ML model training pipelines, hyperparameter tuning, model deployment automation, experiment tracking, and MLOps workflows
Plugin machine-learning-ops from marketplace claude-code-workflows in shotcowboystyle/ag-skills. Commands read from the repo's manifest — 11 days ago.
ml-pipeline-workflowBuild an ML training pipeline as a DAG of ingest, data validation, training, evaluation and a promotion gate that decides whether a candidate model replaces the current one. Use when creating ML pipelines, adding a promotion gate or continuous training, or automating model training and deployment wo
recsys-pipeline-architectDesign composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced X For You algorithm. Use when building any system that picks "the top K items for a (user, context)" — content feeds, search
/machine-learning-ops:ml-pipelineOrchestrate specialized agents to build a production ML pipeline from data analysis through training, deployment, and monitoring
data-scientistAnswer one analytical question with data: explore, test a hypothesis, fit and validate a model, or size an experiment, and report the result with its uncertainty. Use when a question needs statistics or a predictive model rather than a production pipeline.
ml-engineerTake one trained model or training script to production quality: serving code, feature pipeline, inference optimization, tests and monitoring hooks. Use when the work is turning a model into a reliable service or batch job.
mlops-engineerDesign or implement one piece of ML platform plumbing: a training pipeline, experiment tracking, model registry, deployment automation or monitoring, on the tools the project already uses. Use when ML work needs repeatable training, versioned models or automated promotion.
UX/UI design ops — briefs, tokens, components, screens and pages graded against live Awwwards and Mobbin references, plus Material 3/Compose, React Native, and web component design. Absorbs the former ui-design plugin.
47 skills · 39 commands · 4 agents
Image editing, batch operations, format conversion (WebP, AVIF, JPEG XL, PDF), metadata, and library organization — bucket by resolution, aspect ratio, orientation, format, capture time, and camera; dedupe near-duplicates.
28 skills · 19 commands
Drive an AI-generated video project end to end — brief, model selection, characters, script, storyboard, generation pipelines (text-to-image, image-to-video, voice, lip-sync), GPU-aware assembly, ComfyUI import/export, budgets, export — plus a curated index of agent-callable video and audio tooling.
13 skills · 11 commands · 7 agents · 3 MCP servers
Chain-of-custody evidence handling — hash, timestamp, inspect metadata, append to an immutable custody register, package as BagIt, verify, and sync to WORM or S3 Object Lock storage.
14 skills · 12 commands
Modern Python development with Python 3.12+, Django, FastAPI, async patterns, and production best practices
16 skills · 1 command · 3 agents
Work out the real baggage allowance for every segment of an itinerary, inventory what is carried by weight, solve the pack against the binding limit, price excess-baggage options, rank a leave-behind list, and render a counter card and packing list with Typst.
9 skills · 10 commands
Eval-gated LLM fine-tuning lifecycle (LoRA/QLoRA, DPO, GRPO/RLVR, vision SFT, quantized export). Use when fine-tuning an open-weights model end-to-end: building the eval harness first, selecting method and model, preparing data, training with Unsloth or TRL, gating checkpoints, and exporting GGUF/FP8.
10 skills · 2 commands · 3 agents
Multi-agent orchestration with AI SDK v5 - handoffs, routing, and coordination for any AI provider (OpenAI, Anthropic, Google)
1 skill · 3 commands · 1 agent
LLM application development, prompt engineering, and AI assistant optimization
5 skills · 3 commands · 2 agents
LLM application development, prompt engineering, and AI assistant optimization
5 skills · 3 commands · 2 agents
LLM application development, prompt engineering, and AI assistant optimization
4 skills · 3 commands · 2 agents
AI & Agents bundle — 388 curated skills (agents, ai-ml, prompt-engineering) for Claude Code, Codex & Antigravity.
200 skills
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