ML Ops
Machine learning operations
jackyshen-design-workshop-outline
by mebusw
Use when user asks to "generate workshop outline", "create training agenda", "design course structure", "build workshop schedule", or requests help planning training sessions. Applies MECE structure, TfBR design (4Cs), and VAK-inclusive learning.
nuxt-layers
by leeovery
Working with Nuxt layers (base, nuxt-ui, x-ui) that provide shared functionality. Use when understanding layer architecture, importing from layers, extending layer functionality, or creating new layers.
gitlab-ci
by grandcamel
"GitLab CI/CD pipeline operations. ALWAYS use this skill when user wants to: (1) view pipeline status, (2) run/trigger pipelines, (3) view/retry jobs, (4) trace job logs, (5) download artifacts, (6) lint CI config."
time-series
by pluginagentmarketplace
ARIMA, SARIMA, Prophet, trend analysis, seasonality detection, anomaly detection, and forecasting methods. Use for time-based predictions, demand forecasting, or temporal pattern analysis.
pyside6-qml-views
by DS-codi
Use this skill when creating QML view files, designing QML component hierarchies, building layouts, styling QML controls, creating reusable QML components, implementing QML navigation / page switching, or working with QML resources. Covers QML file structure, component patterns, Material/Controls styling, resource management, and common QML idioms for desktop applications.
context-fundamentals
by ken-cavanagh-glean
Understand the components, mechanics, and constraints of context in agent systems. Use when designing agent architectures, debugging context-related failures, or optimizing context usage.
qwen3-tts-mlx
by AGISeek
Local Qwen3-TTS speech synthesis on Apple Silicon via MLX. Use for offline narration, audiobooks, video voiceovers, and multilingual TTS.
machine-learning
by pluginagentmarketplace
Supervised/unsupervised learning, model selection, evaluation, and scikit-learn. Use for building classification, regression, or clustering models.
token-optimizer
by alexismunoz1
Practical guide to reduce token consumption, lower AI costs, and improve Claude Code performance through file organization, context management, and strategic model selection. Backed by real experiment data. Use when user mentions "optimize tokens", "reduce costs", "Claude is slow", "too many tokens", "token budget", "context window full", "organize codebase for AI", or "reduce token consumption". Do NOT use for general coding questions, debugging, or performance optimization unrelated to AI token usage.
did-core
by hairyf
W3C DID Core specification—DID/DID URL syntax, data model, core properties, verification methods, services, representations, and DID methods.
nlp-processing
by pluginagentmarketplace
Text processing, sentiment analysis, LLMs, and NLP frameworks. Use for text classification, named entity recognition, or language models.
jackyshen-list-methods
by mebusw
This skill should be used when the user asks about "McKinsey frameworks", "MECE principle", "PREP structure", "SCQA framing", "Training from Back of Room", "TfBR", "ORID facilitation", "NLP patterns", "training methodologies", "Huawei BEM/BLM/DSTE system", "facilitation techniques", "liberating structures", "Scrum/Agile", "OKR", or requests guidance on structured problem solving, participant-centered learning, or communication patterns. This skill provides foundational methodologies referenced by other skills.
jackyshen-create-opening-remarks
by mebusw
Generate engaging opening speeches, icebreakers, and introductions for workshops, training sessions, or presentations. Use when user asks for "opening remarks", "training opening", "icebreaker speech".
ai-ethics
by 89jobrien
Responsible AI development and ethical considerations. Use when evaluating
advanced-evaluation
by ken-cavanagh-glean
Master LLM-as-a-Judge evaluation techniques including direct scoring, pairwise comparison, rubric generation, and bias mitigation. Use when building evaluation systems, comparing model outputs, or establishing quality standards for AI-generated content.
nuxt-models
by leeovery
Domain model classes with automatic hydration, relations, and type casting. Use when creating models for API entities, defining relationships between models, casting properties to enums/dates, or creating value objects.
deep-learning
by pluginagentmarketplace
Neural networks, CNNs, RNNs, Transformers with TensorFlow and PyTorch. Use for image classification, NLP, sequence modeling, or complex pattern recognition.
llm-interview-coach
by llx9826
Prepare for large language model, generative AI, and LLM algorithm interviews. Use when the user wants mock interviews, study plans, question drills, answer review, or targeted prep for 大模型算法岗, LLM engineer, GenAI engineer, 算法工程师, RAG, agent, fine-tuning, inference optimization, evaluation, or model training interviews. Triggers include: "大模型面试", "算法面试", "LLM interview", "mock interview", "帮我准备大模型算法岗", "面试官会怎么问", "RAG面试", "微调面试", "推理优化面试".
pydantic
by jiatastic
Pydantic models and validation. Use when: (1) Defining schemas, (2) Validating input/output, (3) Generating JSON schema.
machine-learning
by 89jobrien
Machine learning development patterns, model training, evaluation, and
skills
by atxinsky
Create detailed implementation plan with bite-sized tasks
skills
by atxinsky
"You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores requirements and design before implementation."
reinforcement-learning
by pluginagentmarketplace
Q-learning, DQN, PPO, A3C, policy gradient methods, multi-agent systems, and Gym environments. Use for training agents, game AI, robotics, or decision-making systems.
model-optimization
by pluginagentmarketplace
Quantization, pruning, AutoML, hyperparameter tuning, and performance optimization. Use for improving model performance, reducing size, or automated ML.