ML Ops
Machine learning operations
google-adk-python
by vibery-studio
Build AI agents with Google's Agent Development Kit (ADK) Python - an open-source toolkit for building, evaluating, and deploying AI agents. Features LlmAgent, workflow agents (sequential, parallel, loop), tool integration, multi-agent systems, and deployment to Vertex AI or Cloud Run.
spice-ai
by spiceai
Add AI and LLM capabilities to Spice — chat completions, text-to-SQL (NSQL), tool use, memory, and model routing. Use when configuring language models, enabling tools (SQL, search, MCP, web search), setting up NSQL, adding conversational memory, configuring model fallback or load balancing, or using the OpenAI-compatible API.
kubeflow-trainer
by tylertitsworth
"Kubeflow Trainer v2 — TrainJob CRD, Training Runtimes, Python SDK, JobSet, multi-framework support. Use when orchestrating distributed training on K8s. NOT for inference or Ray Train."
chunking-strategies
by latestaiagents
Optimize document chunking for RAG performance and retrieval quality. Use this skill when splitting documents, choosing chunk sizes, implementing semantic chunking, or improving RAG retrieval accuracy. Activate when: chunking, split documents, chunk size, text splitting, document processing, RAG performance, semantic chunking, overlap.
axolotl
by tylertitsworth
"Axolotl — config-driven LLM fine-tuning framework. YAML-based SFT, instruction tuning, chat fine-tuning, DPO/IPO/KTO/ORPO preference optimization, GRPO reinforcement learning, reward modeling, LoRA/QLoRA, full fine-tuning with FSDP/DeepSpeed multi-GPU, N-D Parallelism (TP+CP+FSDP composition), multimodal VLM training, text diffusion training, QAT with NVFP4, sample packing, Flash Attention, dataset preprocessing, and checkpoint management. Use when fine-tuning or post-training LLMs with Axolotl."
spice-models
by spiceai
Configure AI/LLM model providers in Spice (OpenAI, Anthropic, Azure, Google, xAI, Bedrock, Perplexity, Databricks, local models). Use when asked to "add a model", "configure LLM", "set up OpenAI", "add language model", "enable chat completions", "serve local model", "add AI gateway", or "configure system prompt".
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".
kueue
by tylertitsworth
"Kueue — ClusterQueues, ResourceFlavors, fair sharing, preemption, TAS, MultiKueue. Use when managing batch workload queuing and GPU quotas on K8s. NOT for Volcano."
llm-integration
by liauw-media
"Use when integrating LLM APIs into applications. Covers API patterns, prompt templates, streaming, error handling, cost optimization, and provider abstraction. Apply when building chat interfaces, completion endpoints, or AI-powered features."
keda
by tylertitsworth
"KEDA — ScaledObject/ScaledJob CRDs, 60+ triggers, scale-to-zero for GPU inference, TriggerAuthentication. Use when configuring event-driven pod autoscaling. NOT for HPA basics or Kueue."
modelmix
by clasen
Instructions for using the ModelMix Node.js library to interact with multiple AI LLM providers through a unified interface. Use when writing code that calls AI models (OpenAI, Anthropic, Google, Groq, Perplexity, Grok, MiniMax, Fireworks, Together, Lambda, Cerebras, OpenRouter, Ollama, LM Studio), chaining models with fallback, getting structured JSON from LLMs, adding MCP tools, streaming responses, managing multi-provider AI workflows, round-robin load balancing, or rate limiting API requests in Node.js. Also use when the user mentions "modelmix", "ModelMix", asks to "call an LLM", "query a model", "add AI to my app", or wants to integrate any supported provider.
jackyshen-create-invitation-email
by mebusw
Generate compelling invitation emails for training programs, workshops, or events. Use when user asks to "write class invitation email", "create training invitation", "generate mass email for training", or mentions "course promotion email".
vargdown
by wassname
Verified Argdown maps with credences and source quotes.
jackyshen-design-quiz
by mebusw
Generate quiz questions, assessments, and knowledge checks for training programs. Use when user asks to "create quiz questions", "generate assessment", "make test paper", or similar requests for training evaluations after class.
swiftui-development
by ProjAnvil
专注于使用 modern SwiftUI 构建用户界面，涵盖 NavigationStack, Observation 框架和 SwiftData 集成。
hugging-face-evaluation-manager
by Nymbo
Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.
renaissance-statistical-arbitrage
by copyleftdev
Build trading systems in the style of Renaissance Technologies, the most successful quantitative hedge fund in history. Emphasizes statistical arbitrage, signal processing, and rigorous scientific methodology. Use when developing alpha research, signal extraction, or systematic trading strategies.
dbt-expert
by timequity
dbt best practices for models, tests, documentation, and project organization.
maciver-hypothesis-testing
by copyleftdev
Test software in the style of David MacIver, creator of Hypothesis. Emphasizes sophisticated shrinking, example databases, stateful testing, and practical property-based testing in Python. Use when testing Python code with complex data structures, APIs, or stateful systems.
two-sigma-ml-at-scale
by copyleftdev
Build trading systems in the style of Two Sigma, the systematic investment manager pioneering machine learning at scale. Emphasizes alternative data, distributed computing, feature engineering, and rigorous ML infrastructure. Use when building ML pipelines for alpha research, feature stores, or large-scale backtesting systems.
fowler
by copyleftdev
Design systems using Martin Fowler's principles of refactoring, continuous integration, and patterns of enterprise application architecture. Emphasizes clean code, evolution over revolution, and writing code for humans first. Use when designing enterprise systems, planning refactors, or establishing engineering culture.
nano-banana
by Nymbo
Generate and edit images using the Gemini API (Nano Banana). Use this skill when creating images from text prompts, editing existing images, applying style transfers, generating logos with text, creating stickers, product mockups, or any image generation/manipulation task. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images.
gemini-api
by diskd-ai
Google Gemini API integration for building AI-powered applications. Use when working with Google's Gemini API, Python SDK (google-genai), TypeScript SDK (@google/genai), multimodal inputs (image, video, audio, PDF), thinking/reasoning features, streaming responses, structured outputs with JSON schemas, multi-turn chat, system instructions, image generation (Nano Banana), video generation (Veo), music generation (Lyria), embeddings, document/PDF processing, or any Gemini API integration task. Triggers on mentions of Gemini, Gemini 3, Gemini 2.5, Google AI, Nano Banana, Veo, Lyria, google-genai, or @google/genai SDK usage.