ML Ops
Machine learning operations
ml-expert
by personamanagmentlayer
Expert-level machine learning, deep learning, model training, and MLOps
databricks-expert
by personamanagmentlayer
Expert-level Databricks platform, Apache Spark, Delta Lake, MLflow, notebooks, and cluster management
competitor-analysis
by assimovt
Analyze competitive landscape with feature matrices, positioning maps, and strategic gap analysis. Use when asked to analyze competitors, map the competitive landscape, find differentiation, or evaluate alternatives to a product.
sequelize-patterns
by joneqian
Sequelize Node.js ORM for SQL databases. Use for database models, migrations, associations, queries, transactions, validations, hooks, and working with PostgreSQL, MySQL, MariaDB, SQLite, SQL Server.
reinforcement-learning
by Aznatkoiny
Reinforcement Learning best practices for Python using modern libraries (Stable-Baselines3, RLlib, Gymnasium). Use when: - Implementing RL algorithms (PPO, SAC, DQN, TD3, A2C) - Creating custom Gymnasium environments - Training, debugging, or evaluating RL agents - Setting up hyperparameter tuning for RL - Deploying RL models to production
deep-learning
by Aznatkoiny
"Comprehensive guide for Deep Learning with Keras 3 (Multi-Backend: JAX, TensorFlow, PyTorch). Use when building neural networks, CNNs for computer vision, RNNs/Transformers for NLP, time series forecasting, or generative models (VAEs, GANs). Covers model building (Sequential/Functional/Subclassing APIs), custom training loops, data augmentation, transfer learning, and production best practices."
consulting-frameworks
by Aznatkoiny
Core consulting thinking frameworks and methodologies for structuring business problems, communicating findings, analyzing strategy, building financial models, and designing operations. Use when any agent or command needs to apply MECE decomposition, pyramid principle, hypothesis-driven analysis, issue trees, SCR communication, Porter's Five Forces, TAM/SAM/SOM market sizing, value chain analysis, NPV/IRR decision criteria, build/buy/partner evaluation, RACI matrices, or any standard consulting framework. This skill provides procedural guidance — not just framework names, but how to apply them correctly.
openclaw-setup
by Aznatkoiny
Set up, install, configure, and deploy OpenClaw (formerly ClawdBot/MoltBot) — a personal AI assistant that runs on your own devices and connects to messaging channels. Use when users ask to "set up OpenClaw," "install ClawdBot," "install MoltBot," "deploy a personal AI assistant," "configure OpenClaw on Mac," "deploy OpenClaw to VPS," "set up OpenClaw on Hostinger," "connect OpenClaw to Telegram," "configure iMessage with OpenClaw," or any variation involving OpenClaw installation, gateway configuration, channel setup, Anthropic auth, or security hardening. Also triggers on "openclaw onboard," "openclaw doctor," "openclaw security audit," troubleshooting OpenClaw deployments, OpenClaw security, OpenClaw cost control, or ClawHub skills safety.
cpp-reinforcement-learning
by Aznatkoiny
C++ Reinforcement Learning best practices using libtorch (PyTorch C++ frontend) and modern C++17/20. Use when: - Implementing RL algorithms in C++ for performance-critical applications - Building production RL systems with libtorch - Creating replay buffers and experience storage - Optimizing RL training with GPU acceleration - Deploying RL models with ONNX Runtime
langchain-use
by NanmiCoder
LangChain 1.0 使用指南。提供 Agent、Tool、Memory、Middleware 等核心概念的快速参考。当用户需要创建 AI Agent、集成 LangChain、或解决 LangChain 相关问题时激活。
signum
by heurema
Use when the user wants contract-first development — define correctness before coding, implement against a contract, audit with multiple models, and package proof artifacts.
