state persistence. Keywords: cloudflare sandbox, container execution, code execution, isolated environment, durable objects, linux container, python execution, node execution, git operations, code interpreter, AI agents, session management, ephemeral container, workspace, sandbox SDK, @cloudflare/sandbox, exec(), getSandbox(), runCode(), gitCheckout(), ubuntu container
Xcode project setup, SwiftData persistence, testing, debugging, profiling, and app distribution for iOS development. This skill should be used when setting up Xcode projects, working with SwiftData models and queries, writing Swift tests, debugging with breakpoints, profiling with Instruments, distributing via TestFlight, or building for visionOS and ML features.
Expert blueprint for scene loading, transitions, async (background) loading, instance management, and caching. Covers fade transitions, loading screens, dynamic spawning, and scene persistence. Use when implementing level changes OR dynamic content loading. Keywords scene, loading, transition, async, ResourceLoader, change_scene, preload, PackedScene, fade.
Use when a migration is already known to stay on the LangGraph orchestration side, including stages, routing, checkpoints, interrupts, persistence, streaming, and subgraph boundaries.