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Found 1,564 Skills
Build LLM-powered chat apps with the right SDK — Anthropic SDK / Claude API (prompt caching, thinking, tool use, batch, files, citations, memory, model migrations) AND Vercel AI SDK (useChat, streamText, tool calls, UIMessage, ChatStatus, addToolOutput). Use when implementing chat interfaces, tuning Claude features, migrating between Claude model versions, or wiring up streaming with @ai-sdk/react.
Router skill for LLMQuant Data primitive workflows. Use when the user needs SEC filings, 13F holders, macro snapshots, or source-grounded macro briefs.
Router skill for LLMQuant market-intelligence workflows. Use when the user needs macro views, market sentiment dashboards, or event probability signals.
USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.
Step-by-step guide for adding support for a new LLM in Dust. Use when adding a new model, or updating a previous one.
Optimize programmatic SEO pages for visibility and citation in AI-generated answers from ChatGPT, Perplexity, Google AI Overviews, and other LLM-powered search. Use when optimizing for LLM citation, implementing llms.txt, configuring AI crawler access, structuring content for AI extraction, or when the user asks about generative engine optimization (GEO), AI search visibility, or getting cited by AI.
Master local LLM inference, model selection, VRAM optimization, and local deployment using Ollama, llama.cpp, vLLM, and LM Studio. Expert in quantization formats (GGUF, EXL2) and local AI privacy.
Review, design, and refactor TensorRT-LLM PyTorch MoE code for architecture fit, clean code, maintainability, and testability. Always use for any modification, review, refactor, or design planning that touches MoE modules, including tensorrt_llm/_torch/modules/fused_moe, ConfigurableMoE, MoE backends, MoEScheduler/moe_scheduler.py, forward execution/chunking, communication strategies, EPLB, quantization/weight handling, routing, factories, MoE docs, or MoE tests. Also use when the user asks whether a MoE design follows the current architecture or whether a MoE refactor is reasonable.
Router skill for LLMQuant macro workflows. Use when the user needs macro dashboards, Fed or central-bank previews, inflation and growth context, liquidity, or macro-to-portfolio impact analysis.
Router skill for LLMQuant options workflows. Use when the user needs IV rank, option scoring, strategy construction, Greeks, P&L simulation, volatility surface, unusual activity, earnings IV crush, backtests, or hedges.
List available large language models and send chat completion requests programmatically. Use this skill when you need to call an LLM within a snippet, including model comparison, visual understanding, batch inference, and model performance testing.
Run 250+ AI apps via inference.sh CLI - image generation, video creation, LLMs, search, 3D, Twitter automation. Models: FLUX, Veo, Gemini, Grok, Claude, Seedance, OmniHuman, Tavily, Exa, OpenRouter, and many more. Use when running AI apps, generating images/videos, calling LLMs, web search, or automating Twitter. Triggers: inference.sh, infsh, ai model, run ai, serverless ai, ai api, flux, veo, claude api, image generation, video generation, openrouter, tavily, exa search, twitter api, grok