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Reusable instructions for compatible AI agents.
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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.
Autonomous biomedical AI agent framework for executing complex research tasks across genomics, drug discovery, molecular biology, and clinical analysis. Use this skill when conducting multi-step biomedical research including CRISPR screening design, single-cell RNA-seq analysis, ADMET prediction,...
CLI/Python toolkit for rapid bioinformatics queries. Preferred for quick BLAST searches. Access to 20+ databases: gene info (Ensembl/UniProt), AlphaFold, ARCHS4, Enrichr, OpenTargets, COSMIC, genome downloads. For advanced BLAST/batch processing, use biopython. For multi-database integration, use...
Build and query embedded GraphRAG knowledge graphs with DuckDB-backed vector, full-text, and hybrid search. Use when the user wants to store entities and relations, run RAG over a graph, extract knowledge graphs from text with DSPy, run graph algorithms (PageRank, centrality, components), merge/u...
An MCP server that provides on-demand skill loading for AI coding assistants.
An MCP server that provides on-demand skill loading for AI coding assistants.
Master Moon Dev's Ai Agents Github with 48+ specialized agents, multi-exchange support, LLM abstraction, and autonomous trading capabilities across crypto markets
LLM API 使用成本优化模式 —— 基于任务复杂度的模型路由、预算跟踪、重试逻辑和提示缓存。
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-p...
Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library
Best practices for using the oracle CLI (prompt + file bundling, engines, sessions, and file attachment patterns).
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.
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