Total 50,678 skills, AI & Machine Learning has 8495 skills
Showing 12 of 8495 skills
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.
Master of LLM Economic Orchestration, specialized in Google GenAI (Gemini 3), Context Caching, and High-Fidelity Token Engineering.
Interleaves context from recently active Claude/Amp threads into current activity via random walk.
Design and evaluate compression strategies for long-running sessions
Applies general engineering conventions optimized for AI agents. Use when creating or refactoring codebases and you need strict file discipline, clear module boundaries, naming/layout rules, and anti-pattern avoidance.
Guidance for text embedding retrieval tasks using sentence transformers or similar embedding models. This skill should be used when the task involves loading documents, encoding text with embedding models, computing similarity scores (cosine similarity), and retrieving/ranking documents based on semantic similarity to a query. Applies to MTEB benchmark tasks, document retrieval, semantic search, and text similarity ranking.
Guidance for optimizing MuJoCo MJCF model files for simulation performance while maintaining numerical accuracy. This skill should be used when tuning physics simulation parameters, optimizing MuJoCo XML configurations, or balancing speed vs accuracy tradeoffs in robotics simulations.
Integration guide for Morph's WarpGrep (fast agentic code search) and Fast Apply (10,500 tok/s code editing). Use when building coding agents that need fast, accurate code search or need to apply AI-generated edits to code efficiently. Particularly useful for large codebases, deep logic queries, bug tracing, and code path analysis.
Guidance for extracting weight matrices from black-box ReLU neural networks using only input-output queries. This skill applies when tasked with recovering internal parameters (weights, biases) of a neural network that can only be queried for outputs, particularly two-layer ReLU networks. Use this skill for model extraction, model stealing, or neural network reverse engineering tasks.
Suggest agent rules analyzing the session history and the current repository.
Train ML models with scikit-learn, PyTorch, TensorFlow. Use for classification/regression, neural networks, hyperparameter tuning, or encountering overfitting, underfitting, convergence issues.
Build agents that generate creative content including music, memes, podcasts, and multimedia. Covers generative models, content synthesis, style transfer, and creative control. Use when building creative assistants, automated content creators, multimedia generators, or artistic AI systems.