dongzhuoyao
@dongzhuoyao
Public Skills
slurm-gpu-training
by dongzhuoyao
Use when running ML training on HPC clusters with Slurm, including job submission, environment setup, monitoring, and failure triage. Applies to any GPU training workload on Slurm-managed clusters. Triggers: "sbatch", "srun", "Slurm", "SBATCH", "job submission", "HPC", "cluster", "walltime", "squeue"
fail-fast-ml-engineering
by dongzhuoyao
Use when designing ML training pipelines, data loaders, or inference systems. Enforces engineering discipline — no silent fallbacks, explicit errors on critical paths, config as single source of truth. Triggers: "silent failure", "fallback", "preflight", "assertion", "error handling", "fail fast", "config truth"
wandb-experiment-tracking
by dongzhuoyao
Use when integrating W&B experiment tracking into ML training pipelines, including logging strategy, run configuration, and online/offline mode management. Triggers: "W&B", "wandb", "weights and biases", "experiment logging", "wandb.log", "wandb.init", "training dashboard"
ios-swiftui-app
by dongzhuoyao
Use when building iOS apps with SwiftUI, UIKit bridging, SSH terminal integration, or voice input pipelines. Applies to Swift 5.9+/iOS 17+ projects using SPM, xcodegen, Citadel, SwiftTerm, or AVFoundation. Triggers: "SwiftUI", "UIViewRepresentable", "ObservableObject", "@MainActor", "xcodegen", "SwiftTerm", "Citadel", "SSH", "STT", "AVAudioEngine", "iOS app", "terminal emulator", "voice input"
vercel-cost-optimization
by dongzhuoyao
Use when deploying Next.js apps to Vercel and costs are high, or when setting up a new Vercel project. Covers ISR-breaking patterns, function constraints, caching, Fluid Compute, build optimization. Triggers: "Vercel bill", "Vercel cost", "ISR broken", "dynamic rendering", "cache-control private", "x-vercel-cache MISS", "function invocations", "Fluid Compute", "GB-hours", "s-maxage", "stale-while-revalidate", "maxDuration", "build minutes"
agents-md-writing
by dongzhuoyao
Use when writing or improving CLAUDE.md, AGENTS.md, GEMINI.md, or any agent instruction file. Covers section structure, memory patterns, workflow rules, and anti-patterns. Triggers: "CLAUDE.md", "AGENTS.md", "agent instructions", "project memory", "MEMORY.md", "instruction file"
github-cli
by dongzhuoyao
Use when interacting with GitHub repos, PRs, issues, releases, or API data. Covers gh CLI usage patterns, authentication, and common queries. Triggers: "gh", "github", "pull request", "PR", "issue", "gh api", "gh pr", "gh issue", "github release"
claude-code-config
by dongzhuoyao
Use when setting up Claude Code on a new machine, configuring permissions, statusline, or plugins. Contains the standard settings.json and statusline script.
tmux
by dongzhuoyao
Use when setting up tmux on a new machine, looking up key bindings, debugging terminal colors, or restoring tmux dotfiles. Triggers: "tmux", "terminal multiplexer", "tmux.conf", "pane", "window split", "copy mode", "prefix key"
zsh
by dongzhuoyao
Use when setting up zsh and Oh My Zsh on a new machine, configuring shell plugins, PATH, or conda initialization. Triggers: "zsh", "zshrc", "Oh My Zsh", "shell config", "dotfiles", "conda init", "PATH"
ml-ablation-design
by dongzhuoyao
Use when designing ablation studies to compare model components, loss functions, or architectural choices. Covers synthetic data experiments, variant loops, production metrics, and W&B grouping. Triggers: "ablation", "ablation study", "variant comparison", "controlled experiment", "synthetic data experiment"
hydra-experiment-config
by dongzhuoyao
Use when structuring ML experiment configs with Hydra, adding new config groups, or debugging config resolution. Applies to any project using Hydra for hyperparameter management. Triggers: "Hydra", "config", "yaml config", "OmegaConf", "config groups", "defaults list", "config override"
gpu-training-acceleration
by dongzhuoyao
Use when optimizing PyTorch training speed or memory on CUDA GPUs — global flags, torch.compile, fused optimizers, mixed precision, gradient checkpointing, kernel fusion, memory layout, or latent-space training. Applies to any PyTorch training workload. Triggers: "torch.compile", "TF32", "fused optimizer", "mixed precision", "bf16", "fp16", "gradient checkpointing", "Triton kernel", "CUDA flags", "GPU slow", "GPU memory"
lumi-supercomputer
by dongzhuoyao
Use when running workloads on LUMI supercomputer, including GPU job submission, PyTorch with ROCm/AMD MI250X, container workflows, and LUMI-specific Slurm configuration. Triggers: "LUMI", "MI250X", "ROCm", "AMD GPU", "CSC", "LUMI-G"