ML Ops
Machine learning operations
Article Pipeline
by 0xAxiom
Ratio: 5:2 (1250x500px) for X Articles
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"
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"
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"
megaeth-developer
by Demerzels-lab
End-to-end MegaETH development playbook (Feb 2026). Covers wallet operations, token swaps (Kyber Network), eth_sendRawTransactionSync (EIP-7966) for instant receipts, JSON-RPC batching, real-time mini-block subscriptions, storage-aware contract patterns (Solady RedBlackTreeLib), MegaEVM gas model, WebSocket keepalive, bridging from Ethereum, and debugging with mega-evme. Use when building on MegaETH, managing wallets, sending transactions, or deploying contracts.
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"
garmin-connect
by eddmann
Query Garmin Connect fitness and health data including activities, athlete stats, sleep, heart rate, stress, and body battery. Use when the user asks about Garmin data, workouts, training, or health metrics.
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"
vercel-ai-sdk
by wsimmonds
Guide for Vercel AI SDK v5 implementation patterns including generateText, streamText, useChat hook, tool calling, embeddings, and MCP integration. Use when implementing AI chat interfaces, streaming responses, tool/function calling, text embeddings, or working with convertToModelMessages and toUIMessageStreamResponse. Activates for AI SDK integration, useChat hook usage, message streaming, or tool calling tasks.
paper-reading
by yishuai778
"Read research papers and turn them into clear, decision-oriented notes, comparisons, and implementation takeaways. Use this skill whenever someone wants to read, summarize, analyze, compare, or review papers; build a literature overview; extract methods, datasets, benchmarks, or limitations; judge whether a paper is worth reproducing; or turn papers into actionable notes. Also trigger on requests like '读这篇论文', '帮我总结 paper', '精读这篇', '对比这几篇论文', '做文献综述', '提炼贡献/局限/实验设置', '这篇值不值得复现', or '把论文讲明白'."
codex-config
by outfitter-dev
This skill should be used when configuring Codex CLI, setting up profiles, or when "config.toml", "sandbox mode", "Codex config", or "approval policy" are mentioned.
r3f-loaders
by EnzeD
React Three Fiber asset loading - useGLTF, useLoader, Suspense patterns, preloading. Use when loading 3D models, textures, HDR environments, or managing loading states.
endurance-coach
by shiv19
Create personalized triathlon, marathon, and ultra-endurance training plans. Use when athletes ask for training plans, workout schedules, race preparation, or coaching advice. Can sync with Strava to analyze training history, or work from manually provided fitness data. Generates periodized plans with sport-specific workouts, zones, and race-day strategies.
Google ADK Python Skill
by zircote
Remember: ADK treats agent development like traditional software engineering - use version control, write tests, and follow engineering best practices.
model-council
by michaelboeding
This skill should be used when the user asks for "model council", "multi-model", "compare models", "ask multiple AIs", "consensus across models", "run on different models", or wants to get solutions from multiple AI providers (Claude, GPT, Gemini, Grok) and compare results. Orchestrates parallel execution across AI models/CLIs and synthesizes the best answer.
marginaleffects
by vincentarelbundock
Manual for the marginaleffects R and Python package, and guide to the book "Model to Meaning". Use when users ask about predictions, comparisons, slopes, marginal effects, average treatment effects (ATE/ATT/CATE), hypothesis testing, contrasts, counterfactuals, risk ratios, odds ratios, causal inference with G-computation, or need help with marginaleffects functions like predictions(), comparisons(), slopes(), hypotheses(), datagrid(), avg_predictions(), avg_comparisons(), avg_slopes(), or plot functions.
domain-model-boundaries-mapper
by patricio0312rev
Identifies domain modules, ownership boundaries, dependencies, and interfaces using Domain-Driven Design principles. Provides domain maps, bounded contexts, refactor recommendations. Use for "DDD", "domain modeling", "bounded contexts", or "service boundaries".
ollama-optimizer
by Montimage
Optimize Ollama configuration for maximum performance on the current machine. Use when asked to "optimize Ollama", "configure Ollama", "speed up Ollama", "tune LLM performance", "setup local LLM", "fix Ollama performance", "Ollama running slow", or when users want to maximize inference speed, reduce memory usage, or select appropriate models for their hardware. Analyzes system hardware (GPU, RAM, CPU) and provides tailored recommendations.
tinygrad
by av
Deep learning framework development with tinygrad - a minimal tensor library with autograd, JIT compilation, and multi-device support. Use when writing neural networks, training models, implementing tensor operations, working with UOps/PatternMatcher for graph transformations, or contributing to tinygrad internals. Triggers on tinygrad imports, Tensor operations, nn modules, optimizer usage, schedule/codegen work, or device backends.
laravel-migrations-and-factories
by noartem
Safe database change patterns; when to modify vs add migrations; always pair models with migrations and factories; seeding guidance
run-llms
by av
Guide for setting up and running local LLMs using Harbor. Use when user wants to run LLMs locally, set up Ollama, Open WebUI, llama.cpp, vLLM, or similar local AI services. Covers full setup from Docker prerequisites through running models, configuration, profiles, tunnels, and advanced features.
laravel-policies-and-authorization
by noartem
Enforce access via Policies and Gates; use authorize() and authorizeResource() to standardize controller protections
clip
by ovachiever
OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.