unifuncs-deep-search
by UniFuncs
使用 UniFuncs API 进行深度搜索，高速全面地搜索信息。当用户需要深度搜索、深搜、全面信息收集时使用。
mlops-engineer
by olehsvyrydov
Senior MLOps Engineer with 8+ years ML systems experience. Use when integrating LLM APIs (Gemini, OpenAI, Groq), building AI pipelines, managing prompts, setting up model serving, implementing AI cost optimization, or building training data pipelines.
mineru-extract
by blessonism
Use the official MinerU (mineru.net) parsing API to convert a URL (HTML pages like WeChat articles, or direct PDF/Office/image links) into clean Markdown + structured outputs. Use when web_fetch/browser can’t access or extracts messy content, and you want higher-fidelity parsing (layout/table/formula/OCR).
notebook-ai-agents-skill
by fmschulz
Create/refactor reproducible analysis notebooks with Marimo (preferred) or Jupyter (minimal support). Use for interactive, narrative-first analyses.
prompt-engineering
by lv416e
"Use when designing, testing, or deploying LLM prompts for applications - systematic prompt design methodology (pattern selection, structured output, evaluation, versioning) ensuring every prompt is tested against ground truth before production LLMプロンプトの設計、テスト、デプロイ時に使用 - 体系的なプロンプト設計手法（パターン選択、構造化出力、評価、バージョン管理）により、すべてのプロンプトが本番前にグランドトゥルースに対してテスト済みであることを保証"
dataverse-plugins
by DanielKerridge
Use when developing, registering, or deploying Dataverse plugins (C# server-side extensions). Covers the IPlugin interface, execution pipeline stages, entity images, common patterns (auto-numbering, cascading updates, validation), and registration/deployment. Triggers on: "plugin", "server-side logic", "business logic", "auto-number", "cascading update", "pre-operation", "post-operation", "plugin registration", "IPlugin", "execution pipeline", "plugin trace", "InvalidPluginExecutionException", "PreValidation", "PostOperation".
unit-economics
by mfwarren
Production-ready entrepreneurship skills for Claude Code — marketing, sales, operations, finance, and leadership. 24 skills built by a founder, for founders.
scanpy
by tondevrel
Scalable toolkit for analyzing single-cell gene expression data. Built on top of Anndata, focusing on clustering, trajectory inference, and visualization.
pytorch-deployment
by tondevrel
Advanced sub-skill for PyTorch focused on model productionization and deployment. Covers TorchScript (JIT/Tracing), ONNX export, LibTorch (C++ API), and inference optimization (Quantization, Pruning).
photutils
by tondevrel
An Astropy coordinated package for detecting and performing photometry of astronomical sources. Provides tools for background estimation, source detection (DAOFIND, IRAF), aperture photometry, and PSF (Point Spread Function) fitting. Use when working with astronomical image analysis, star/galaxy detection, measuring brightness (photometry), background subtraction, PSF fitting, aperture photometry, centroiding, or isophotal analysis.
cobrapy
by tondevrel
Constraints-Based Reconstruction and Analysis for Python. Used for modeling large-scale metabolic networks in microorganisms.
pyomo
by tondevrel
Python Optimization Modeling Objects. A high-level framework for formulating, solving, and analyzing optimization models. Supports Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Non-Linear Programming (NLP). Part of the COIN-OR project. Use for mathematical optimization, linear programming, mixed-integer programming, non-linear programming, strategic planning, process engineering, energy systems, supply chain optimization, stochastic programming, and solver integration with IPOPT, SCIP, Gurobi, CPLEX, or GLPK.
fastapi-streamlit
by tondevrel
Dual skill for deploying scientific models. FastAPI provides a high-performance, asynchronous web framework for building APIs with automatic documentation. Streamlit enables rapid creation of interactive data applications and dashboards directly from Python scripts. Load when working with web APIs, model serving, REST endpoints, interactive dashboards, data visualization UIs, scientific app deployment, async web frameworks, Pydantic validation, uvicorn, or building production-ready scientific tools.