Total 50,542 skills, AI & Machine Learning has 8483 skills
Showing 12 of 8483 skills
Run Gemini CLI for AI-powered tasks, code understanding, file operations, and automation. Free tier with Google OAuth (included in Gemini Advanced). Use for fast generation, bulk content, debugging, and research. Preferred for load balancing sub-agent work (35% weight).
Amazon Bedrock AgentCore Policy for defining agent boundaries using natural language and Cedar. Deterministic policy enforcement at the Gateway level. Use when setting agent guardrails, access control, tool permissions, or compliance rules.
Design MCP prompts to expose reusable prompt templates. Use when creating parameterized prompts in xmcp.
Enables Claude to create, manage, and organize events in Google Calendar via Playwright MCP
Cancel any active OMC mode (autopilot, ralph, ultrawork, ecomode, ultraqa, swarm, ultrapilot, pipeline, team)
Parallel autopilot with file ownership partitioning
Save notes to notepad.md for compaction resilience
Implement AI image generation capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to create images from text descriptions, generate visual content, create artwork, design assets, or build applications with AI-powered image creation. Supports multiple image sizes and returns base64 encoded images. Also includes CLI tool for quick image generation.
Helps coding agents use vit to discover, follow, skim, and ship software capabilities (caps) over ATProto. Activates when the user mentions vit, beacons, caps, shipping, skimming, following, vetting, or social coding.
Wandb Experiment Logger - Auto-activating skill for ML Training. Triggers on: wandb experiment logger, wandb experiment logger Part of the ML Training skill category.
Guidance for creating standalone CLI tools that perform neural network inference by extracting PyTorch model weights and reimplementing inference in C/C++. This skill applies when tasks involve converting PyTorch models to standalone executables, extracting model weights to portable formats (JSON), implementing neural network forward passes in C/C++, or creating CLI tools that load images and run inference without Python dependencies.
Improve and rewrite user prompts to reduce ambiguity and improve LLM output quality. Use when a user asks to optimize, refine, clarify, or rewrite a prompt for better results, or when the request is about prompt optimization or prompt rewriting.