Total 44,222 skills, AI & Machine Learning has 7033 skills
Showing 12 of 7033 skills
Master dispatcher for all MLflow workflows. Use this skill when the user wants to do anything with MLflow — tracing, evaluating, debugging, or improving an agent. Routes to the right MLflow sub-skill automatically. Triggers on: "use mlflow", "help with mlflow", "mlflow agent", "add mlflow to my project", "trace my agent", "evaluate my agent", or any MLflow task without a specific skill in mind.
Expert skill for OmniVoice, a massively multilingual zero-shot TTS model supporting 600+ languages with voice cloning and voice design capabilities.
Deep dive into Claude Code source code to learn production-grade AI agent architecture patterns
Agent skill to convert any arxiv paper into a citation-anchored, working Python implementation with ambiguity auditing
Tong Jincheng Perspective Skill - Analyze interpersonal relationships, romantic issues and human nature insights using the thinking framework of the 'Affectionate Grandmaster'
Build and use free-code, the open-source fork of Claude Code CLI with telemetry removed, guardrails stripped, and all experimental features unlocked.
On-device, real-time multimodal AI voice and vision assistant powered by Gemma 4 E2B and Kokoro TTS, running entirely locally via FastAPI WebSocket server.
AI-powered job search pipeline built on Claude Code with 14 skill modes, Go dashboard, PDF generation, batch processing, and portal scanning.
Query AI Engineer Europe 2026 conference data — speakers, talks, schedule, and more. Use when building apps, AI integrations, or tools on top of conference data. Provides REST endpoints (JSON + plain text), an MCP server for agent tool calls, and a CLI. Covers 150+ talks, 150+ speakers, workshops, and the full 3-day schedule.
Use when designing and building knowledge graphs from unstructured data. Invoke when user mentions entity extraction, schema design, LPG vs RDF, graph data model, ontology alignment, knowledge graph construction, or building a KG for RAG. Provides extraction pipelines, schema patterns, and data model selection guidance.
Autonomous LLM training optimization with GPU support. Runs 5-minute training experiments, measures val_bpb, keeps improvements or reverts — repeat forever. Use this skill when the user asks to "train a model autonomously", "optimize LLM training", "run ML experiments", "autoresearch with GPU", "optimize val_bpb", "autonomous ML training", "LLM pretraining loop", "setup ML autoresearch", "GPU training experiments", "pretrain from scratch", "speed up training", "lower my loss", "GPU optimization", "CUDA training", or mentions "train.py", "prepare.py", "bits per byte", "val_bpb", "NVIDIA GPU training", "RTX training", "H100 training", "autonomous model training", "consumer GPU training", "low VRAM training". Always use this skill when the user wants to autonomously optimize any ML training metric.
Retrieve a GitHub issue using the `gh` CLI, analyze it, and spawn a PM + developer team to address it. Accepts an issue URL, issue number, or `owner/repo#number`.