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Found 1,564 Skills
Eino framework overview, concepts, and navigation. Use when a user asks general questions about Eino, needs help getting started, wants to understand the architecture, or is unsure which Eino skill to use. Eino is a Go framework for building LLM applications with components, orchestration graphs, and an agent development kit.
Opik observability for LLM agents — Agent Configuration, Local Runner (opik connect), Evaluation Suites, threads, integrations. Use for "configure my agent", "connect my agent", "evaluate my agent" or "integrate with Opik".
Manage Databricks Model Serving endpoints via CLI. Use when asked to create, configure, query, or manage model serving endpoints for LLM inference, custom models, or external models.
Design cross-border logistics strategies including direct mail, overseas warehousing, and bonded warehouse models for international e-commerce. Use this skill when the user needs to ship products internationally, choose a logistics model for cross-border sales, optimize shipping costs, or set up fulfillment in a foreign market — even if they say 'ship to Southeast Asia', 'overseas warehouse vs direct shipping', 'customs clearance', or 'reduce international shipping time'.
Design patterns for the Langroid multi-agent LLM framework. Covers agent configuration, tools, task control, and integrations.
Compiles and extracts session knowledge into a living, interconnected LLM-Wiki. Instead of writing isolated logs, it identifies key entities, updates cross-referenced topic files in docs/knowledgelib/, and maintains an index and chronological log. Use this to ensure persistent, compounding project knowledge.
Provides guidance for LLM post-training with RL using slime, a Megatron+SGLang framework. Use when training GLM models, implementing custom data generation workflows, or needing tight Megatron-LM integration for RL scaling.
Generative Engine Optimization review: evaluate your content's visibility to AI-powered search engines — citation-worthiness, content structure, authority signals, llms.txt, entity clarity, and AI retrieval readiness.
Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required.
Local proxy that lets OpenAI Codex CLI/desktop talk to MiMo, DeepSeek, and other LLMs via Responses API translation
A curated collection of research papers and resources on agentic reasoning for Large Language Models, organized by planning, tool use, search, self-evolution, and multi-agent systems.
This skill should be used when the user asks to "quantize a model", "run PTQ", "post-training quantization", "NVFP4 quantization", "FP8 quantization", "INT8 quantization", "INT4 AWQ", "quantize LLM", "quantize MoE", "quantize VLM", or needs to produce a quantized HuggingFace or TensorRT-LLM checkpoint from a pretrained model using ModelOpt.