Total 55,501 skills, AI & Machine Learning has 9232 skills
Showing 12 of 9232 skills
Transform user requests into detailed, precise prompts for AI models. Use when users say "promptify", "promptify this", or explicitly request prompt engineering or improvement of their request for better AI responses.
Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.
Molecular featurization for ML (100+ featurizers). ECFP, MACCS, descriptors, pretrained models (ChemBERTa), convert SMILES to features, for QSAR and molecular ML.
This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.
Vercel AI SDK for building chat interfaces with streaming. Use when implementing useChat hook, handling tool calls, streaming responses, or building chat UI. Triggers on useChat, @ai-sdk/react, UIMessage, ChatStatus, streamText, toUIMessageStreamResponse, addToolOutput, onToolCall, sendMessage.
Generate images and videos using Kling AI API. Use when creating AI-generated images from text prompts, converting images to videos, or generating videos from text descriptions.
Use when "CLIP", "Whisper", "Stable Diffusion", "SDXL", "speech-to-text", "text-to-image", "image generation", "transcription", "zero-shot classification", "image-text similarity", "inpainting", "ControlNet"
Production MLOps and ML/LLM/agent security skill for deploying and operating ML systems in production (registry + CI/CD, serving, monitoring/drift, evaluation loops, incident response/runbooks, and governance), including GenAI security (prompt injection, jailbreaks, RAG security, privacy, and supply chain).
Automate AI ML API tasks via Rube MCP (Composio). Always search tools first for current schemas.
Use this skill for ANY question about CREATING evaluators. Covers creating custom metrics, LLM as Judge evaluators, code-based evaluators, and uploading evaluation logic to LangSmith. Includes basic usage of evaluators to run evaluations.
Build trustless escrow for agent-to-agent transactions on Solana and Base. Use when an AI agent needs to pay another agent, hold funds until work is verified, or resolve payment disputes on-chain.
Model Context Protocol (MCP) サーバーの作成・管理ガイド。カスタムツールの追加方法。 使用タイミング: (1) Claude Codeにカスタムツールを追加したい時 (2) 外部サービス連携時 (3) プロジェクト固有の自動化ツールを作りたい時 (4) MCPサーバーの設定方法を知りたい時。 トリガー例: 「MCPサーバーを作って」「カスタムツールを追加」「MCP設定」 「外部APIをツール化」「テストランナーMCP」