Total 50,613 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
AI Intelligent Email Assistant that analyzes email content to generate summaries, determines whether a reply is needed, and creates professional reply drafts based on context.
Develops custom FiftyOne plugins (operators and panels) from scratch. Use when creating plugins, extending FiftyOne with custom operators, building interactive panels, or integrating external APIs.
Coordinate parallel feature development with file ownership strategies, conflict avoidance rules, and integration patterns for multi-agent implementation. Use this skill when decomposing features for parallel development, establishing file ownership boundaries, or managing integration between parallel work streams.
Agent Skill: Generate and maintain AGENTS.md files following the public agents.md convention. Use when creating AI agent documentation, onboarding guides, or standardizing agent patterns. By Netresearch.
Complete guide to using @openserv-labs/client for managing agents, workflows, triggers, and tasks on the OpenServ Platform. Covers provisioning, authentication, x402 payments, ERC-8004 on-chain identity, and the full Platform API. IMPORTANT - Always read the companion skill openserv-agent-sdk alongside this skill, as both packages are required to build any agent. Read reference.md for the full API reference.
Use when conversation context is too long, hitting token limits, or responses are degrading. Compresses history while preserving critical information using anchored summarization and probe-based validation.
Deep learning framework development with tinygrad - a minimal tensor library with autograd, JIT compilation, and multi-device support. Use when writing neural networks, training models, implementing tensor operations, working with UOps/PatternMatcher for graph transformations, or contributing to tinygrad internals. Triggers on tinygrad imports, Tensor operations, nn modules, optimizer usage, schedule/codegen work, or device backends.
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.
Scientific research and analysis skills
Interleaves context from recently active Claude/Amp threads into current activity via random walk.
Design and evaluate compression strategies for long-running sessions