ML Ops
Machine learning operations
mcp-memory-gateway
by IgorGanapolsky
The Agentic Feedback Studio & Veto Layer. Persistent agent memory, high-density context packs, and Agentic Guardrails (V2V) for Claude Code, Codex, and Gemini.
ai-ml-development
by travisjneuman
AI and machine learning development with PyTorch, TensorFlow, and LLM integration. Use when building ML models, training pipelines, fine-tuning LLMs, or implementing AI features.
replicate
by replicate
Discover, compare, and run AI models using Replicate's API
seedance-storyboard
by elementsix
将任何想法转换成即梦 Seedance 2.0 专业分镜提示词。当用户想要生成视频、制作短视频、创作分镜、使用 Seedance/即梦/剪映 AI 视频时调用。
Gym & Training Expert
by frankxai
Apply cutting-edge exercise science from 2025 research on hypertrophy, progressive overload, biomechanics, and evidence-based training protocols for optimal strength and muscle development
project-development
by Svenja-dev
Design and build LLM-powered projects from ideation through deployment. Use when starting new agent projects, choosing between LLM and traditional approaches, or structuring batch processing pipelines.
fairchem
by jkitchin
Expert guidance for Meta's FAIRChem library - machine learning methods for materials science and quantum chemistry using pretrained UMA models with ASE integration for fast, accurate predictions
design-of-experiments
by jkitchin
Expert guidance for Design of Experiments (DOE) in Python - interactive goal-driven design selection, classical DOE (factorial, response surface, screening), Bayesian optimization with Gaussian processes, model-driven optimal designs, active learning, and sequential experimentation; includes pyDOE3, pycse, GPyOpt, scikit-optimize, statsmodels
python-regression-statistics
by jkitchin
Expert guidance for regression analysis, statistical modeling, and outlier detection in Python using statsmodels, scikit-learn, scipy, and PyOD - includes model diagnostics, assumption checking, robust methods, and comprehensive outlier detection strategies
idaes
by jkitchin
Comprehensive guidance for using IDAES (Institute for the Design of Advanced Energy Systems) for process systems engineering. Covers flowsheet modeling, property packages, unit models, optimization, scaling, initialization, and diagnostics. Use when working with chemical process simulations, energy systems modeling, power plant design, material and energy balances, or process optimization. Triggers include 'IDAES', 'flowsheet', 'process model', 'unit operation', 'process optimization', 'property package', 'energy systems', or process engineering tasks.
threat-model-generation
by Factory-AI
Generate a STRIDE-based security threat model for a repository. Use when setting up security monitoring, after architecture changes, or for security audits.
model-evaluation-benchmark
by rysweet
Automated reproduction of comprehensive model evaluation benchmarks following the Benchmark Suite V3. Auto-activates for model benchmarking, comparison evaluation, or performance testing between AI models.
agent-sdk
by rysweet
Comprehensive knowledge of Claude Agent SDK architecture, tools, hooks, skills, and production patterns. Auto-activates for agent building, SDK integration, tool design, and MCP server tasks.
text-to-speech
by sarvamai
Convert text to natural speech using Sarvam AI's Bulbul model. Use when the user needs to generate audio from text, create voiceovers, build voice interfaces, or synthesize Indian language speech. Supports 11 Indian languages with multiple voices, controllable pitch/pace/loudness, and real-time streaming. Returns base64-encoded audio.
ai-mlops
by vasilyu1983
Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).
marketing-leads-generation
by vasilyu1983
Use when building or fixing B2B pipeline. Revenue-aligned demand generation with lead types, funnel design, conversion paths, scoring/routing, attribution, ABS motions, and compliance.
ai-llm-inference
by vasilyu1983
"Operational patterns for LLM inference: latency budgeting, tail-latency control, caching, batching/scheduling, quantization/compression, parallelism, and reliable serving at scale. Emphasizes production-grade performance, cost control, and observability."
ai-llm
by vasilyu1983
Production LLM engineering skill. Covers strategy selection (prompting vs RAG vs fine-tuning), dataset design, PEFT/LoRA, evaluation workflows, deployment handoff to inference serving, and lifecycle operations with cost/safety controls.
ai-ml-data-science
by vasilyu1983
"End-to-end data science and ML engineering workflows: problem framing, data/EDA, feature engineering (feature stores), modelling, evaluation/reporting, plus SQL transformations with SQLMesh. Use for dataset exploration, feature design, model selection, metrics and slice analysis, model cards/eval reports, experiment reproducibility, and production handoff (monitoring and retraining)."
ai-ml-timeseries
by vasilyu1983
"Operational patterns, templates, and decision rules for time series forecasting (modern best practices): tree-based methods (LightGBM), deep learning (Transformers, RNNs), future-guided learning, temporal validation, feature engineering, generative TS (Chronos), and production deployment. Emphasizes explainability, long-term dependency handling, and adaptive forecasting."
visionos-design-guidelines
by dirnbauer
Apple Human Interface Guidelines for Apple Vision Pro. Use when building spatial computing apps, implementing eye/hand input, or designing immersive experiences. Triggers on tasks involving visionOS, RealityKit, spatial UI, or mixed reality.
model-router
by nguyenthienthanh
"Automatically select optimal Claude model (Haiku/Sonnet/Opus) based on task complexity to reduce costs while maintaining quality."
ai-pricing
by chadboyda
"When the user wants to price an AI product, choose a charge metric, design pricing tiers, or optimize margins. Also use when the user mentions 'AI pricing,' 'usage-based pricing,' 'consumption pricing,' 'outcome pricing,' 'BYOK,' 'bring your own key,' 'per-seat pricing,' 'pricing tiers,' 'AI margins,' 'cost per token,' or 'pricing model.' This skill covers pricing strategy, packaging, and margin management for AI-native products."
MLOps Industrialization
by fmind
Guide to transform prototypes into robust, distributable Python packages using the src layout, hybrid paradigm, and strict configuration management.