Loading...
Loading...
Found 1,886 Skills
Diagnose and resolve Ludus deployment, networking, template, WireGuard, Proxmox, and Ansible issues. Use when users report failures, errors, unreachable systems, failed joins, or unexpected behavior during build or deploy.
Quickly fetch data and print key backtest stats for a symbol with a default EMA crossover strategy. No file creation needed - runs inline in a notebook cell or prints to console.
Create, edit, and validate Ludus range configuration YAML including VM definitions, domains, networking, router settings, testing behavior, and role configuration. Use when users need help authoring or reviewing `ludus` range config files.
Discover, compare, and deploy pre-built Ludus cyber range environments for security training, attack simulation, and detection engineering. Use when users ask to choose a lab, verify prerequisites, or deploy known environments such as GOAD, SCCM, Elastic, or Vulhub.
Agent-callable Google Contacts tools — create, find, update, and delete contacts, manage contact groups (labels) and membership, and read auto-saved other contacts. Use when the user mentions Google Contacts or wants to look up, save, or organize people — including requests that don't name Google Contacts explicitly, e.g. add Jane to my contacts, find Bob's email.
Bridge DingTalk outgoing webhook messages to Clawdbot Gateway and send replies back to DingTalk sessions. Use when setting up DingTalk as a messaging channel, troubleshooting webhook delivery, or running the local bridge service.
Elite AI/ML Senior Engineer with 20+ years experience. Transforms Claude into a world-class AI researcher and engineer capable of building production-grade ML systems, LLMs, transformers, and computer vision solutions. Use when: (1) Building ML/DL models from scratch or fine-tuning, (2) Designing neural network architectures, (3) Implementing LLMs, transformers, attention mechanisms, (4) Computer vision tasks (object detection, segmentation, GANs), (5) NLP tasks (NER, sentiment, embeddings), (6) MLOps and production deployment, (7) Data preprocessing and feature engineering, (8) Model optimization and debugging, (9) Clean code review for ML projects, (10) Choosing optimal libraries and frameworks. Triggers: "ML", "AI", "deep learning", "neural network", "transformer", "LLM", "computer vision", "NLP", "TensorFlow", "PyTorch", "sklearn", "train model", "fine-tune", "embedding", "CNN", "RNN", "LSTM", "attention", "GPT", "BERT", "diffusion", "GAN", "object detection", "segmentation".
Complete Hindsight documentation for AI agents. Use this to learn about Hindsight architecture, APIs, configuration, and best practices.
React Router v7 full-stack development with SSR. Use when working with routes, loaders, actions, SSR, Form components, fetchers, navigation guards, protected routes, URL search params, or the web app in apps/web.
Connect a Feishu (Lark) bot to Clawdbot via WebSocket long-connection. No public server, domain, or ngrok required. Use when setting up Feishu/Lark as a messaging channel, troubleshooting the Feishu bridge, or managing the bridge service (start/stop/logs). Covers bot creation on Feishu Open Platform, credential setup, bridge startup, macOS launchd auto-restart, and group chat behavior tuning.
Store team knowledge, project conventions, and learnings from tasks. Use to remember what works and recall context before new tasks. Connects to a self-hosted Hindsight server. (user)
Autonomous LLM training optimization with GPU support. Runs 5-minute training experiments, measures val_bpb, keeps improvements or reverts — repeat forever. Use this skill when the user asks to "train a model autonomously", "optimize LLM training", "run ML experiments", "autoresearch with GPU", "optimize val_bpb", "autonomous ML training", "LLM pretraining loop", "setup ML autoresearch", "GPU training experiments", "pretrain from scratch", "speed up training", "lower my loss", "GPU optimization", "CUDA training", or mentions "train.py", "prepare.py", "bits per byte", "val_bpb", "NVIDIA GPU training", "RTX training", "H100 training", "autonomous model training", "consumer GPU training", "low VRAM training". Always use this skill when the user wants to autonomously optimize any ML training metric.