Total 58,115 skills, AI & Machine Learning has 9659 skills
Showing 12 of 9659 skills
Deploys ML and LLM models on TrueFoundry with GPU inference servers (vLLM, TGI, NVIDIA NIM). Uses YAML manifests with `tfy apply`. Use when serving language models, deploying Hugging Face models, or hosting GPU-accelerated inference endpoints.
GAN-inspired Generator-Evaluator agent harness for building high-quality applications autonomously. Based on Anthropic's March 2026 harness design paper.
Visual UI annotation tool for AI agents. Drop the React toolbar into any app — humans click elements and leave feedback, agents receive structured CSS selectors, bounding boxes, and React component trees to find exact code. Supports MCP watch-loop, platform-specific hooks (Claude Code / Codex / Gemini CLI / OpenCode), webhook delivery, and autonomous self-driving critique with agent-browser.
Model configuration editor for ~/.pi/agent/models.json with multi-protocol curl testing support.
Build AI-powered chat applications with TanStack AI and React. Use when working with @tanstack/ai, @tanstack/ai-react, @tanstack/ai-client, or any TanStack AI packages. Covers useChat hook, streaming, tools (server/client/hybrid), tool approval, structured outputs, multimodal content, adapters (OpenAI, Anthropic, Gemini, Ollama, Grok), agentic cycles, devtools, and type safety patterns. Triggers on AI chat UI, function calling, LLM integration, or streaming response tasks using TanStack AI.
AI-powered search that aggregates and summarizes results from multiple sources including web, X/Twitter, Reddit, Hacker News, YouTube, ArXiv, and Wikipedia. Use this when you need a synthesized answer or curated links from across the internet and social platforms.
Use when entering orchestrator mode to manage agents via Paseo CLI
Writes rigorous mathematical proofs for ML/AI theory. Use when asked to prove a theorem, lemma, proposition, or corollary, fill in missing proof steps, formalize a proof sketch, 补全证明, 写证明, 证明某个命题, or determine whether a claimed proof can actually be completed under the stated assumptions.
Audits Claude Code context window consumption across agents, skills, MCP servers, and rules. Identifies bloat, redundant components, and produces prioritized token-savings recommendations.
PUA Loop — Autonomous Iterative Development with PUA Pressure. Runs continuously until the task is completed, no user interaction required. Combines the Ralph Loop iteration mechanism with PUA quality enforcement. Triggered by: '/pua loop', '/pua:loop', 'automatic loop', 'loop mode', 'keep running', 'automatic iteration'.
Paper Workflow: Read papers and create reading cards in one go. Accepts one or more arXiv links, paper URLs, PDFs, or paper titles. For each paper, it runs ljg-paper (generates org-format analysis) followed by ljg-card -l (generates long-form reading card PNG). Trigger this workflow when the user says '论文流', 'paper flow', '读论文并做卡片', '论文卡片', or provides multiple papers and requires both analysis and reading cards.
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.